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chore: upgrade DataFusion family, again (#7578)

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* chore: upgrade DataFusion family

Signed-off-by: luofucong <luofc@foxmail.com>

* chore: switch to released version of datafusion-pg-catalog

---------

Signed-off-by: luofucong <luofc@foxmail.com>
Co-authored-by: Ning Sun <sunning@greptime.com>
Co-authored-by: Ning Sun <sunng@protonmail.com>
This commit is contained in:
LFC
2026-03-03 15:36:39 +08:00
committed by GitHub
parent aab839b6e4
commit b2074e3863
135 changed files with 1589 additions and 2555 deletions
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1291
Cargo.lock generated
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File diff suppressed because it is too large Load Diff

76
Cargo.toml
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@@ -100,13 +100,13 @@ rust.unexpected_cfgs = { level = "warn", check-cfg = ['cfg(tokio_unstable)'] }
# See for more detaiils: https://github.com/rust-lang/cargo/issues/11329
ahash = { version = "0.8", features = ["compile-time-rng"] }
aquamarine = "0.6"
arrow = { version = "57.0", features = ["prettyprint"] }
arrow-array = { version = "57.0", default-features = false, features = ["chrono-tz"] }
arrow-buffer = "57.0"
arrow-cast = "57.0"
arrow-flight = "57.0"
arrow-ipc = { version = "57.0", default-features = false, features = ["lz4", "zstd"] }
arrow-schema = { version = "57.0", features = ["serde"] }
arrow = { version = "57.2", features = ["prettyprint"] }
arrow-array = { version = "57.2", default-features = false, features = ["chrono-tz"] }
arrow-buffer = "57.2"
arrow-cast = "57.2"
arrow-flight = "57.2"
arrow-ipc = { version = "57.2", default-features = false, features = ["lz4", "zstd"] }
arrow-schema = { version = "57.2", features = ["serde"] }
async-stream = "0.3"
async-trait = "0.1"
# Remember to update axum-extra, axum-macros when updating axum
@@ -127,20 +127,20 @@ const_format = "0.2"
criterion = "0.7"
crossbeam-utils = "0.8"
dashmap = "6.1"
datafusion = "51.0"
datafusion-common = "51.0"
datafusion-datasource = "51.0"
datafusion-expr = "51.0"
datafusion-functions = "51.0"
datafusion-functions-aggregate-common = "51.0"
datafusion-functions-window-common = "51.0"
datafusion-optimizer = "51.0"
datafusion-orc = { git = "https://github.com/GreptimeTeam/datafusion-orc.git", rev = "35f2e04bf81f2ab7b6f86c0450d6a77b7098d43e" }
datafusion-pg-catalog = "0.13"
datafusion-physical-expr = "51.0"
datafusion-physical-plan = "51.0"
datafusion-sql = "51.0"
datafusion-substrait = "51.0"
datafusion = "52.1"
datafusion-common = "52.1"
datafusion-datasource = "52.1"
datafusion-expr = "52.1"
datafusion-functions = "52.1"
datafusion-functions-aggregate-common = "52.1"
datafusion-functions-window-common = "52.1"
datafusion-optimizer = "52.1"
datafusion-orc = "0.7"
datafusion-pg-catalog = "0.15.1"
datafusion-physical-expr = "52.1"
datafusion-physical-plan = "52.1"
datafusion-sql = "52.1"
datafusion-substrait = "52.1"
deadpool = "0.12"
deadpool-postgres = "0.14"
derive_builder = "0.20"
@@ -187,7 +187,7 @@ otel-arrow-rust = { git = "https://github.com/GreptimeTeam/otel-arrow", rev = "5
"server",
] }
parking_lot = "0.12"
parquet = { version = "57.0", default-features = false, features = ["arrow", "async", "object_store"] }
parquet = { version = "57.2", default-features = false, features = ["arrow", "async", "object_store"] }
paste = "1.0"
pin-project = "1.0"
pretty_assertions = "1.4.0"
@@ -226,7 +226,7 @@ simd-json = "0.15"
similar-asserts = "1.6.0"
smallvec = { version = "1", features = ["serde"] }
snafu = "0.8"
sqlparser = { version = "0.59.0", default-features = false, features = ["std", "visitor", "serde"] }
sqlparser = { version = "0.61.0", default-features = false, features = ["std", "visitor", "serde"] }
sqlx = { version = "0.8", default-features = false, features = [
"any",
"macros",
@@ -331,21 +331,21 @@ git = "https://github.com/GreptimeTeam/greptime-meter.git"
rev = "5618e779cf2bb4755b499c630fba4c35e91898cb"
[patch.crates-io]
datafusion = { git = "https://github.com/GreptimeTeam/datafusion.git", rev = "7143b2fc4492a7970774583ed0997a459f3e5c05" }
datafusion-common = { git = "https://github.com/GreptimeTeam/datafusion.git", rev = "7143b2fc4492a7970774583ed0997a459f3e5c05" }
datafusion-expr = { git = "https://github.com/GreptimeTeam/datafusion.git", rev = "7143b2fc4492a7970774583ed0997a459f3e5c05" }
datafusion-functions = { git = "https://github.com/GreptimeTeam/datafusion.git", rev = "7143b2fc4492a7970774583ed0997a459f3e5c05" }
datafusion-functions-aggregate-common = { git = "https://github.com/GreptimeTeam/datafusion.git", rev = "7143b2fc4492a7970774583ed0997a459f3e5c05" }
datafusion-functions-window-common = { git = "https://github.com/GreptimeTeam/datafusion.git", rev = "7143b2fc4492a7970774583ed0997a459f3e5c05" }
datafusion-optimizer = { git = "https://github.com/GreptimeTeam/datafusion.git", rev = "7143b2fc4492a7970774583ed0997a459f3e5c05" }
datafusion-physical-expr = { git = "https://github.com/GreptimeTeam/datafusion.git", rev = "7143b2fc4492a7970774583ed0997a459f3e5c05" }
datafusion-physical-expr-common = { git = "https://github.com/GreptimeTeam/datafusion.git", rev = "7143b2fc4492a7970774583ed0997a459f3e5c05" }
datafusion-physical-plan = { git = "https://github.com/GreptimeTeam/datafusion.git", rev = "7143b2fc4492a7970774583ed0997a459f3e5c05" }
datafusion-pg-catalog = { git = "https://github.com/GreptimeTeam/datafusion-postgres.git", rev = "f675927a79cd714a8eeb438b0d3015cd54d4e60a" }
datafusion-datasource = { git = "https://github.com/GreptimeTeam/datafusion.git", rev = "7143b2fc4492a7970774583ed0997a459f3e5c05" }
datafusion-sql = { git = "https://github.com/GreptimeTeam/datafusion.git", rev = "7143b2fc4492a7970774583ed0997a459f3e5c05" }
datafusion-substrait = { git = "https://github.com/GreptimeTeam/datafusion.git", rev = "7143b2fc4492a7970774583ed0997a459f3e5c05" }
sqlparser = { git = "https://github.com/GreptimeTeam/sqlparser-rs.git", rev = "d7d95a44889e099e32d78e9bad9bc00598faef28" } # on branch v0.59.x
datafusion = { git = "https://github.com/GreptimeTeam/datafusion.git", rev = "02b82535e0160c4545667f36a03e1ff9d1d2e51f" }
datafusion-common = { git = "https://github.com/GreptimeTeam/datafusion.git", rev = "02b82535e0160c4545667f36a03e1ff9d1d2e51f" }
datafusion-expr = { git = "https://github.com/GreptimeTeam/datafusion.git", rev = "02b82535e0160c4545667f36a03e1ff9d1d2e51f" }
datafusion-functions = { git = "https://github.com/GreptimeTeam/datafusion.git", rev = "02b82535e0160c4545667f36a03e1ff9d1d2e51f" }
datafusion-functions-aggregate-common = { git = "https://github.com/GreptimeTeam/datafusion.git", rev = "02b82535e0160c4545667f36a03e1ff9d1d2e51f" }
datafusion-functions-window-common = { git = "https://github.com/GreptimeTeam/datafusion.git", rev = "02b82535e0160c4545667f36a03e1ff9d1d2e51f" }
datafusion-optimizer = { git = "https://github.com/GreptimeTeam/datafusion.git", rev = "02b82535e0160c4545667f36a03e1ff9d1d2e51f" }
datafusion-physical-expr = { git = "https://github.com/GreptimeTeam/datafusion.git", rev = "02b82535e0160c4545667f36a03e1ff9d1d2e51f" }
datafusion-physical-expr-common = { git = "https://github.com/GreptimeTeam/datafusion.git", rev = "02b82535e0160c4545667f36a03e1ff9d1d2e51f" }
datafusion-physical-plan = { git = "https://github.com/GreptimeTeam/datafusion.git", rev = "02b82535e0160c4545667f36a03e1ff9d1d2e51f" }
datafusion-datasource = { git = "https://github.com/GreptimeTeam/datafusion.git", rev = "02b82535e0160c4545667f36a03e1ff9d1d2e51f" }
datafusion-sql = { git = "https://github.com/GreptimeTeam/datafusion.git", rev = "02b82535e0160c4545667f36a03e1ff9d1d2e51f" }
datafusion-substrait = { git = "https://github.com/GreptimeTeam/datafusion.git", rev = "02b82535e0160c4545667f36a03e1ff9d1d2e51f" }
sqlparser = { git = "https://github.com/GreptimeTeam/sqlparser-rs.git", rev = "2aefa08a8d69c96eec2d6d6703598a009bba6e4c" } # on branch v0.61.x
[profile.release]
debug = 1

2
flake.nix
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@@ -15,6 +15,7 @@
let
pkgs = nixpkgs.legacyPackages.${system};
buildInputs = with pkgs; [
libz.out
];
lib = nixpkgs.lib;
rustToolchain = fenix.packages.${system}.fromToolchainName {
@@ -53,6 +54,7 @@
NIX_HARDENING_ENABLE = "";
LD_LIBRARY_PATH = with pkgs; lib.makeLibraryPath [
stdenv.cc.cc.lib
libz
];
};
});

2
src/common/datasource/Cargo.toml
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@@ -10,7 +10,7 @@ workspace = true
[dependencies]
arrow.workspace = true
arrow-schema.workspace = true
async-compression = { version = "0.3", features = [
async-compression = { version = "0.4", features = [
"bzip2",
"gzip",
"xz",

7
src/common/datasource/src/error.rs
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@@ -203,8 +203,8 @@ pub enum Error {
error: parquet::errors::ParquetError,
},
#[snafu(display("Failed to build file stream"))]
BuildFileStream {
#[snafu(transparent)]
DataFusion {
#[snafu(implicit)]
location: Location,
#[snafu(source)]
@@ -241,8 +241,9 @@ impl ErrorExt for Error {
| ReadRecordBatch { .. }
| WriteRecordBatch { .. }
| EncodeRecordBatch { .. }
| BuildFileStream { .. }
| OrcReader { .. } => StatusCode::Unexpected,
DataFusion { .. } => StatusCode::Internal,
}
}

9
src/common/datasource/src/file_format.rs
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@@ -313,16 +313,13 @@ pub async fn file_to_stream(
filename.to_string(),
0,
)]))
.with_projection_indices(projection)
.with_projection_indices(projection)?
.with_file_compression_type(df_compression)
.build();
let store = Arc::new(OpendalStore::new(store.clone()));
let file_opener = file_source
.with_projection(&config)
.create_file_opener(store, &config, 0);
let stream = FileStream::new(&config, 0, file_opener, &ExecutionPlanMetricsSet::new())
.context(error::BuildFileStreamSnafu)?;
let file_opener = config.file_source().create_file_opener(store, &config, 0)?;
let stream = FileStream::new(&config, 0, file_opener, &ExecutionPlanMetricsSet::new())?;
Ok(Box::pin(stream))
}

5
src/common/datasource/src/file_format/tests.rs
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@@ -46,7 +46,10 @@ struct Test<'a> {
impl Test<'_> {
async fn run(self, store: &ObjectStore) {
let store = Arc::new(object_store_opendal::OpendalStore::new(store.clone()));
let file_opener = self.file_source.create_file_opener(store, &self.config, 0);
let file_opener = self
.file_source
.create_file_opener(store, &self.config, 0)
.unwrap();
let result = FileStream::new(
&self.config,

13
src/common/datasource/src/test_util.rs
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@@ -104,6 +104,7 @@ pub async fn setup_stream_to_json_test(origin_path: &str, threshold: impl Fn(usi
schema.clone(),
FileCompressionType::UNCOMPRESSED,
Arc::new(object_store_opendal::OpendalStore::new(store.clone())),
true,
);
let size = store.read(origin_path).await.unwrap().len();
@@ -154,11 +155,13 @@ pub async fn setup_stream_to_csv_test(
let config = scan_config(None, origin_path, csv_source.clone());
let size = store.read(origin_path).await.unwrap().len();
let csv_opener = csv_source.create_file_opener(
Arc::new(object_store_opendal::OpendalStore::new(store.clone())),
&config,
0,
);
let csv_opener = csv_source
.create_file_opener(
Arc::new(object_store_opendal::OpendalStore::new(store.clone())),
&config,
0,
)
.unwrap();
let stream = FileStream::new(&config, 0, csv_opener, &ExecutionPlanMetricsSet::new()).unwrap();
let (tmp_store, dir) = test_tmp_store("test_stream_to_csv");

8
src/common/function/src/aggrs/aggr_wrapper/tests.rs
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@@ -61,18 +61,18 @@ use crate::scalars::uddsketch_calc::UddSketchCalcFunction;
pub struct MockInputExec {
input: Vec<RecordBatch>,
schema: SchemaRef,
properties: PlanProperties,
properties: Arc<PlanProperties>,
}
impl MockInputExec {
pub fn new(input: Vec<RecordBatch>, schema: SchemaRef) -> Self {
Self {
properties: PlanProperties::new(
properties: Arc::new(PlanProperties::new(
EquivalenceProperties::new(schema.clone()),
Partitioning::UnknownPartitioning(1),
EmissionType::Incremental,
Boundedness::Bounded,
),
)),
input,
schema,
}
@@ -94,7 +94,7 @@ impl ExecutionPlan for MockInputExec {
self
}
fn properties(&self) -> &PlanProperties {
fn properties(&self) -> &Arc<PlanProperties> {
&self.properties
}

2
src/common/function/src/aggrs/count_hash.rs
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@@ -428,7 +428,7 @@ impl Accumulator for CountHashAccumulator {
&self.random_state,
&mut self.batch_hashes,
)?;
for hash in hashes.as_slice() {
for hash in hashes {
self.values.insert(*hash);
}
Ok(())

2
src/common/query/src/logical_plan.rs
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@@ -48,7 +48,7 @@ pub fn rename_logical_plan_columns(
plan.schema().qualified_field_from_column(&old_column)?;
for (qualifier, field) in plan.schema().iter() {
if qualifier.eq(&qualifier_rename) && field.as_ref() == field_rename {
if qualifier.eq(&qualifier_rename) && field == field_rename {
projection.push(col(Column::from((qualifier, field))).alias(new_name));
}
}

8
src/common/query/src/stream.rs
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@@ -32,7 +32,7 @@ pub struct StreamScanAdapter {
stream: Mutex<Option<SendableRecordBatchStream>>,
schema: SchemaRef,
arrow_schema: ArrowSchemaRef,
properties: PlanProperties,
properties: Arc<PlanProperties>,
output_ordering: Option<Vec<PhysicalSortExpr>>,
}
@@ -49,12 +49,12 @@ impl StreamScanAdapter {
pub fn new(stream: SendableRecordBatchStream) -> Self {
let schema = stream.schema();
let arrow_schema = schema.arrow_schema().clone();
let properties = PlanProperties::new(
let properties = Arc::new(PlanProperties::new(
EquivalenceProperties::new(arrow_schema.clone()),
Partitioning::UnknownPartitioning(1),
EmissionType::Incremental,
Boundedness::Bounded,
);
));
Self {
stream: Mutex::new(Some(stream)),
@@ -91,7 +91,7 @@ impl ExecutionPlan for StreamScanAdapter {
self.arrow_schema.clone()
}
fn properties(&self) -> &PlanProperties {
fn properties(&self) -> &Arc<PlanProperties> {
&self.properties
}

3
src/datatypes/src/value.rs
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@@ -1229,7 +1229,8 @@ impl TryFrom<ScalarValue> for Value {
| ScalarValue::Utf8View(_)
| ScalarValue::BinaryView(_)
| ScalarValue::Map(_)
| ScalarValue::Date64(_) => {
| ScalarValue::Date64(_)
| ScalarValue::RunEndEncoded(_, _, _) => {
return error::UnsupportedArrowTypeSnafu {
arrow_type: v.data_type(),
}

3
src/datatypes/src/vectors/helper.rs
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@@ -256,7 +256,8 @@ impl Helper {
| ScalarValue::Utf8View(_)
| ScalarValue::BinaryView(_)
| ScalarValue::Map(_)
| ScalarValue::Date64(_) => {
| ScalarValue::Date64(_)
| ScalarValue::RunEndEncoded(_, _, _) => {
return error::ConversionSnafu {
from: format!("Unsupported scalar value: {value}"),
}

9
src/file-engine/src/error.rs
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@@ -178,8 +178,8 @@ pub enum Error {
location: Location,
},
#[snafu(display("Failed to extract column from filter"))]
ExtractColumnFromFilter {
#[snafu(transparent)]
DataFusion {
#[snafu(source)]
error: DataFusionError,
#[snafu(implicit)]
@@ -225,8 +225,9 @@ impl ErrorExt for Error {
| ManifestExists { .. }
| BuildStream { .. }
| ParquetScanPlan { .. }
| UnexpectedEngine { .. }
| ExtractColumnFromFilter { .. } => StatusCode::Unexpected,
| UnexpectedEngine { .. } => StatusCode::Unexpected,
DataFusion { .. } => StatusCode::Internal,
}
}

8
src/file-engine/src/query.rs
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@@ -37,10 +37,7 @@ use snafu::{GenerateImplicitData, ResultExt, ensure};
use store_api::storage::ScanRequest;
use self::file_stream::ScanPlanConfig;
use crate::error::{
BuildBackendSnafu, ExtractColumnFromFilterSnafu, ProjectSchemaSnafu,
ProjectionOutOfBoundsSnafu, Result,
};
use crate::error::{BuildBackendSnafu, ProjectSchemaSnafu, ProjectionOutOfBoundsSnafu, Result};
use crate::region::FileRegion;
impl FileRegion {
@@ -126,8 +123,7 @@ impl FileRegion {
let mut aux_column_set = HashSet::new();
for scan_filter in scan_filters {
df_logical_expr_utils::expr_to_columns(scan_filter, &mut aux_column_set)
.context(ExtractColumnFromFilterSnafu)?;
df_logical_expr_utils::expr_to_columns(scan_filter, &mut aux_column_set)?;
let all_file_columns = aux_column_set
.iter()

6
src/file-engine/src/query/file_stream.rs
View File

@@ -56,7 +56,7 @@ fn build_record_batch_stream(
let config =
FileScanConfigBuilder::new(ObjectStoreUrl::local_filesystem(), file_source.clone())
.with_projection_indices(scan_plan_config.projection.cloned())
.with_projection_indices(scan_plan_config.projection.cloned())?
.with_limit(limit)
.with_file_group(FileGroup::new(files))
.build();
@@ -65,7 +65,7 @@ fn build_record_batch_stream(
scan_plan_config.store.clone(),
));
let file_opener = file_source.create_file_opener(store, &config, 0);
let file_opener = config.file_source().create_file_opener(store, &config, 0)?;
let stream = FileStream::new(
&config,
0, // partition: hard-code
@@ -146,7 +146,7 @@ fn new_parquet_stream_with_exec_plan(
let file_scan_config =
FileScanConfigBuilder::new(ObjectStoreUrl::local_filesystem(), Arc::new(parquet_source))
.with_file_group(file_group)
.with_projection_indices(projection.cloned())
.with_projection_indices(projection.cloned())?
.with_limit(*limit)
.build();

10
src/mito2/src/memtable/bulk/row_group_reader.rs
View File

@@ -21,7 +21,7 @@ use datatypes::arrow::error::ArrowError;
use parquet::arrow::arrow_reader::{ParquetRecordBatchReader, RowGroups, RowSelection};
use parquet::arrow::{FieldLevels, ProjectionMask, parquet_to_arrow_field_levels};
use parquet::column::page::{PageIterator, PageReader};
use parquet::file::metadata::ParquetMetaData;
use parquet::file::metadata::{ParquetMetaData, RowGroupMetaData};
use snafu::ResultExt;
use crate::error;
@@ -103,6 +103,14 @@ impl RowGroups for MemtableRowGroupPageFetcher<'_> {
reader: Some(self.column_page_reader(i)),
}))
}
fn row_groups(&self) -> Box<dyn Iterator<Item = &RowGroupMetaData> + '_> {
Box::new(std::iter::once(self.base.row_group_metadata()))
}
fn metadata(&self) -> &ParquetMetaData {
self.base.parquet_metadata()
}
}
impl RowGroupReaderContext for BulkIterContextRef {

39
src/mito2/src/sst/parquet/row_group.rs
View File

@@ -205,7 +205,8 @@ impl ParquetFetchMetrics {
}
pub(crate) struct RowGroupBase<'a> {
metadata: &'a RowGroupMetaData,
parquet_metadata: &'a ParquetMetaData,
row_group_idx: usize,
pub(crate) offset_index: Option<&'a [OffsetIndexMetaData]>,
/// Compressed page of each column.
column_chunks: Vec<Option<Arc<ColumnChunkData>>>,
@@ -225,7 +226,8 @@ impl<'a> RowGroupBase<'a> {
.map(|x| x[row_group_idx].as_slice());
Self {
metadata,
parquet_metadata: parquet_meta,
row_group_idx,
offset_index,
column_chunks: vec![None; metadata.columns().len()],
row_count: metadata.num_rows() as usize,
@@ -244,7 +246,7 @@ impl<'a> RowGroupBase<'a> {
let ranges = self
.column_chunks
.iter()
.zip(self.metadata.columns())
.zip(self.row_group_metadata().columns())
.enumerate()
.filter(|&(idx, (chunk, _chunk_meta))| chunk.is_none() && projection.leaf_included(idx))
.flat_map(|(idx, (_chunk, chunk_meta))| {
@@ -293,8 +295,12 @@ impl<'a> RowGroupBase<'a> {
chunks.push(chunk_data.next().unwrap());
}
let column = self
.parquet_metadata
.row_group(self.row_group_idx)
.column(idx);
*chunk = Some(Arc::new(ColumnChunkData::Sparse {
length: self.metadata.column(idx).byte_range().1 as usize,
length: column.byte_range().1 as usize,
data: offsets.into_iter().zip(chunks).collect(),
}))
}
@@ -307,7 +313,7 @@ impl<'a> RowGroupBase<'a> {
.enumerate()
.filter(|&(idx, chunk)| chunk.is_none() && projection.leaf_included(idx))
.map(|(idx, _chunk)| {
let column = self.metadata.column(idx);
let column = self.row_group_metadata().column(idx);
let (start, length) = column.byte_range();
start..(start + length)
})
@@ -333,7 +339,10 @@ impl<'a> RowGroupBase<'a> {
continue;
};
let column = self.metadata.column(idx);
let column = self
.parquet_metadata
.row_group(self.row_group_idx)
.column(idx);
*chunk = Some(Arc::new(ColumnChunkData::Dense {
offset: column.byte_range().0 as usize,
data,
@@ -360,7 +369,7 @@ impl<'a> RowGroupBase<'a> {
.map(|index| index[col_idx].page_locations.clone());
SerializedPageReader::new(
data.clone(),
self.metadata.column(col_idx),
self.row_group_metadata().column(col_idx),
self.row_count,
page_locations,
)?
@@ -369,6 +378,14 @@ impl<'a> RowGroupBase<'a> {
Ok(page_reader)
}
pub(crate) fn parquet_metadata(&self) -> &ParquetMetaData {
self.parquet_metadata
}
pub(crate) fn row_group_metadata(&self) -> &RowGroupMetaData {
self.parquet_metadata().row_group(self.row_group_idx)
}
}
/// An in-memory collection of column chunks
@@ -599,6 +616,14 @@ impl RowGroups for InMemoryRowGroup<'_> {
reader: Some(Ok(Box::new(page_reader))),
}))
}
fn row_groups(&self) -> Box<dyn Iterator<Item = &RowGroupMetaData> + '_> {
Box::new(std::iter::once(self.base.row_group_metadata()))
}
fn metadata(&self) -> &ParquetMetaData {
self.base.parquet_metadata()
}
}
/// An in-memory column chunk

13
src/operator/src/expr_helper.rs
View File

@@ -550,15 +550,10 @@ fn find_primary_keys(
let columns_pk = columns
.iter()
.filter_map(|x| {
if x.options().iter().any(|o| {
matches!(
o.option,
ColumnOption::Unique {
is_primary: true,
..
}
)
}) {
if x.options()
.iter()
.any(|o| matches!(o.option, ColumnOption::PrimaryKey(_)))
{
Some(x.name().value.clone())
} else {
None

16
src/promql/src/extension_plan/absent.rs
View File

@@ -238,12 +238,12 @@ impl Absent {
pub fn to_execution_plan(&self, exec_input: Arc<dyn ExecutionPlan>) -> Arc<dyn ExecutionPlan> {
let output_schema = Arc::new(self.output_schema.as_arrow().clone());
let properties = PlanProperties::new(
let properties = Arc::new(PlanProperties::new(
EquivalenceProperties::new(output_schema.clone()),
Partitioning::UnknownPartitioning(1),
EmissionType::Incremental,
Boundedness::Bounded,
);
));
Arc::new(AbsentExec {
start: self.start,
end: self.end,
@@ -323,7 +323,7 @@ pub struct AbsentExec {
fake_labels: Vec<(String, String)>,
output_schema: SchemaRef,
input: Arc<dyn ExecutionPlan>,
properties: PlanProperties,
properties: Arc<PlanProperties>,
metric: ExecutionPlanMetricsSet,
}
@@ -336,7 +336,7 @@ impl ExecutionPlan for AbsentExec {
self.output_schema.clone()
}
fn properties(&self) -> &PlanProperties {
fn properties(&self) -> &Arc<PlanProperties> {
&self.properties
}
@@ -624,12 +624,12 @@ mod tests {
fake_labels: vec![],
output_schema: output_schema.clone(),
input: Arc::new(memory_exec),
properties: PlanProperties::new(
properties: Arc::new(PlanProperties::new(
EquivalenceProperties::new(output_schema.clone()),
Partitioning::UnknownPartitioning(1),
EmissionType::Incremental,
Boundedness::Bounded,
),
)),
metric: ExecutionPlanMetricsSet::new(),
};
@@ -692,12 +692,12 @@ mod tests {
fake_labels: vec![],
output_schema: output_schema.clone(),
input: Arc::new(memory_exec),
properties: PlanProperties::new(
properties: Arc::new(PlanProperties::new(
EquivalenceProperties::new(output_schema.clone()),
Partitioning::UnknownPartitioning(1),
EmissionType::Incremental,
Boundedness::Bounded,
),
)),
metric: ExecutionPlanMetricsSet::new(),
};

6
src/promql/src/extension_plan/empty_metric.rs
View File

@@ -81,7 +81,7 @@ impl EmptyMetric {
) -> DataFusionResult<Self> {
let qualifier = Some(TableReference::bare(""));
let ts_only_schema = build_ts_only_schema(&time_index_column_name);
let mut fields = vec![(qualifier.clone(), Arc::new(ts_only_schema.field(0).clone()))];
let mut fields = vec![(qualifier.clone(), ts_only_schema.field(0).clone())];
if let Some(field_expr) = &field_expr {
let field_data_type = field_expr.get_type(&ts_only_schema)?;
fields.push((
@@ -232,8 +232,8 @@ impl ExecutionPlan for EmptyMetricExec {
self.result_schema.clone()
}
fn properties(&self) -> &PlanProperties {
self.properties.as_ref()
fn properties(&self) -> &Arc<PlanProperties> {
&self.properties
}
fn maintains_input_order(&self) -> Vec<bool> {

16
src/promql/src/extension_plan/histogram_fold.rs
View File

@@ -296,7 +296,7 @@ impl HistogramFold {
)) as _);
let output_schema: SchemaRef = self.output_schema.inner().clone();
let properties = PlanProperties::new(
let properties = Arc::new(PlanProperties::new(
EquivalenceProperties::new(output_schema.clone()),
Partitioning::Hash(
partition_exprs.clone(),
@@ -304,7 +304,7 @@ impl HistogramFold {
),
EmissionType::Incremental,
Boundedness::Bounded,
);
));
Arc::new(HistogramFoldExec {
le_column_index,
field_column_index,
@@ -416,7 +416,7 @@ pub struct HistogramFoldExec {
partition_exprs: Vec<Arc<dyn PhysicalExpr>>,
quantile: f64,
metric: ExecutionPlanMetricsSet,
properties: PlanProperties,
properties: Arc<PlanProperties>,
}
impl ExecutionPlan for HistogramFoldExec {
@@ -424,7 +424,7 @@ impl ExecutionPlan for HistogramFoldExec {
self
}
fn properties(&self) -> &PlanProperties {
fn properties(&self) -> &Arc<PlanProperties> {
&self.properties
}
@@ -486,7 +486,7 @@ impl ExecutionPlan for HistogramFoldExec {
) -> DataFusionResult<Arc<dyn ExecutionPlan>> {
assert!(!children.is_empty());
let new_input = children[0].clone();
let properties = PlanProperties::new(
let properties = Arc::new(PlanProperties::new(
EquivalenceProperties::new(self.output_schema.clone()),
Partitioning::Hash(
self.partition_exprs.clone(),
@@ -494,7 +494,7 @@ impl ExecutionPlan for HistogramFoldExec {
),
EmissionType::Incremental,
Boundedness::Bounded,
);
));
Ok(Arc::new(Self {
input: new_input,
metric: self.metric.clone(),
@@ -1241,7 +1241,7 @@ mod test {
type PlanPropsResult = (
Vec<Arc<dyn PhysicalExpr>>,
Vec<Arc<dyn PhysicalExpr>>,
PlanProperties,
Arc<PlanProperties>,
);
fn build_test_plan_properties(
@@ -1282,7 +1282,7 @@ mod test {
Boundedness::Bounded,
);
(tag_columns, partition_exprs, properties)
(tag_columns, partition_exprs, Arc::new(properties))
}
#[tokio::test]

2
src/promql/src/extension_plan/instant_manipulate.rs
View File

@@ -293,7 +293,7 @@ impl ExecutionPlan for InstantManipulateExec {
self.input.schema()
}
fn properties(&self) -> &PlanProperties {
fn properties(&self) -> &Arc<PlanProperties> {
self.input.properties()
}

6
src/promql/src/extension_plan/normalize.rs
View File

@@ -273,6 +273,10 @@ impl ExecutionPlan for SeriesNormalizeExec {
}
fn required_input_distribution(&self) -> Vec<Distribution> {
if self.tag_columns.is_empty() {
return vec![Distribution::SinglePartition];
}
let schema = self.input.schema();
vec![Distribution::HashPartitioned(
self.tag_columns
@@ -283,7 +287,7 @@ impl ExecutionPlan for SeriesNormalizeExec {
)]
}
fn properties(&self) -> &PlanProperties {
fn properties(&self) -> &Arc<PlanProperties> {
self.input.properties()
}

18
src/promql/src/extension_plan/range_manipulate.rs
View File

@@ -129,7 +129,7 @@ impl RangeManipulate {
let mut new_columns = Vec::with_capacity(columns.len() + 1);
for i in 0..columns.len() {
let x = input_schema.qualified_field(i);
new_columns.push((x.0.cloned(), Arc::new(x.1.clone())));
new_columns.push((x.0.cloned(), x.1.clone()));
}
// process time index column
@@ -170,12 +170,12 @@ impl RangeManipulate {
pub fn to_execution_plan(&self, exec_input: Arc<dyn ExecutionPlan>) -> Arc<dyn ExecutionPlan> {
let output_schema: SchemaRef = self.output_schema.inner().clone();
let properties = exec_input.properties();
let properties = PlanProperties::new(
let properties = Arc::new(PlanProperties::new(
EquivalenceProperties::new(output_schema.clone()),
properties.partitioning.clone(),
properties.emission_type,
properties.boundedness,
);
));
Arc::new(RangeManipulateExec {
start: self.start,
end: self.end,
@@ -421,7 +421,7 @@ pub struct RangeManipulateExec {
input: Arc<dyn ExecutionPlan>,
output_schema: SchemaRef,
metric: ExecutionPlanMetricsSet,
properties: PlanProperties,
properties: Arc<PlanProperties>,
}
impl ExecutionPlan for RangeManipulateExec {
@@ -433,7 +433,7 @@ impl ExecutionPlan for RangeManipulateExec {
self.output_schema.clone()
}
fn properties(&self) -> &PlanProperties {
fn properties(&self) -> &Arc<PlanProperties> {
&self.properties
}
@@ -463,12 +463,12 @@ impl ExecutionPlan for RangeManipulateExec {
assert!(!children.is_empty());
let exec_input = children[0].clone();
let properties = exec_input.properties();
let properties = PlanProperties::new(
let properties = Arc::new(PlanProperties::new(
EquivalenceProperties::new(self.output_schema.clone()),
properties.partitioning.clone(),
properties.emission_type,
properties.boundedness,
);
));
Ok(Arc::new(Self {
start: self.start,
end: self.end,
@@ -856,12 +856,12 @@ mod test {
.as_arrow()
.clone(),
);
let properties = PlanProperties::new(
let properties = Arc::new(PlanProperties::new(
EquivalenceProperties::new(manipulate_output_schema.clone()),
Partitioning::UnknownPartitioning(1),
EmissionType::Incremental,
Boundedness::Bounded,
);
));
let normalize_exec = Arc::new(RangeManipulateExec {
start,
end,

14
src/promql/src/extension_plan/scalar_calculate.rs
View File

@@ -94,7 +94,7 @@ impl ScalarCalculate {
let qualifier = table_name.map(TableReference::bare);
let schema = DFSchema::new_with_metadata(
vec![
(qualifier.clone(), Arc::new(ts_field)),
(qualifier.clone(), ts_field),
(qualifier, Arc::new(val_field)),
],
input_schema.metadata().clone(),
@@ -139,12 +139,12 @@ impl ScalarCalculate {
.map_err(|e| DataFusionError::ArrowError(Box::new(e), None))?;
let schema = Arc::new(Schema::new(fields));
let properties = exec_input.properties();
let properties = PlanProperties::new(
let properties = Arc::new(PlanProperties::new(
EquivalenceProperties::new(schema.clone()),
Partitioning::UnknownPartitioning(1),
properties.emission_type,
properties.boundedness,
);
));
Ok(Arc::new(ScalarCalculateExec {
start: self.start,
end: self.end,
@@ -384,7 +384,7 @@ struct ScalarCalculateExec {
input: Arc<dyn ExecutionPlan>,
tag_columns: Vec<String>,
metric: ExecutionPlanMetricsSet,
properties: PlanProperties,
properties: Arc<PlanProperties>,
}
impl ExecutionPlan for ScalarCalculateExec {
@@ -396,7 +396,7 @@ impl ExecutionPlan for ScalarCalculateExec {
self.schema.clone()
}
fn properties(&self) -> &PlanProperties {
fn properties(&self) -> &Arc<PlanProperties> {
&self.properties
}
@@ -769,12 +769,12 @@ mod test {
Field::new("ts", DataType::Timestamp(TimeUnit::Millisecond, None), true),
Field::new("val", DataType::Float64, true),
]));
let properties = PlanProperties::new(
let properties = Arc::new(PlanProperties::new(
EquivalenceProperties::new(schema.clone()),
Partitioning::UnknownPartitioning(1),
EmissionType::Incremental,
Boundedness::Bounded,
);
));
let scalar_exec = Arc::new(ScalarCalculateExec {
start: 0,
end: 15_000,

5
src/promql/src/extension_plan/series_divide.rs
View File

@@ -389,11 +389,14 @@ impl ExecutionPlan for SeriesDivideExec {
self.input.schema()
}
fn properties(&self) -> &PlanProperties {
fn properties(&self) -> &Arc<PlanProperties> {
self.input.properties()
}
fn required_input_distribution(&self) -> Vec<Distribution> {
if self.tag_columns.is_empty() {
return vec![Distribution::SinglePartition];
}
let schema = self.input.schema();
vec![Distribution::HashPartitioned(
self.tag_columns

4
src/promql/src/extension_plan/union_distinct_on.rs
View File

@@ -307,8 +307,8 @@ impl ExecutionPlan for UnionDistinctOnExec {
vec![Distribution::SinglePartition, Distribution::SinglePartition]
}
fn properties(&self) -> &PlanProperties {
self.properties.as_ref()
fn properties(&self) -> &Arc<PlanProperties> {
&self.properties
}
fn children(&self) -> Vec<&Arc<dyn ExecutionPlan>> {

49
src/promql/src/range_array.rs
View File

@@ -14,9 +14,6 @@
//！An extended "array" based on [DictionaryArray].
use std::sync::Arc;
use datafusion::arrow::buffer::NullBuffer;
use datafusion::arrow::datatypes::Field;
use datatypes::arrow::array::{Array, ArrayData, ArrayRef, DictionaryArray, Int64Array};
use datatypes::arrow::datatypes::{DataType, Int64Type};
@@ -225,52 +222,6 @@ impl RangeArray {
}
}
impl Array for RangeArray {
fn as_any(&self) -> &dyn std::any::Any {
self
}
fn into_data(self) -> ArrayData {
self.array.into_data()
}
fn to_data(&self) -> ArrayData {
self.array.to_data()
}
fn slice(&self, offset: usize, length: usize) -> ArrayRef {
Arc::new(self.array.slice(offset, length))
}
fn nulls(&self) -> Option<&NullBuffer> {
self.array.nulls()
}
fn data_type(&self) -> &DataType {
self.array.data_type()
}
fn len(&self) -> usize {
self.len()
}
fn is_empty(&self) -> bool {
self.is_empty()
}
fn offset(&self) -> usize {
self.array.offset()
}
fn get_buffer_memory_size(&self) -> usize {
self.array.get_buffer_memory_size()
}
fn get_array_memory_size(&self) -> usize {
self.array.get_array_memory_size()
}
}
impl std::fmt::Debug for RangeArray {
fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
let ranges = self

6
src/query/src/analyze.rs
View File

@@ -49,7 +49,7 @@ const PLAN: &str = "plan";
pub struct DistAnalyzeExec {
input: Arc<dyn ExecutionPlan>,
schema: SchemaRef,
properties: PlanProperties,
properties: Arc<PlanProperties>,
verbose: bool,
format: AnalyzeFormat,
}
@@ -62,7 +62,7 @@ impl DistAnalyzeExec {
Field::new(NODE, DataType::UInt32, true),
Field::new(PLAN, DataType::Utf8, true),
]));
let properties = Self::compute_properties(&input, schema.clone());
let properties = Arc::new(Self::compute_properties(&input, schema.clone()));
Self {
input,
schema,
@@ -108,7 +108,7 @@ impl ExecutionPlan for DistAnalyzeExec {
self
}
fn properties(&self) -> &PlanProperties {
fn properties(&self) -> &Arc<PlanProperties> {
&self.properties
}

2
src/query/src/dist_plan/analyzer/utils.rs
View File

@@ -46,7 +46,7 @@ pub(crate) struct PatchOptimizerContext {
}
impl OptimizerConfig for PatchOptimizerContext {
fn query_execution_start_time(&self) -> DateTime<Utc> {
fn query_execution_start_time(&self) -> Option<DateTime<Utc>> {
self.inner.query_execution_start_time()
}

3
src/query/src/dist_plan/commutativity.rs
View File

@@ -334,7 +334,8 @@ impl Categorizer {
Expr::Unnest(_)
| Expr::GroupingSet(_)
| Expr::Placeholder(_)
| Expr::OuterReferenceColumn(_, _) => Commutativity::Unimplemented,
| Expr::OuterReferenceColumn(_, _)
| Expr::SetComparison(_) => Commutativity::Unimplemented,
}
}

12
src/query/src/dist_plan/merge_scan.rs
View File

@@ -139,7 +139,7 @@ pub struct MergeScanExec {
arrow_schema: ArrowSchemaRef,
region_query_handler: RegionQueryHandlerRef,
metric: ExecutionPlanMetricsSet,
properties: PlanProperties,
properties: Arc<PlanProperties>,
/// Metrics from sub stages
sub_stage_metrics: Arc<Mutex<HashMap<RegionId, RecordBatchMetrics>>>,
/// Metrics for each partition
@@ -226,12 +226,12 @@ impl MergeScanExec {
.collect();
let partitioning = Partitioning::Hash(partition_exprs, target_partition);
let properties = PlanProperties::new(
let properties = Arc::new(PlanProperties::new(
eq_properties,
partitioning,
EmissionType::Incremental,
Boundedness::Bounded,
);
));
Ok(Self {
table,
regions,
@@ -453,12 +453,12 @@ impl MergeScanExec {
arrow_schema: self.arrow_schema.clone(),
region_query_handler: self.region_query_handler.clone(),
metric: self.metric.clone(),
properties: PlanProperties::new(
properties: Arc::new(PlanProperties::new(
self.properties.eq_properties.clone(),
Partitioning::Hash(overlaps, self.target_partition),
self.properties.emission_type,
self.properties.boundedness,
),
)),
sub_stage_metrics: self.sub_stage_metrics.clone(),
partition_metrics: self.partition_metrics.clone(),
query_ctx: self.query_ctx.clone(),
@@ -584,7 +584,7 @@ impl ExecutionPlan for MergeScanExec {
self.arrow_schema.clone()
}
fn properties(&self) -> &PlanProperties {
fn properties(&self) -> &Arc<PlanProperties> {
&self.properties
}

44
src/query/src/log_query/planner.rs
View File

@@ -729,9 +729,9 @@ mod tests {
};
let plan = planner.query_to_plan(log_query).await.unwrap();
let expected = "Limit: skip=0, fetch=100 [message:Utf8, timestamp:Timestamp(Millisecond, None), host:Utf8;N, is_active:Boolean;N]\
\n Filter: greptime.public.test_table.timestamp >= Utf8(\"2021-01-01T00:00:00Z\") AND greptime.public.test_table.timestamp <= Utf8(\"2021-01-02T00:00:00Z\") AND greptime.public.test_table.message LIKE Utf8(\"%error%\") [message:Utf8, timestamp:Timestamp(Millisecond, None), host:Utf8;N, is_active:Boolean;N]\
\n TableScan: greptime.public.test_table [message:Utf8, timestamp:Timestamp(Millisecond, None), host:Utf8;N, is_active:Boolean;N]";
let expected = "Limit: skip=0, fetch=100 [message:Utf8, timestamp:Timestamp(ms), host:Utf8;N, is_active:Boolean;N]\
\n Filter: greptime.public.test_table.timestamp >= Utf8(\"2021-01-01T00:00:00Z\") AND greptime.public.test_table.timestamp <= Utf8(\"2021-01-02T00:00:00Z\") AND greptime.public.test_table.message LIKE Utf8(\"%error%\") [message:Utf8, timestamp:Timestamp(ms), host:Utf8;N, is_active:Boolean;N]\
\n TableScan: greptime.public.test_table [message:Utf8, timestamp:Timestamp(ms), host:Utf8;N, is_active:Boolean;N]";
assert_eq!(plan.display_indent_schema().to_string(), expected);
}
@@ -850,9 +850,9 @@ mod tests {
};
let plan = planner.query_to_plan(log_query).await.unwrap();
let expected = "Limit: skip=10, fetch=1000 [message:Utf8, timestamp:Timestamp(Millisecond, None), host:Utf8;N, is_active:Boolean;N]\
\n Filter: greptime.public.test_table.timestamp >= Utf8(\"2021-01-01T00:00:00Z\") AND greptime.public.test_table.timestamp <= Utf8(\"2021-01-02T00:00:00Z\") AND greptime.public.test_table.message LIKE Utf8(\"%error%\") [message:Utf8, timestamp:Timestamp(Millisecond, None), host:Utf8;N, is_active:Boolean;N]\
\n TableScan: greptime.public.test_table [message:Utf8, timestamp:Timestamp(Millisecond, None), host:Utf8;N, is_active:Boolean;N]";
let expected = "Limit: skip=10, fetch=1000 [message:Utf8, timestamp:Timestamp(ms), host:Utf8;N, is_active:Boolean;N]\
\n Filter: greptime.public.test_table.timestamp >= Utf8(\"2021-01-01T00:00:00Z\") AND greptime.public.test_table.timestamp <= Utf8(\"2021-01-02T00:00:00Z\") AND greptime.public.test_table.message LIKE Utf8(\"%error%\") [message:Utf8, timestamp:Timestamp(ms), host:Utf8;N, is_active:Boolean;N]\
\n TableScan: greptime.public.test_table [message:Utf8, timestamp:Timestamp(ms), host:Utf8;N, is_active:Boolean;N]";
assert_eq!(plan.display_indent_schema().to_string(), expected);
}
@@ -885,9 +885,9 @@ mod tests {
};
let plan = planner.query_to_plan(log_query).await.unwrap();
let expected = "Limit: skip=0, fetch=1000 [message:Utf8, timestamp:Timestamp(Millisecond, None), host:Utf8;N, is_active:Boolean;N]\
\n Filter: greptime.public.test_table.timestamp >= Utf8(\"2021-01-01T00:00:00Z\") AND greptime.public.test_table.timestamp <= Utf8(\"2021-01-02T00:00:00Z\") AND greptime.public.test_table.message LIKE Utf8(\"%error%\") [message:Utf8, timestamp:Timestamp(Millisecond, None), host:Utf8;N, is_active:Boolean;N]\
\n TableScan: greptime.public.test_table [message:Utf8, timestamp:Timestamp(Millisecond, None), host:Utf8;N, is_active:Boolean;N]";
let expected = "Limit: skip=0, fetch=1000 [message:Utf8, timestamp:Timestamp(ms), host:Utf8;N, is_active:Boolean;N]\
\n Filter: greptime.public.test_table.timestamp >= Utf8(\"2021-01-01T00:00:00Z\") AND greptime.public.test_table.timestamp <= Utf8(\"2021-01-02T00:00:00Z\") AND greptime.public.test_table.message LIKE Utf8(\"%error%\") [message:Utf8, timestamp:Timestamp(ms), host:Utf8;N, is_active:Boolean;N]\
\n TableScan: greptime.public.test_table [message:Utf8, timestamp:Timestamp(ms), host:Utf8;N, is_active:Boolean;N]";
assert_eq!(plan.display_indent_schema().to_string(), expected);
}
@@ -933,9 +933,9 @@ mod tests {
let plan = planner.query_to_plan(log_query).await.unwrap();
let expected = "Aggregate: groupBy=[[greptime.public.test_table.host]], aggr=[[count(greptime.public.test_table.message) AS count_result]] [host:Utf8;N, count_result:Int64]\
\n Limit: skip=0, fetch=100 [message:Utf8, timestamp:Timestamp(Millisecond, None), host:Utf8;N, is_active:Boolean;N]\
\n Filter: greptime.public.test_table.timestamp >= Utf8(\"2021-01-01T00:00:00Z\") AND greptime.public.test_table.timestamp <= Utf8(\"2021-01-02T00:00:00Z\") [message:Utf8, timestamp:Timestamp(Millisecond, None), host:Utf8;N, is_active:Boolean;N]\
\n TableScan: greptime.public.test_table [message:Utf8, timestamp:Timestamp(Millisecond, None), host:Utf8;N, is_active:Boolean;N]";
\n Limit: skip=0, fetch=100 [message:Utf8, timestamp:Timestamp(ms), host:Utf8;N, is_active:Boolean;N]\
\n Filter: greptime.public.test_table.timestamp >= Utf8(\"2021-01-01T00:00:00Z\") AND greptime.public.test_table.timestamp <= Utf8(\"2021-01-02T00:00:00Z\") [message:Utf8, timestamp:Timestamp(ms), host:Utf8;N, is_active:Boolean;N]\
\n TableScan: greptime.public.test_table [message:Utf8, timestamp:Timestamp(ms), host:Utf8;N, is_active:Boolean;N]";
assert_eq!(plan.display_indent_schema().to_string(), expected);
}
@@ -964,18 +964,18 @@ mod tests {
exprs: vec![LogExpr::ScalarFunc {
name: "date_trunc".to_string(),
args: vec![
LogExpr::NamedIdent("timestamp".to_string()),
LogExpr::Literal("day".to_string()),
LogExpr::NamedIdent("timestamp".to_string()),
],
alias: Some("time_bucket".to_string()),
}],
};
let plan = planner.query_to_plan(log_query).await.unwrap();
let expected = "Projection: date_trunc(greptime.public.test_table.timestamp, Utf8(\"day\")) AS time_bucket [time_bucket:Timestamp(Nanosecond, None);N]\
\n Limit: skip=0, fetch=100 [message:Utf8, timestamp:Timestamp(Millisecond, None), host:Utf8;N, is_active:Boolean;N]\
\n Filter: greptime.public.test_table.timestamp >= Utf8(\"2021-01-01T00:00:00Z\") AND greptime.public.test_table.timestamp <= Utf8(\"2021-01-02T00:00:00Z\") [message:Utf8, timestamp:Timestamp(Millisecond, None), host:Utf8;N, is_active:Boolean;N]\
\n TableScan: greptime.public.test_table [message:Utf8, timestamp:Timestamp(Millisecond, None), host:Utf8;N, is_active:Boolean;N]";
let expected = "Projection: date_trunc(Utf8(\"day\"), greptime.public.test_table.timestamp) AS time_bucket [time_bucket:Timestamp(ms)]\
\n Limit: skip=0, fetch=100 [message:Utf8, timestamp:Timestamp(ms), host:Utf8;N, is_active:Boolean;N]\
\n Filter: greptime.public.test_table.timestamp >= Utf8(\"2021-01-01T00:00:00Z\") AND greptime.public.test_table.timestamp <= Utf8(\"2021-01-02T00:00:00Z\") [message:Utf8, timestamp:Timestamp(ms), host:Utf8;N, is_active:Boolean;N]\
\n TableScan: greptime.public.test_table [message:Utf8, timestamp:Timestamp(ms), host:Utf8;N, is_active:Boolean;N]";
assert_eq!(plan.display_indent_schema().to_string(), expected);
}
@@ -1055,11 +1055,11 @@ mod tests {
};
let plan = planner.query_to_plan(log_query).await.unwrap();
let expected = "Aggregate: groupBy=[[2__date_histogram__time_bucket]], aggr=[[count(2__date_histogram__time_bucket) AS count_result]] [2__date_histogram__time_bucket:Timestamp(Nanosecond, None);N, count_result:Int64]\
\n Projection: date_bin(Utf8(\"30 seconds\"), greptime.public.test_table.timestamp) AS 2__date_histogram__time_bucket [2__date_histogram__time_bucket:Timestamp(Nanosecond, None);N]\
\n Limit: skip=0, fetch=1000 [message:Utf8, timestamp:Timestamp(Millisecond, None), host:Utf8;N, is_active:Boolean;N]\
\n Filter: greptime.public.test_table.timestamp >= Utf8(\"2021-01-01T00:00:00Z\") AND greptime.public.test_table.timestamp <= Utf8(\"2021-01-02T00:00:00Z\") [message:Utf8, timestamp:Timestamp(Millisecond, None), host:Utf8;N, is_active:Boolean;N]\
\n TableScan: greptime.public.test_table [message:Utf8, timestamp:Timestamp(Millisecond, None), host:Utf8;N, is_active:Boolean;N]";
let expected = "Aggregate: groupBy=[[2__date_histogram__time_bucket]], aggr=[[count(2__date_histogram__time_bucket) AS count_result]] [2__date_histogram__time_bucket:Timestamp(ns);N, count_result:Int64]\
\n Projection: date_bin(Utf8(\"30 seconds\"), greptime.public.test_table.timestamp) AS 2__date_histogram__time_bucket [2__date_histogram__time_bucket:Timestamp(ns);N]\
\n Limit: skip=0, fetch=1000 [message:Utf8, timestamp:Timestamp(ms), host:Utf8;N, is_active:Boolean;N]\
\n Filter: greptime.public.test_table.timestamp >= Utf8(\"2021-01-01T00:00:00Z\") AND greptime.public.test_table.timestamp <= Utf8(\"2021-01-02T00:00:00Z\") [message:Utf8, timestamp:Timestamp(ms), host:Utf8;N, is_active:Boolean;N]\
\n TableScan: greptime.public.test_table [message:Utf8, timestamp:Timestamp(ms), host:Utf8;N, is_active:Boolean;N]";
assert_eq!(plan.display_indent_schema().to_string(), expected);
}

9
src/query/src/optimizer/constant_term.rs
View File

@@ -23,7 +23,7 @@ use datafusion::config::ConfigOptions;
use datafusion::error::Result as DfResult;
use datafusion::physical_optimizer::PhysicalOptimizerRule;
use datafusion::physical_plan::ExecutionPlan;
use datafusion::physical_plan::filter::FilterExec;
use datafusion::physical_plan::filter::{FilterExec, FilterExecBuilder};
use datafusion_common::ScalarValue;
use datafusion_common::tree_node::{Transformed, TreeNode};
use datafusion_expr::ColumnarValue;
@@ -205,9 +205,10 @@ impl PhysicalOptimizerRule for MatchesConstantTermOptimizer {
})?;
if new_pred.transformed {
let exec = FilterExec::try_new(new_pred.data, filter.input().clone())?
.with_default_selectivity(filter.default_selectivity())?
.with_projection(filter.projection().cloned())?;
let exec = FilterExecBuilder::new(new_pred.data, filter.input().clone())
.with_default_selectivity(filter.default_selectivity())
.apply_projection_by_ref(filter.projection().as_ref())
.and_then(|x| x.build())?;
return Ok(Transformed::yes(Arc::new(exec) as _));
}
}

53
src/query/src/optimizer/remove_duplicate.rs
View File

@@ -17,13 +17,12 @@ use std::sync::Arc;
use datafusion::config::ConfigOptions;
use datafusion::physical_optimizer::PhysicalOptimizerRule;
use datafusion::physical_plan::ExecutionPlan;
use datafusion::physical_plan::coalesce_batches::CoalesceBatchesExec;
use datafusion::physical_plan::repartition::RepartitionExec;
use datafusion_common::Result as DfResult;
use datafusion_common::tree_node::{Transformed, TreeNode};
/// This is [PhysicalOptimizerRule] to remove duplicate physical plans such as two
/// adjoining [CoalesceBatchesExec] or [RepartitionExec]. They won't have any effect
/// adjoining [RepartitionExec]. They won't have any effect
/// if one runs right after another.
///
/// This rule is expected to be run in the final stage of the optimization process.
@@ -52,9 +51,7 @@ impl RemoveDuplicate {
fn do_optimize(plan: Arc<dyn ExecutionPlan>) -> DfResult<Arc<dyn ExecutionPlan>> {
let result = plan
.transform_down(|plan| {
if plan.as_any().is::<CoalesceBatchesExec>()
|| plan.as_any().is::<RepartitionExec>()
{
if plan.as_any().is::<RepartitionExec>() {
// check child
let child = plan.children()[0].clone();
if child.as_any().type_id() == plan.as_any().type_id() {
@@ -72,49 +69,3 @@ impl RemoveDuplicate {
Ok(result)
}
}
#[cfg(test)]
mod test {
use std::sync::Arc;
use arrow_schema::Schema;
use datafusion::physical_plan::displayable;
use datafusion::physical_plan::empty::EmptyExec;
use datafusion_physical_expr::Partitioning;
use super::*;
#[test]
fn remove_coalesce_batches() {
let empty = Arc::new(EmptyExec::new(Arc::new(Schema::empty())));
let coalesce_batches = Arc::new(CoalesceBatchesExec::new(empty, 1024));
let another_coalesce_batches = Arc::new(CoalesceBatchesExec::new(coalesce_batches, 8192));
let optimized = RemoveDuplicate::do_optimize(another_coalesce_batches).unwrap();
let formatted = displayable(optimized.as_ref()).indent(true).to_string();
let expected = "CoalesceBatchesExec: target_batch_size=8192\
\n EmptyExec\n";
assert_eq!(expected, formatted);
}
#[test]
fn non_continuous_coalesce_batches() {
let empty = Arc::new(EmptyExec::new(Arc::new(Schema::empty())));
let coalesce_batches = Arc::new(CoalesceBatchesExec::new(empty, 1024));
let repartition = Arc::new(
RepartitionExec::try_new(coalesce_batches, Partitioning::UnknownPartitioning(1))
.unwrap(),
);
let another_coalesce_batches = Arc::new(CoalesceBatchesExec::new(repartition, 8192));
let optimized = RemoveDuplicate::do_optimize(another_coalesce_batches).unwrap();
let formatted = displayable(optimized.as_ref()).indent(true).to_string();
let expected = "CoalesceBatchesExec: target_batch_size=8192\
\n RepartitionExec: partitioning=UnknownPartitioning(1), input_partitions=1\
\n CoalesceBatchesExec: target_batch_size=1024\
\n EmptyExec\n";
assert_eq!(expected, formatted);
}
}

45
src/query/src/optimizer/windowed_sort.rs
View File

@@ -17,7 +17,6 @@ use std::sync::Arc;
use datafusion::physical_optimizer::PhysicalOptimizerRule;
use datafusion::physical_plan::ExecutionPlan;
use datafusion::physical_plan::coalesce_batches::CoalesceBatchesExec;
use datafusion::physical_plan::coalesce_partitions::CoalescePartitionsExec;
use datafusion::physical_plan::coop::CooperativeExec;
use datafusion::physical_plan::filter::FilterExec;
@@ -80,8 +79,6 @@ impl WindowedSortPhysicalRule {
let preserve_partitioning = sort_exec.preserve_partitioning();
let sort_input = remove_repartition(sort_exec.input().clone())?.data;
let sort_input =
remove_coalesce_batches_exec(sort_input, sort_exec.fetch())?.data;
// Gets scanner info from the input without repartition before filter.
let Some(scanner_info) = fetch_partition_range(sort_input.clone())? else {
@@ -164,7 +161,6 @@ fn fetch_partition_range(input: Arc<dyn ExecutionPlan>) -> DataFusionResult<Opti
let mut time_index = HashSet::new();
let mut alias_map = Vec::new();
let mut tag_columns = None;
let mut is_batch_coalesced = false;
input.transform_up(|plan| {
if plan.as_any().is::<CooperativeExec>() {
@@ -180,16 +176,9 @@ fn fetch_partition_range(input: Arc<dyn ExecutionPlan>) -> DataFusionResult<Opti
partition_ranges = None;
}
if plan.as_any().is::<CoalesceBatchesExec>() {
is_batch_coalesced = true;
}
// only a very limited set of plans can exist between region scan and sort exec
// other plans might make this optimize wrong, so be safe here by limiting it
if !(plan.as_any().is::<ProjectionExec>()
|| plan.as_any().is::<FilterExec>()
|| plan.as_any().is::<CoalesceBatchesExec>())
{
if !(plan.as_any().is::<ProjectionExec>() || plan.as_any().is::<FilterExec>()) {
partition_ranges = None;
}
@@ -219,10 +208,7 @@ fn fetch_partition_range(input: Arc<dyn ExecutionPlan>) -> DataFusionResult<Opti
time_index = HashSet::from([region_scan_exec.time_index()]);
tag_columns = Some(region_scan_exec.tag_columns());
// set distinguish_partition_ranges to true, this is an incorrect workaround
if !is_batch_coalesced {
region_scan_exec.with_distinguish_partition_range(true);
}
region_scan_exec.with_distinguish_partition_range(true);
}
Ok(Transformed::no(plan))
@@ -260,33 +246,6 @@ fn remove_repartition(
})
}
/// Remove `CoalesceBatchesExec` if the limit is less than the batch size.
///
/// so that if limit is too small we can avoid need to scan for more rows than necessary
fn remove_coalesce_batches_exec(
plan: Arc<dyn ExecutionPlan>,
fetch: Option<usize>,
) -> DataFusionResult<Transformed<Arc<dyn ExecutionPlan>>> {
let Some(fetch) = fetch else {
return Ok(Transformed::no(plan));
};
// Avoid removing multiple coalesce batches
let mut is_done = false;
plan.transform_down(|plan| {
if let Some(coalesce_batches_exec) = plan.as_any().downcast_ref::<CoalesceBatchesExec>() {
let target_batch_size = coalesce_batches_exec.target_batch_size();
if fetch < target_batch_size && !is_done {
is_done = true;
return Ok(Transformed::yes(coalesce_batches_exec.input().clone()));
}
}
Ok(Transformed::no(plan))
})
}
/// Resolves alias of the time index column.
///
/// i.e if a is time index, alias= {a:b, b:c}, then result should be {a, b}(not {a, c}) because projection is not transitive

8
src/query/src/part_sort.rs
View File

@@ -114,7 +114,7 @@ pub struct PartSortExec {
/// Execution metrics
metrics: ExecutionPlanMetricsSet,
partition_ranges: Vec<Vec<PartitionRange>>,
properties: PlanProperties,
properties: Arc<PlanProperties>,
/// Filter matching the state of the sort for dynamic filter pushdown.
/// If `limit` is `Some`, this will also be set and a TopK operator may be used.
/// If `limit` is `None`, this will be `None`.
@@ -132,12 +132,12 @@ impl PartSortExec {
let metrics = ExecutionPlanMetricsSet::new();
let properties = input.properties();
let properties = PlanProperties::new(
let properties = Arc::new(PlanProperties::new(
input.equivalence_properties().clone(),
input.output_partitioning().clone(),
properties.emission_type,
properties.boundedness,
);
));
let filter = limit
.is_some()
@@ -220,7 +220,7 @@ impl ExecutionPlan for PartSortExec {
self.input.schema()
}
fn properties(&self) -> &PlanProperties {
fn properties(&self) -> &Arc<PlanProperties> {
&self.properties
}

396
src/query/src/promql/planner.rs
View File

@@ -4365,13 +4365,13 @@ mod test {
.unwrap();
let expected = String::from(
"Filter: TEMPLATE(field_0) IS NOT NULL [timestamp:Timestamp(Millisecond, None), TEMPLATE(field_0):Float64;N, tag_0:Utf8]\
\n Projection: some_metric.timestamp, TEMPLATE(some_metric.field_0) AS TEMPLATE(field_0), some_metric.tag_0 [timestamp:Timestamp(Millisecond, None), TEMPLATE(field_0):Float64;N, tag_0:Utf8]\
\n PromInstantManipulate: range=[0..100000000], lookback=[1000], interval=[5000], time index=[timestamp] [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N]\
\n PromSeriesDivide: tags=[\"tag_0\"] [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N]\
\n Sort: some_metric.tag_0 ASC NULLS FIRST, some_metric.timestamp ASC NULLS FIRST [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N]\
\n Filter: some_metric.tag_0 != Utf8(\"bar\") AND some_metric.timestamp >= TimestampMillisecond(-999, None) AND some_metric.timestamp <= TimestampMillisecond(100000000, None) [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N]\
\n TableScan: some_metric [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N]"
"Filter: TEMPLATE(field_0) IS NOT NULL [timestamp:Timestamp(ms), TEMPLATE(field_0):Float64;N, tag_0:Utf8]\
\n Projection: some_metric.timestamp, TEMPLATE(some_metric.field_0) AS TEMPLATE(field_0), some_metric.tag_0 [timestamp:Timestamp(ms), TEMPLATE(field_0):Float64;N, tag_0:Utf8]\
\n PromInstantManipulate: range=[0..100000000], lookback=[1000], interval=[5000], time index=[timestamp] [tag_0:Utf8, timestamp:Timestamp(ms), field_0:Float64;N]\
\n PromSeriesDivide: tags=[\"tag_0\"] [tag_0:Utf8, timestamp:Timestamp(ms), field_0:Float64;N]\
\n Sort: some_metric.tag_0 ASC NULLS FIRST, some_metric.timestamp ASC NULLS FIRST [tag_0:Utf8, timestamp:Timestamp(ms), field_0:Float64;N]\
\n Filter: some_metric.tag_0 != Utf8(\"bar\") AND some_metric.timestamp >= TimestampMillisecond(-999, None) AND some_metric.timestamp <= TimestampMillisecond(100000000, None) [tag_0:Utf8, timestamp:Timestamp(ms), field_0:Float64;N]\
\n TableScan: some_metric [tag_0:Utf8, timestamp:Timestamp(ms), field_0:Float64;N]"
).replace("TEMPLATE", plan_name);
assert_eq!(plan.display_indent_schema().to_string(), expected);
@@ -4574,13 +4574,13 @@ mod test {
.await
.unwrap();
let expected_no_without = String::from(
"Sort: some_metric.tag_1 ASC NULLS LAST, some_metric.timestamp ASC NULLS LAST [tag_1:Utf8, timestamp:Timestamp(Millisecond, None), TEMPLATE(some_metric.field_0):Float64;N, TEMPLATE(some_metric.field_1):Float64;N]\
\n Aggregate: groupBy=[[some_metric.tag_1, some_metric.timestamp]], aggr=[[TEMPLATE(some_metric.field_0), TEMPLATE(some_metric.field_1)]] [tag_1:Utf8, timestamp:Timestamp(Millisecond, None), TEMPLATE(some_metric.field_0):Float64;N, TEMPLATE(some_metric.field_1):Float64;N]\
\n PromInstantManipulate: range=[0..100000000], lookback=[1000], interval=[5000], time index=[timestamp] [tag_0:Utf8, tag_1:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N, field_1:Float64;N]\
\n PromSeriesDivide: tags=[\"tag_0\", \"tag_1\"] [tag_0:Utf8, tag_1:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N, field_1:Float64;N]\
\n Sort: some_metric.tag_0 ASC NULLS FIRST, some_metric.tag_1 ASC NULLS FIRST, some_metric.timestamp ASC NULLS FIRST [tag_0:Utf8, tag_1:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N, field_1:Float64;N]\
\n Filter: some_metric.tag_0 != Utf8(\"bar\") AND some_metric.timestamp >= TimestampMillisecond(-999, None) AND some_metric.timestamp <= TimestampMillisecond(100000000, None) [tag_0:Utf8, tag_1:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N, field_1:Float64;N]\
\n TableScan: some_metric [tag_0:Utf8, tag_1:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N, field_1:Float64;N]"
"Sort: some_metric.tag_1 ASC NULLS LAST, some_metric.timestamp ASC NULLS LAST [tag_1:Utf8, timestamp:Timestamp(ms), TEMPLATE(some_metric.field_0):Float64;N, TEMPLATE(some_metric.field_1):Float64;N]\
\n Aggregate: groupBy=[[some_metric.tag_1, some_metric.timestamp]], aggr=[[TEMPLATE(some_metric.field_0), TEMPLATE(some_metric.field_1)]] [tag_1:Utf8, timestamp:Timestamp(ms), TEMPLATE(some_metric.field_0):Float64;N, TEMPLATE(some_metric.field_1):Float64;N]\
\n PromInstantManipulate: range=[0..100000000], lookback=[1000], interval=[5000], time index=[timestamp] [tag_0:Utf8, tag_1:Utf8, timestamp:Timestamp(ms), field_0:Float64;N, field_1:Float64;N]\
\n PromSeriesDivide: tags=[\"tag_0\", \"tag_1\"] [tag_0:Utf8, tag_1:Utf8, timestamp:Timestamp(ms), field_0:Float64;N, field_1:Float64;N]\
\n Sort: some_metric.tag_0 ASC NULLS FIRST, some_metric.tag_1 ASC NULLS FIRST, some_metric.timestamp ASC NULLS FIRST [tag_0:Utf8, tag_1:Utf8, timestamp:Timestamp(ms), field_0:Float64;N, field_1:Float64;N]\
\n Filter: some_metric.tag_0 != Utf8(\"bar\") AND some_metric.timestamp >= TimestampMillisecond(-999, None) AND some_metric.timestamp <= TimestampMillisecond(100000000, None) [tag_0:Utf8, tag_1:Utf8, timestamp:Timestamp(ms), field_0:Float64;N, field_1:Float64;N]\
\n TableScan: some_metric [tag_0:Utf8, tag_1:Utf8, timestamp:Timestamp(ms), field_0:Float64;N, field_1:Float64;N]"
).replace("TEMPLATE", plan_name);
assert_eq!(
plan.display_indent_schema().to_string(),
@@ -4604,13 +4604,13 @@ mod test {
.await
.unwrap();
let expected_without = String::from(
"Sort: some_metric.tag_0 ASC NULLS LAST, some_metric.timestamp ASC NULLS LAST [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), TEMPLATE(some_metric.field_0):Float64;N, TEMPLATE(some_metric.field_1):Float64;N]\
\n Aggregate: groupBy=[[some_metric.tag_0, some_metric.timestamp]], aggr=[[TEMPLATE(some_metric.field_0), TEMPLATE(some_metric.field_1)]] [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), TEMPLATE(some_metric.field_0):Float64;N, TEMPLATE(some_metric.field_1):Float64;N]\
\n PromInstantManipulate: range=[0..100000000], lookback=[1000], interval=[5000], time index=[timestamp] [tag_0:Utf8, tag_1:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N, field_1:Float64;N]\
\n PromSeriesDivide: tags=[\"tag_0\", \"tag_1\"] [tag_0:Utf8, tag_1:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N, field_1:Float64;N]\
\n Sort: some_metric.tag_0 ASC NULLS FIRST, some_metric.tag_1 ASC NULLS FIRST, some_metric.timestamp ASC NULLS FIRST [tag_0:Utf8, tag_1:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N, field_1:Float64;N]\
\n Filter: some_metric.tag_0 != Utf8(\"bar\") AND some_metric.timestamp >= TimestampMillisecond(-999, None) AND some_metric.timestamp <= TimestampMillisecond(100000000, None) [tag_0:Utf8, tag_1:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N, field_1:Float64;N]\
\n TableScan: some_metric [tag_0:Utf8, tag_1:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N, field_1:Float64;N]"
"Sort: some_metric.tag_0 ASC NULLS LAST, some_metric.timestamp ASC NULLS LAST [tag_0:Utf8, timestamp:Timestamp(ms), TEMPLATE(some_metric.field_0):Float64;N, TEMPLATE(some_metric.field_1):Float64;N]\
\n Aggregate: groupBy=[[some_metric.tag_0, some_metric.timestamp]], aggr=[[TEMPLATE(some_metric.field_0), TEMPLATE(some_metric.field_1)]] [tag_0:Utf8, timestamp:Timestamp(ms), TEMPLATE(some_metric.field_0):Float64;N, TEMPLATE(some_metric.field_1):Float64;N]\
\n PromInstantManipulate: range=[0..100000000], lookback=[1000], interval=[5000], time index=[timestamp] [tag_0:Utf8, tag_1:Utf8, timestamp:Timestamp(ms), field_0:Float64;N, field_1:Float64;N]\
\n PromSeriesDivide: tags=[\"tag_0\", \"tag_1\"] [tag_0:Utf8, tag_1:Utf8, timestamp:Timestamp(ms), field_0:Float64;N, field_1:Float64;N]\
\n Sort: some_metric.tag_0 ASC NULLS FIRST, some_metric.tag_1 ASC NULLS FIRST, some_metric.timestamp ASC NULLS FIRST [tag_0:Utf8, tag_1:Utf8, timestamp:Timestamp(ms), field_0:Float64;N, field_1:Float64;N]\
\n Filter: some_metric.tag_0 != Utf8(\"bar\") AND some_metric.timestamp >= TimestampMillisecond(-999, None) AND some_metric.timestamp <= TimestampMillisecond(100000000, None) [tag_0:Utf8, tag_1:Utf8, timestamp:Timestamp(ms), field_0:Float64;N, field_1:Float64;N]\
\n TableScan: some_metric [tag_0:Utf8, tag_1:Utf8, timestamp:Timestamp(ms), field_0:Float64;N, field_1:Float64;N]"
).replace("TEMPLATE", plan_name);
assert_eq!(plan.display_indent_schema().to_string(), expected_without);
}
@@ -5167,20 +5167,20 @@ mod test {
.unwrap();
let expected = String::from(
"Projection: rhs.tag_0, rhs.timestamp, lhs.field_0 + rhs.field_0 AS lhs.field_0 + rhs.field_0 [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), lhs.field_0 + rhs.field_0:Float64;N]\
\n Inner Join: lhs.tag_0 = rhs.tag_0, lhs.timestamp = rhs.timestamp [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N, tag_0:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N]\
\n SubqueryAlias: lhs [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N]\
\n PromInstantManipulate: range=[0..100000000], lookback=[1000], interval=[5000], time index=[timestamp] [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N]\
\n PromSeriesDivide: tags=[\"tag_0\"] [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N]\
\n Sort: some_metric.tag_0 ASC NULLS FIRST, some_metric.timestamp ASC NULLS FIRST [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N]\
\n Filter: some_metric.tag_0 = Utf8(\"foo\") AND some_metric.timestamp >= TimestampMillisecond(-999, None) AND some_metric.timestamp <= TimestampMillisecond(100000000, None) [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N]\
\n TableScan: some_metric [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N]\
\n SubqueryAlias: rhs [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N]\
\n PromInstantManipulate: range=[0..100000000], lookback=[1000], interval=[5000], time index=[timestamp] [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N]\
\n PromSeriesDivide: tags=[\"tag_0\"] [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N]\
\n Sort: some_metric.tag_0 ASC NULLS FIRST, some_metric.timestamp ASC NULLS FIRST [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N]\
\n Filter: some_metric.tag_0 = Utf8(\"bar\") AND some_metric.timestamp >= TimestampMillisecond(-999, None) AND some_metric.timestamp <= TimestampMillisecond(100000000, None) [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N]\
\n TableScan: some_metric [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N]",
"Projection: rhs.tag_0, rhs.timestamp, lhs.field_0 + rhs.field_0 AS lhs.field_0 + rhs.field_0 [tag_0:Utf8, timestamp:Timestamp(ms), lhs.field_0 + rhs.field_0:Float64;N]\
\n Inner Join: lhs.tag_0 = rhs.tag_0, lhs.timestamp = rhs.timestamp [tag_0:Utf8, timestamp:Timestamp(ms), field_0:Float64;N, tag_0:Utf8, timestamp:Timestamp(ms), field_0:Float64;N]\
\n SubqueryAlias: lhs [tag_0:Utf8, timestamp:Timestamp(ms), field_0:Float64;N]\
\n PromInstantManipulate: range=[0..100000000], lookback=[1000], interval=[5000], time index=[timestamp] [tag_0:Utf8, timestamp:Timestamp(ms), field_0:Float64;N]\
\n PromSeriesDivide: tags=[\"tag_0\"] [tag_0:Utf8, timestamp:Timestamp(ms), field_0:Float64;N]\
\n Sort: some_metric.tag_0 ASC NULLS FIRST, some_metric.timestamp ASC NULLS FIRST [tag_0:Utf8, timestamp:Timestamp(ms), field_0:Float64;N]\
\n Filter: some_metric.tag_0 = Utf8(\"foo\") AND some_metric.timestamp >= TimestampMillisecond(-999, None) AND some_metric.timestamp <= TimestampMillisecond(100000000, None) [tag_0:Utf8, timestamp:Timestamp(ms), field_0:Float64;N]\
\n TableScan: some_metric [tag_0:Utf8, timestamp:Timestamp(ms), field_0:Float64;N]\
\n SubqueryAlias: rhs [tag_0:Utf8, timestamp:Timestamp(ms), field_0:Float64;N]\
\n PromInstantManipulate: range=[0..100000000], lookback=[1000], interval=[5000], time index=[timestamp] [tag_0:Utf8, timestamp:Timestamp(ms), field_0:Float64;N]\
\n PromSeriesDivide: tags=[\"tag_0\"] [tag_0:Utf8, timestamp:Timestamp(ms), field_0:Float64;N]\
\n Sort: some_metric.tag_0 ASC NULLS FIRST, some_metric.timestamp ASC NULLS FIRST [tag_0:Utf8, timestamp:Timestamp(ms), field_0:Float64;N]\
\n Filter: some_metric.tag_0 = Utf8(\"bar\") AND some_metric.timestamp >= TimestampMillisecond(-999, None) AND some_metric.timestamp <= TimestampMillisecond(100000000, None) [tag_0:Utf8, timestamp:Timestamp(ms), field_0:Float64;N]\
\n TableScan: some_metric [tag_0:Utf8, timestamp:Timestamp(ms), field_0:Float64;N]",
);
assert_eq!(plan.display_indent_schema().to_string(), expected);
@@ -5222,12 +5222,12 @@ mod test {
async fn binary_op_literal_column() {
let query = r#"1 + some_metric{tag_0="bar"}"#;
let expected = String::from(
"Projection: some_metric.tag_0, some_metric.timestamp, Float64(1) + some_metric.field_0 AS Float64(1) + field_0 [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), Float64(1) + field_0:Float64;N]\
\n PromInstantManipulate: range=[0..100000000], lookback=[1000], interval=[5000], time index=[timestamp] [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N]\
\n PromSeriesDivide: tags=[\"tag_0\"] [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N]\
\n Sort: some_metric.tag_0 ASC NULLS FIRST, some_metric.timestamp ASC NULLS FIRST [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N]\
\n Filter: some_metric.tag_0 = Utf8(\"bar\") AND some_metric.timestamp >= TimestampMillisecond(-999, None) AND some_metric.timestamp <= TimestampMillisecond(100000000, None) [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N]\
\n TableScan: some_metric [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N]",
"Projection: some_metric.tag_0, some_metric.timestamp, Float64(1) + some_metric.field_0 AS Float64(1) + field_0 [tag_0:Utf8, timestamp:Timestamp(ms), Float64(1) + field_0:Float64;N]\
\n PromInstantManipulate: range=[0..100000000], lookback=[1000], interval=[5000], time index=[timestamp] [tag_0:Utf8, timestamp:Timestamp(ms), field_0:Float64;N]\
\n PromSeriesDivide: tags=[\"tag_0\"] [tag_0:Utf8, timestamp:Timestamp(ms), field_0:Float64;N]\
\n Sort: some_metric.tag_0 ASC NULLS FIRST, some_metric.timestamp ASC NULLS FIRST [tag_0:Utf8, timestamp:Timestamp(ms), field_0:Float64;N]\
\n Filter: some_metric.tag_0 = Utf8(\"bar\") AND some_metric.timestamp >= TimestampMillisecond(-999, None) AND some_metric.timestamp <= TimestampMillisecond(100000000, None) [tag_0:Utf8, timestamp:Timestamp(ms), field_0:Float64;N]\
\n TableScan: some_metric [tag_0:Utf8, timestamp:Timestamp(ms), field_0:Float64;N]",
);
indie_query_plan_compare(query, expected).await;
@@ -5236,8 +5236,8 @@ mod test {
#[tokio::test]
async fn binary_op_literal_literal() {
let query = r#"1 + 1"#;
let expected = r#"EmptyMetric: range=[0..100000000], interval=[5000] [time:Timestamp(Millisecond, None), value:Float64;N]
TableScan: dummy [time:Timestamp(Millisecond, None), value:Float64;N]"#;
let expected = r#"EmptyMetric: range=[0..100000000], interval=[5000] [time:Timestamp(ms), value:Float64;N]
TableScan: dummy [time:Timestamp(ms), value:Float64;N]"#;
indie_query_plan_compare(query, expected).await;
}
@@ -5245,12 +5245,12 @@ mod test {
async fn simple_bool_grammar() {
let query = "some_metric != bool 1.2345";
let expected = String::from(
"Projection: some_metric.tag_0, some_metric.timestamp, CAST(some_metric.field_0 != Float64(1.2345) AS Float64) AS field_0 != Float64(1.2345) [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), field_0 != Float64(1.2345):Float64;N]\
\n PromInstantManipulate: range=[0..100000000], lookback=[1000], interval=[5000], time index=[timestamp] [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N]\
\n PromSeriesDivide: tags=[\"tag_0\"] [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N]\
\n Sort: some_metric.tag_0 ASC NULLS FIRST, some_metric.timestamp ASC NULLS FIRST [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N]\
\n Filter: some_metric.timestamp >= TimestampMillisecond(-999, None) AND some_metric.timestamp <= TimestampMillisecond(100000000, None) [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N]\
\n TableScan: some_metric [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N]",
"Projection: some_metric.tag_0, some_metric.timestamp, CAST(some_metric.field_0 != Float64(1.2345) AS Float64) AS field_0 != Float64(1.2345) [tag_0:Utf8, timestamp:Timestamp(ms), field_0 != Float64(1.2345):Float64;N]\
\n PromInstantManipulate: range=[0..100000000], lookback=[1000], interval=[5000], time index=[timestamp] [tag_0:Utf8, timestamp:Timestamp(ms), field_0:Float64;N]\
\n PromSeriesDivide: tags=[\"tag_0\"] [tag_0:Utf8, timestamp:Timestamp(ms), field_0:Float64;N]\
\n Sort: some_metric.tag_0 ASC NULLS FIRST, some_metric.timestamp ASC NULLS FIRST [tag_0:Utf8, timestamp:Timestamp(ms), field_0:Float64;N]\
\n Filter: some_metric.timestamp >= TimestampMillisecond(-999, None) AND some_metric.timestamp <= TimestampMillisecond(100000000, None) [tag_0:Utf8, timestamp:Timestamp(ms), field_0:Float64;N]\
\n TableScan: some_metric [tag_0:Utf8, timestamp:Timestamp(ms), field_0:Float64;N]",
);
indie_query_plan_compare(query, expected).await;
@@ -5260,12 +5260,12 @@ mod test {
async fn bool_with_additional_arithmetic() {
let query = "some_metric + (1 == bool 2)";
let expected = String::from(
"Projection: some_metric.tag_0, some_metric.timestamp, some_metric.field_0 + CAST(Float64(1) = Float64(2) AS Float64) AS field_0 + Float64(1) = Float64(2) [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), field_0 + Float64(1) = Float64(2):Float64;N]\
\n PromInstantManipulate: range=[0..100000000], lookback=[1000], interval=[5000], time index=[timestamp] [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N]\
\n PromSeriesDivide: tags=[\"tag_0\"] [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N]\
\n Sort: some_metric.tag_0 ASC NULLS FIRST, some_metric.timestamp ASC NULLS FIRST [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N]\
\n Filter: some_metric.timestamp >= TimestampMillisecond(-999, None) AND some_metric.timestamp <= TimestampMillisecond(100000000, None) [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N]\
\n TableScan: some_metric [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N]",
"Projection: some_metric.tag_0, some_metric.timestamp, some_metric.field_0 + CAST(Float64(1) = Float64(2) AS Float64) AS field_0 + Float64(1) = Float64(2) [tag_0:Utf8, timestamp:Timestamp(ms), field_0 + Float64(1) = Float64(2):Float64;N]\
\n PromInstantManipulate: range=[0..100000000], lookback=[1000], interval=[5000], time index=[timestamp] [tag_0:Utf8, timestamp:Timestamp(ms), field_0:Float64;N]\
\n PromSeriesDivide: tags=[\"tag_0\"] [tag_0:Utf8, timestamp:Timestamp(ms), field_0:Float64;N]\
\n Sort: some_metric.tag_0 ASC NULLS FIRST, some_metric.timestamp ASC NULLS FIRST [tag_0:Utf8, timestamp:Timestamp(ms), field_0:Float64;N]\
\n Filter: some_metric.timestamp >= TimestampMillisecond(-999, None) AND some_metric.timestamp <= TimestampMillisecond(100000000, None) [tag_0:Utf8, timestamp:Timestamp(ms), field_0:Float64;N]\
\n TableScan: some_metric [tag_0:Utf8, timestamp:Timestamp(ms), field_0:Float64;N]",
);
indie_query_plan_compare(query, expected).await;
@@ -5275,12 +5275,12 @@ mod test {
async fn simple_unary() {
let query = "-some_metric";
let expected = String::from(
"Projection: some_metric.tag_0, some_metric.timestamp, (- some_metric.field_0) AS (- field_0) [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), (- field_0):Float64;N]\
\n PromInstantManipulate: range=[0..100000000], lookback=[1000], interval=[5000], time index=[timestamp] [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N]\
\n PromSeriesDivide: tags=[\"tag_0\"] [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N]\
\n Sort: some_metric.tag_0 ASC NULLS FIRST, some_metric.timestamp ASC NULLS FIRST [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N]\
\n Filter: some_metric.timestamp >= TimestampMillisecond(-999, None) AND some_metric.timestamp <= TimestampMillisecond(100000000, None) [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N]\
\n TableScan: some_metric [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N]",
"Projection: some_metric.tag_0, some_metric.timestamp, (- some_metric.field_0) AS (- field_0) [tag_0:Utf8, timestamp:Timestamp(ms), (- field_0):Float64;N]\
\n PromInstantManipulate: range=[0..100000000], lookback=[1000], interval=[5000], time index=[timestamp] [tag_0:Utf8, timestamp:Timestamp(ms), field_0:Float64;N]\
\n PromSeriesDivide: tags=[\"tag_0\"] [tag_0:Utf8, timestamp:Timestamp(ms), field_0:Float64;N]\
\n Sort: some_metric.tag_0 ASC NULLS FIRST, some_metric.timestamp ASC NULLS FIRST [tag_0:Utf8, timestamp:Timestamp(ms), field_0:Float64;N]\
\n Filter: some_metric.timestamp >= TimestampMillisecond(-999, None) AND some_metric.timestamp <= TimestampMillisecond(100000000, None) [tag_0:Utf8, timestamp:Timestamp(ms), field_0:Float64;N]\
\n TableScan: some_metric [tag_0:Utf8, timestamp:Timestamp(ms), field_0:Float64;N]",
);
indie_query_plan_compare(query, expected).await;
@@ -5290,14 +5290,14 @@ mod test {
async fn increase_aggr() {
let query = "increase(some_metric[5m])";
let expected = String::from(
"Filter: prom_increase(timestamp_range,field_0,timestamp,Int64(300000)) IS NOT NULL [timestamp:Timestamp(Millisecond, None), prom_increase(timestamp_range,field_0,timestamp,Int64(300000)):Float64;N, tag_0:Utf8]\
\n Projection: some_metric.timestamp, prom_increase(timestamp_range, field_0, some_metric.timestamp, Int64(300000)) AS prom_increase(timestamp_range,field_0,timestamp,Int64(300000)), some_metric.tag_0 [timestamp:Timestamp(Millisecond, None), prom_increase(timestamp_range,field_0,timestamp,Int64(300000)):Float64;N, tag_0:Utf8]\
\n PromRangeManipulate: req range=[0..100000000], interval=[5000], eval range=[300000], time index=[timestamp], values=[\"field_0\"] [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Dictionary(Int64, Float64);N, timestamp_range:Dictionary(Int64, Timestamp(Millisecond, None))]\
\n PromSeriesNormalize: offset=[0], time index=[timestamp], filter NaN: [true] [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N]\
\n PromSeriesDivide: tags=[\"tag_0\"] [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N]\
\n Sort: some_metric.tag_0 ASC NULLS FIRST, some_metric.timestamp ASC NULLS FIRST [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N]\
\n Filter: some_metric.timestamp >= TimestampMillisecond(-299999, None) AND some_metric.timestamp <= TimestampMillisecond(100000000, None) [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N]\
\n TableScan: some_metric [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N]",
"Filter: prom_increase(timestamp_range,field_0,timestamp,Int64(300000)) IS NOT NULL [timestamp:Timestamp(ms), prom_increase(timestamp_range,field_0,timestamp,Int64(300000)):Float64;N, tag_0:Utf8]\
\n Projection: some_metric.timestamp, prom_increase(timestamp_range, field_0, some_metric.timestamp, Int64(300000)) AS prom_increase(timestamp_range,field_0,timestamp,Int64(300000)), some_metric.tag_0 [timestamp:Timestamp(ms), prom_increase(timestamp_range,field_0,timestamp,Int64(300000)):Float64;N, tag_0:Utf8]\
\n PromRangeManipulate: req range=[0..100000000], interval=[5000], eval range=[300000], time index=[timestamp], values=[\"field_0\"] [tag_0:Utf8, timestamp:Timestamp(ms), field_0:Dictionary(Int64, Float64);N, timestamp_range:Dictionary(Int64, Timestamp(ms))]\
\n PromSeriesNormalize: offset=[0], time index=[timestamp], filter NaN: [true] [tag_0:Utf8, timestamp:Timestamp(ms), field_0:Float64;N]\
\n PromSeriesDivide: tags=[\"tag_0\"] [tag_0:Utf8, timestamp:Timestamp(ms), field_0:Float64;N]\
\n Sort: some_metric.tag_0 ASC NULLS FIRST, some_metric.timestamp ASC NULLS FIRST [tag_0:Utf8, timestamp:Timestamp(ms), field_0:Float64;N]\
\n Filter: some_metric.timestamp >= TimestampMillisecond(-299999, None) AND some_metric.timestamp <= TimestampMillisecond(100000000, None) [tag_0:Utf8, timestamp:Timestamp(ms), field_0:Float64;N]\
\n TableScan: some_metric [tag_0:Utf8, timestamp:Timestamp(ms), field_0:Float64;N]",
);
indie_query_plan_compare(query, expected).await;
@@ -5307,12 +5307,12 @@ mod test {
async fn less_filter_on_value() {
let query = "some_metric < 1.2345";
let expected = String::from(
"Filter: some_metric.field_0 < Float64(1.2345) [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N]\
\n PromInstantManipulate: range=[0..100000000], lookback=[1000], interval=[5000], time index=[timestamp] [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N]\
\n PromSeriesDivide: tags=[\"tag_0\"] [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N]\
\n Sort: some_metric.tag_0 ASC NULLS FIRST, some_metric.timestamp ASC NULLS FIRST [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N]\
\n Filter: some_metric.timestamp >= TimestampMillisecond(-999, None) AND some_metric.timestamp <= TimestampMillisecond(100000000, None) [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N]\
\n TableScan: some_metric [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N]",
"Filter: some_metric.field_0 < Float64(1.2345) [tag_0:Utf8, timestamp:Timestamp(ms), field_0:Float64;N]\
\n PromInstantManipulate: range=[0..100000000], lookback=[1000], interval=[5000], time index=[timestamp] [tag_0:Utf8, timestamp:Timestamp(ms), field_0:Float64;N]\
\n PromSeriesDivide: tags=[\"tag_0\"] [tag_0:Utf8, timestamp:Timestamp(ms), field_0:Float64;N]\
\n Sort: some_metric.tag_0 ASC NULLS FIRST, some_metric.timestamp ASC NULLS FIRST [tag_0:Utf8, timestamp:Timestamp(ms), field_0:Float64;N]\
\n Filter: some_metric.timestamp >= TimestampMillisecond(-999, None) AND some_metric.timestamp <= TimestampMillisecond(100000000, None) [tag_0:Utf8, timestamp:Timestamp(ms), field_0:Float64;N]\
\n TableScan: some_metric [tag_0:Utf8, timestamp:Timestamp(ms), field_0:Float64;N]",
);
indie_query_plan_compare(query, expected).await;
@@ -5322,14 +5322,14 @@ mod test {
async fn count_over_time() {
let query = "count_over_time(some_metric[5m])";
let expected = String::from(
"Filter: prom_count_over_time(timestamp_range,field_0) IS NOT NULL [timestamp:Timestamp(Millisecond, None), prom_count_over_time(timestamp_range,field_0):Float64;N, tag_0:Utf8]\
\n Projection: some_metric.timestamp, prom_count_over_time(timestamp_range, field_0) AS prom_count_over_time(timestamp_range,field_0), some_metric.tag_0 [timestamp:Timestamp(Millisecond, None), prom_count_over_time(timestamp_range,field_0):Float64;N, tag_0:Utf8]\
\n PromRangeManipulate: req range=[0..100000000], interval=[5000], eval range=[300000], time index=[timestamp], values=[\"field_0\"] [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Dictionary(Int64, Float64);N, timestamp_range:Dictionary(Int64, Timestamp(Millisecond, None))]\
\n PromSeriesNormalize: offset=[0], time index=[timestamp], filter NaN: [true] [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N]\
\n PromSeriesDivide: tags=[\"tag_0\"] [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N]\
\n Sort: some_metric.tag_0 ASC NULLS FIRST, some_metric.timestamp ASC NULLS FIRST [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N]\
\n Filter: some_metric.timestamp >= TimestampMillisecond(-299999, None) AND some_metric.timestamp <= TimestampMillisecond(100000000, None) [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N]\
\n TableScan: some_metric [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N]",
"Filter: prom_count_over_time(timestamp_range,field_0) IS NOT NULL [timestamp:Timestamp(ms), prom_count_over_time(timestamp_range,field_0):Float64;N, tag_0:Utf8]\
\n Projection: some_metric.timestamp, prom_count_over_time(timestamp_range, field_0) AS prom_count_over_time(timestamp_range,field_0), some_metric.tag_0 [timestamp:Timestamp(ms), prom_count_over_time(timestamp_range,field_0):Float64;N, tag_0:Utf8]\
\n PromRangeManipulate: req range=[0..100000000], interval=[5000], eval range=[300000], time index=[timestamp], values=[\"field_0\"] [tag_0:Utf8, timestamp:Timestamp(ms), field_0:Dictionary(Int64, Float64);N, timestamp_range:Dictionary(Int64, Timestamp(ms))]\
\n PromSeriesNormalize: offset=[0], time index=[timestamp], filter NaN: [true] [tag_0:Utf8, timestamp:Timestamp(ms), field_0:Float64;N]\
\n PromSeriesDivide: tags=[\"tag_0\"] [tag_0:Utf8, timestamp:Timestamp(ms), field_0:Float64;N]\
\n Sort: some_metric.tag_0 ASC NULLS FIRST, some_metric.timestamp ASC NULLS FIRST [tag_0:Utf8, timestamp:Timestamp(ms), field_0:Float64;N]\
\n Filter: some_metric.timestamp >= TimestampMillisecond(-299999, None) AND some_metric.timestamp <= TimestampMillisecond(100000000, None) [tag_0:Utf8, timestamp:Timestamp(ms), field_0:Float64;N]\
\n TableScan: some_metric [tag_0:Utf8, timestamp:Timestamp(ms), field_0:Float64;N]",
);
indie_query_plan_compare(query, expected).await;
@@ -5739,42 +5739,42 @@ mod test {
async fn custom_schema() {
let query = "some_alt_metric{__schema__=\"greptime_private\"}";
let expected = String::from(
"PromInstantManipulate: range=[0..100000000], lookback=[1000], interval=[5000], time index=[timestamp] [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N]\
\n PromSeriesDivide: tags=[\"tag_0\"] [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N]\
\n Sort: greptime_private.some_alt_metric.tag_0 ASC NULLS FIRST, greptime_private.some_alt_metric.timestamp ASC NULLS FIRST [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N]\
\n Filter: greptime_private.some_alt_metric.timestamp >= TimestampMillisecond(-999, None) AND greptime_private.some_alt_metric.timestamp <= TimestampMillisecond(100000000, None) [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N]\
\n TableScan: greptime_private.some_alt_metric [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N]",
"PromInstantManipulate: range=[0..100000000], lookback=[1000], interval=[5000], time index=[timestamp] [tag_0:Utf8, timestamp:Timestamp(ms), field_0:Float64;N]\
\n PromSeriesDivide: tags=[\"tag_0\"] [tag_0:Utf8, timestamp:Timestamp(ms), field_0:Float64;N]\
\n Sort: greptime_private.some_alt_metric.tag_0 ASC NULLS FIRST, greptime_private.some_alt_metric.timestamp ASC NULLS FIRST [tag_0:Utf8, timestamp:Timestamp(ms), field_0:Float64;N]\
\n Filter: greptime_private.some_alt_metric.timestamp >= TimestampMillisecond(-999, None) AND greptime_private.some_alt_metric.timestamp <= TimestampMillisecond(100000000, None) [tag_0:Utf8, timestamp:Timestamp(ms), field_0:Float64;N]\
\n TableScan: greptime_private.some_alt_metric [tag_0:Utf8, timestamp:Timestamp(ms), field_0:Float64;N]",
);
indie_query_plan_compare(query, expected).await;
let query = "some_alt_metric{__database__=\"greptime_private\"}";
let expected = String::from(
"PromInstantManipulate: range=[0..100000000], lookback=[1000], interval=[5000], time index=[timestamp] [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N]\
\n PromSeriesDivide: tags=[\"tag_0\"] [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N]\
\n Sort: greptime_private.some_alt_metric.tag_0 ASC NULLS FIRST, greptime_private.some_alt_metric.timestamp ASC NULLS FIRST [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N]\
\n Filter: greptime_private.some_alt_metric.timestamp >= TimestampMillisecond(-999, None) AND greptime_private.some_alt_metric.timestamp <= TimestampMillisecond(100000000, None) [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N]\
\n TableScan: greptime_private.some_alt_metric [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N]",
"PromInstantManipulate: range=[0..100000000], lookback=[1000], interval=[5000], time index=[timestamp] [tag_0:Utf8, timestamp:Timestamp(ms), field_0:Float64;N]\
\n PromSeriesDivide: tags=[\"tag_0\"] [tag_0:Utf8, timestamp:Timestamp(ms), field_0:Float64;N]\
\n Sort: greptime_private.some_alt_metric.tag_0 ASC NULLS FIRST, greptime_private.some_alt_metric.timestamp ASC NULLS FIRST [tag_0:Utf8, timestamp:Timestamp(ms), field_0:Float64;N]\
\n Filter: greptime_private.some_alt_metric.timestamp >= TimestampMillisecond(-999, None) AND greptime_private.some_alt_metric.timestamp <= TimestampMillisecond(100000000, None) [tag_0:Utf8, timestamp:Timestamp(ms), field_0:Float64;N]\
\n TableScan: greptime_private.some_alt_metric [tag_0:Utf8, timestamp:Timestamp(ms), field_0:Float64;N]",
);
indie_query_plan_compare(query, expected).await;
let query = "some_alt_metric{__schema__=\"greptime_private\"} / some_metric";
let expected = String::from(
"Projection: some_metric.tag_0, some_metric.timestamp, greptime_private.some_alt_metric.field_0 / some_metric.field_0 AS greptime_private.some_alt_metric.field_0 / some_metric.field_0 [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), greptime_private.some_alt_metric.field_0 / some_metric.field_0:Float64;N]\
\n Inner Join: greptime_private.some_alt_metric.tag_0 = some_metric.tag_0, greptime_private.some_alt_metric.timestamp = some_metric.timestamp [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N, tag_0:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N]\
\n SubqueryAlias: greptime_private.some_alt_metric [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N]\
\n PromInstantManipulate: range=[0..100000000], lookback=[1000], interval=[5000], time index=[timestamp] [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N]\
\n PromSeriesDivide: tags=[\"tag_0\"] [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N]\
\n Sort: greptime_private.some_alt_metric.tag_0 ASC NULLS FIRST, greptime_private.some_alt_metric.timestamp ASC NULLS FIRST [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N]\
\n Filter: greptime_private.some_alt_metric.timestamp >= TimestampMillisecond(-999, None) AND greptime_private.some_alt_metric.timestamp <= TimestampMillisecond(100000000, None) [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N]\
\n TableScan: greptime_private.some_alt_metric [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N]\
\n SubqueryAlias: some_metric [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N]\
\n PromInstantManipulate: range=[0..100000000], lookback=[1000], interval=[5000], time index=[timestamp] [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N]\
\n PromSeriesDivide: tags=[\"tag_0\"] [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N]\
\n Sort: some_metric.tag_0 ASC NULLS FIRST, some_metric.timestamp ASC NULLS FIRST [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N]\
\n Filter: some_metric.timestamp >= TimestampMillisecond(-999, None) AND some_metric.timestamp <= TimestampMillisecond(100000000, None) [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N]\
\n TableScan: some_metric [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N]",
"Projection: some_metric.tag_0, some_metric.timestamp, greptime_private.some_alt_metric.field_0 / some_metric.field_0 AS greptime_private.some_alt_metric.field_0 / some_metric.field_0 [tag_0:Utf8, timestamp:Timestamp(ms), greptime_private.some_alt_metric.field_0 / some_metric.field_0:Float64;N]\
\n Inner Join: greptime_private.some_alt_metric.tag_0 = some_metric.tag_0, greptime_private.some_alt_metric.timestamp = some_metric.timestamp [tag_0:Utf8, timestamp:Timestamp(ms), field_0:Float64;N, tag_0:Utf8, timestamp:Timestamp(ms), field_0:Float64;N]\
\n SubqueryAlias: greptime_private.some_alt_metric [tag_0:Utf8, timestamp:Timestamp(ms), field_0:Float64;N]\
\n PromInstantManipulate: range=[0..100000000], lookback=[1000], interval=[5000], time index=[timestamp] [tag_0:Utf8, timestamp:Timestamp(ms), field_0:Float64;N]\
\n PromSeriesDivide: tags=[\"tag_0\"] [tag_0:Utf8, timestamp:Timestamp(ms), field_0:Float64;N]\
\n Sort: greptime_private.some_alt_metric.tag_0 ASC NULLS FIRST, greptime_private.some_alt_metric.timestamp ASC NULLS FIRST [tag_0:Utf8, timestamp:Timestamp(ms), field_0:Float64;N]\
\n Filter: greptime_private.some_alt_metric.timestamp >= TimestampMillisecond(-999, None) AND greptime_private.some_alt_metric.timestamp <= TimestampMillisecond(100000000, None) [tag_0:Utf8, timestamp:Timestamp(ms), field_0:Float64;N]\
\n TableScan: greptime_private.some_alt_metric [tag_0:Utf8, timestamp:Timestamp(ms), field_0:Float64;N]\
\n SubqueryAlias: some_metric [tag_0:Utf8, timestamp:Timestamp(ms), field_0:Float64;N]\
\n PromInstantManipulate: range=[0..100000000], lookback=[1000], interval=[5000], time index=[timestamp] [tag_0:Utf8, timestamp:Timestamp(ms), field_0:Float64;N]\
\n PromSeriesDivide: tags=[\"tag_0\"] [tag_0:Utf8, timestamp:Timestamp(ms), field_0:Float64;N]\
\n Sort: some_metric.tag_0 ASC NULLS FIRST, some_metric.timestamp ASC NULLS FIRST [tag_0:Utf8, timestamp:Timestamp(ms), field_0:Float64;N]\
\n Filter: some_metric.timestamp >= TimestampMillisecond(-999, None) AND some_metric.timestamp <= TimestampMillisecond(100000000, None) [tag_0:Utf8, timestamp:Timestamp(ms), field_0:Float64;N]\
\n TableScan: some_metric [tag_0:Utf8, timestamp:Timestamp(ms), field_0:Float64;N]",
);
indie_query_plan_compare(query, expected).await;
@@ -5891,12 +5891,12 @@ mod test {
.unwrap();
assert_eq!(
plan.display_indent_schema().to_string(),
"PromInstantManipulate: range=[0..100000000], lookback=[1000], interval=[5000], time index=[timestamp] [field:Float64;N, tag:Utf8, timestamp:Timestamp(Millisecond, None)]\
\n PromSeriesDivide: tags=[\"tag\"] [field:Float64;N, tag:Utf8, timestamp:Timestamp(Millisecond, None)]\
\n Sort: metrics.tag ASC NULLS FIRST, metrics.timestamp ASC NULLS FIRST [field:Float64;N, tag:Utf8, timestamp:Timestamp(Millisecond, None)]\
\n Filter: metrics.tag = Utf8(\"1\") AND metrics.timestamp >= TimestampMillisecond(-999, None) AND metrics.timestamp <= TimestampMillisecond(100000000, None) [field:Float64;N, tag:Utf8, timestamp:Timestamp(Millisecond, None)]\
\n Projection: metrics.field, metrics.tag, CAST(metrics.timestamp AS Timestamp(ms)) AS timestamp [field:Float64;N, tag:Utf8, timestamp:Timestamp(Millisecond, None)]\
\n TableScan: metrics [tag:Utf8, timestamp:Timestamp(Nanosecond, None), field:Float64;N]"
"PromInstantManipulate: range=[0..100000000], lookback=[1000], interval=[5000], time index=[timestamp] [field:Float64;N, tag:Utf8, timestamp:Timestamp(ms)]\
\n PromSeriesDivide: tags=[\"tag\"] [field:Float64;N, tag:Utf8, timestamp:Timestamp(ms)]\
\n Sort: metrics.tag ASC NULLS FIRST, metrics.timestamp ASC NULLS FIRST [field:Float64;N, tag:Utf8, timestamp:Timestamp(ms)]\
\n Filter: metrics.tag = Utf8(\"1\") AND metrics.timestamp >= TimestampMillisecond(-999, None) AND metrics.timestamp <= TimestampMillisecond(100000000, None) [field:Float64;N, tag:Utf8, timestamp:Timestamp(ms)]\
\n Projection: metrics.field, metrics.tag, CAST(metrics.timestamp AS Timestamp(ms)) AS timestamp [field:Float64;N, tag:Utf8, timestamp:Timestamp(ms)]\
\n TableScan: metrics [tag:Utf8, timestamp:Timestamp(ns), field:Float64;N]"
);
let plan = PromPlanner::stmt_to_plan(
DfTableSourceProvider::new(
@@ -5921,15 +5921,15 @@ mod test {
.unwrap();
assert_eq!(
plan.display_indent_schema().to_string(),
"Filter: prom_avg_over_time(timestamp_range,field) IS NOT NULL [timestamp:Timestamp(Millisecond, None), prom_avg_over_time(timestamp_range,field):Float64;N, tag:Utf8]\
\n Projection: metrics.timestamp, prom_avg_over_time(timestamp_range, field) AS prom_avg_over_time(timestamp_range,field), metrics.tag [timestamp:Timestamp(Millisecond, None), prom_avg_over_time(timestamp_range,field):Float64;N, tag:Utf8]\
\n PromRangeManipulate: req range=[0..100000000], interval=[5000], eval range=[5000], time index=[timestamp], values=[\"field\"] [field:Dictionary(Int64, Float64);N, tag:Utf8, timestamp:Timestamp(Millisecond, None), timestamp_range:Dictionary(Int64, Timestamp(Millisecond, None))]\
\n PromSeriesNormalize: offset=[0], time index=[timestamp], filter NaN: [true] [field:Float64;N, tag:Utf8, timestamp:Timestamp(Millisecond, None)]\
\n PromSeriesDivide: tags=[\"tag\"] [field:Float64;N, tag:Utf8, timestamp:Timestamp(Millisecond, None)]\
\n Sort: metrics.tag ASC NULLS FIRST, metrics.timestamp ASC NULLS FIRST [field:Float64;N, tag:Utf8, timestamp:Timestamp(Millisecond, None)]\
\n Filter: metrics.tag = Utf8(\"1\") AND metrics.timestamp >= TimestampMillisecond(-4999, None) AND metrics.timestamp <= TimestampMillisecond(100000000, None) [field:Float64;N, tag:Utf8, timestamp:Timestamp(Millisecond, None)]\
\n Projection: metrics.field, metrics.tag, CAST(metrics.timestamp AS Timestamp(ms)) AS timestamp [field:Float64;N, tag:Utf8, timestamp:Timestamp(Millisecond, None)]\
\n TableScan: metrics [tag:Utf8, timestamp:Timestamp(Nanosecond, None), field:Float64;N]"
"Filter: prom_avg_over_time(timestamp_range,field) IS NOT NULL [timestamp:Timestamp(ms), prom_avg_over_time(timestamp_range,field):Float64;N, tag:Utf8]\
\n Projection: metrics.timestamp, prom_avg_over_time(timestamp_range, field) AS prom_avg_over_time(timestamp_range,field), metrics.tag [timestamp:Timestamp(ms), prom_avg_over_time(timestamp_range,field):Float64;N, tag:Utf8]\
\n PromRangeManipulate: req range=[0..100000000], interval=[5000], eval range=[5000], time index=[timestamp], values=[\"field\"] [field:Dictionary(Int64, Float64);N, tag:Utf8, timestamp:Timestamp(ms), timestamp_range:Dictionary(Int64, Timestamp(ms))]\
\n PromSeriesNormalize: offset=[0], time index=[timestamp], filter NaN: [true] [field:Float64;N, tag:Utf8, timestamp:Timestamp(ms)]\
\n PromSeriesDivide: tags=[\"tag\"] [field:Float64;N, tag:Utf8, timestamp:Timestamp(ms)]\
\n Sort: metrics.tag ASC NULLS FIRST, metrics.timestamp ASC NULLS FIRST [field:Float64;N, tag:Utf8, timestamp:Timestamp(ms)]\
\n Filter: metrics.tag = Utf8(\"1\") AND metrics.timestamp >= TimestampMillisecond(-4999, None) AND metrics.timestamp <= TimestampMillisecond(100000000, None) [field:Float64;N, tag:Utf8, timestamp:Timestamp(ms)]\
\n Projection: metrics.field, metrics.tag, CAST(metrics.timestamp AS Timestamp(ms)) AS timestamp [field:Float64;N, tag:Utf8, timestamp:Timestamp(ms)]\
\n TableScan: metrics [tag:Utf8, timestamp:Timestamp(ns), field:Float64;N]"
);
}
@@ -5986,13 +5986,13 @@ mod test {
.unwrap();
let expected = r#"
Filter: up.field_0 IS NOT NULL [timestamp:Timestamp(Millisecond, None), field_0:Float64;N, foo:Utf8;N, tag_0:Utf8, tag_1:Utf8, tag_2:Utf8, tag_3:Utf8]
Projection: up.timestamp, up.field_0, concat_ws(Utf8(","), up.tag_1, up.tag_2, up.tag_3) AS foo, up.tag_0, up.tag_1, up.tag_2, up.tag_3 [timestamp:Timestamp(Millisecond, None), field_0:Float64;N, foo:Utf8;N, tag_0:Utf8, tag_1:Utf8, tag_2:Utf8, tag_3:Utf8]
PromInstantManipulate: range=[0..100000000], lookback=[1000], interval=[5000], time index=[timestamp] [tag_0:Utf8, tag_1:Utf8, tag_2:Utf8, tag_3:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N]
PromSeriesDivide: tags=["tag_0", "tag_1", "tag_2", "tag_3"] [tag_0:Utf8, tag_1:Utf8, tag_2:Utf8, tag_3:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N]
Sort: up.tag_0 ASC NULLS FIRST, up.tag_1 ASC NULLS FIRST, up.tag_2 ASC NULLS FIRST, up.tag_3 ASC NULLS FIRST, up.timestamp ASC NULLS FIRST [tag_0:Utf8, tag_1:Utf8, tag_2:Utf8, tag_3:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N]
Filter: up.tag_0 = Utf8("api-server") AND up.timestamp >= TimestampMillisecond(-999, None) AND up.timestamp <= TimestampMillisecond(100000000, None) [tag_0:Utf8, tag_1:Utf8, tag_2:Utf8, tag_3:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N]
TableScan: up [tag_0:Utf8, tag_1:Utf8, tag_2:Utf8, tag_3:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N]"#;
Filter: up.field_0 IS NOT NULL [timestamp:Timestamp(ms), field_0:Float64;N, foo:Utf8;N, tag_0:Utf8, tag_1:Utf8, tag_2:Utf8, tag_3:Utf8]
Projection: up.timestamp, up.field_0, concat_ws(Utf8(","), up.tag_1, up.tag_2, up.tag_3) AS foo, up.tag_0, up.tag_1, up.tag_2, up.tag_3 [timestamp:Timestamp(ms), field_0:Float64;N, foo:Utf8;N, tag_0:Utf8, tag_1:Utf8, tag_2:Utf8, tag_3:Utf8]
PromInstantManipulate: range=[0..100000000], lookback=[1000], interval=[5000], time index=[timestamp] [tag_0:Utf8, tag_1:Utf8, tag_2:Utf8, tag_3:Utf8, timestamp:Timestamp(ms), field_0:Float64;N]
PromSeriesDivide: tags=["tag_0", "tag_1", "tag_2", "tag_3"] [tag_0:Utf8, tag_1:Utf8, tag_2:Utf8, tag_3:Utf8, timestamp:Timestamp(ms), field_0:Float64;N]
Sort: up.tag_0 ASC NULLS FIRST, up.tag_1 ASC NULLS FIRST, up.tag_2 ASC NULLS FIRST, up.tag_3 ASC NULLS FIRST, up.timestamp ASC NULLS FIRST [tag_0:Utf8, tag_1:Utf8, tag_2:Utf8, tag_3:Utf8, timestamp:Timestamp(ms), field_0:Float64;N]
Filter: up.tag_0 = Utf8("api-server") AND up.timestamp >= TimestampMillisecond(-999, None) AND up.timestamp <= TimestampMillisecond(100000000, None) [tag_0:Utf8, tag_1:Utf8, tag_2:Utf8, tag_3:Utf8, timestamp:Timestamp(ms), field_0:Float64;N]
TableScan: up [tag_0:Utf8, tag_1:Utf8, tag_2:Utf8, tag_3:Utf8, timestamp:Timestamp(ms), field_0:Float64;N]"#;
let ret = plan.display_indent_schema().to_string();
assert_eq!(format!("\n{ret}"), expected, "\n{}", ret);
@@ -6023,13 +6023,13 @@ Filter: up.field_0 IS NOT NULL [timestamp:Timestamp(Millisecond, None), field_0:
.unwrap();
let expected = r#"
Filter: up.field_0 IS NOT NULL [timestamp:Timestamp(Millisecond, None), field_0:Float64;N, foo:Utf8;N, tag_0:Utf8]
Projection: up.timestamp, up.field_0, regexp_replace(up.tag_0, Utf8("^(?s:(.*):.*)$"), Utf8("$1")) AS foo, up.tag_0 [timestamp:Timestamp(Millisecond, None), field_0:Float64;N, foo:Utf8;N, tag_0:Utf8]
PromInstantManipulate: range=[0..100000000], lookback=[1000], interval=[5000], time index=[timestamp] [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N]
PromSeriesDivide: tags=["tag_0"] [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N]
Sort: up.tag_0 ASC NULLS FIRST, up.timestamp ASC NULLS FIRST [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N]
Filter: up.tag_0 = Utf8("a:c") AND up.timestamp >= TimestampMillisecond(-999, None) AND up.timestamp <= TimestampMillisecond(100000000, None) [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N]
TableScan: up [tag_0:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N]"#;
Filter: up.field_0 IS NOT NULL [timestamp:Timestamp(ms), field_0:Float64;N, foo:Utf8;N, tag_0:Utf8]
Projection: up.timestamp, up.field_0, regexp_replace(up.tag_0, Utf8("^(?s:(.*):.*)$"), Utf8("$1")) AS foo, up.tag_0 [timestamp:Timestamp(ms), field_0:Float64;N, foo:Utf8;N, tag_0:Utf8]
PromInstantManipulate: range=[0..100000000], lookback=[1000], interval=[5000], time index=[timestamp] [tag_0:Utf8, timestamp:Timestamp(ms), field_0:Float64;N]
PromSeriesDivide: tags=["tag_0"] [tag_0:Utf8, timestamp:Timestamp(ms), field_0:Float64;N]
Sort: up.tag_0 ASC NULLS FIRST, up.timestamp ASC NULLS FIRST [tag_0:Utf8, timestamp:Timestamp(ms), field_0:Float64;N]
Filter: up.tag_0 = Utf8("a:c") AND up.timestamp >= TimestampMillisecond(-999, None) AND up.timestamp <= TimestampMillisecond(100000000, None) [tag_0:Utf8, timestamp:Timestamp(ms), field_0:Float64;N]
TableScan: up [tag_0:Utf8, timestamp:Timestamp(ms), field_0:Float64;N]"#;
let ret = plan.display_indent_schema().to_string();
assert_eq!(format!("\n{ret}"), expected, "\n{}", ret);
@@ -6064,13 +6064,13 @@ Filter: up.field_0 IS NOT NULL [timestamp:Timestamp(Millisecond, None), field_0:
PromPlanner::stmt_to_plan(table_provider, &eval_stmt, &build_query_engine_state())
.await
.unwrap();
let expected = "Sort: prometheus_tsdb_head_series.timestamp ASC NULLS LAST [timestamp:Timestamp(Millisecond, None), sum(prometheus_tsdb_head_series.field_0):Float64;N, sum(prometheus_tsdb_head_series.field_1):Float64;N, sum(prometheus_tsdb_head_series.field_2):Float64;N]\
\n Aggregate: groupBy=[[prometheus_tsdb_head_series.timestamp]], aggr=[[sum(prometheus_tsdb_head_series.field_0), sum(prometheus_tsdb_head_series.field_1), sum(prometheus_tsdb_head_series.field_2)]] [timestamp:Timestamp(Millisecond, None), sum(prometheus_tsdb_head_series.field_0):Float64;N, sum(prometheus_tsdb_head_series.field_1):Float64;N, sum(prometheus_tsdb_head_series.field_2):Float64;N]\
\n PromInstantManipulate: range=[0..100000000], lookback=[1000], interval=[5000], time index=[timestamp] [tag_0:Utf8, tag_1:Utf8, tag_2:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N, field_1:Float64;N, field_2:Float64;N]\
\n PromSeriesDivide: tags=[\"tag_0\", \"tag_1\", \"tag_2\"] [tag_0:Utf8, tag_1:Utf8, tag_2:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N, field_1:Float64;N, field_2:Float64;N]\
\n Sort: prometheus_tsdb_head_series.tag_0 ASC NULLS FIRST, prometheus_tsdb_head_series.tag_1 ASC NULLS FIRST, prometheus_tsdb_head_series.tag_2 ASC NULLS FIRST, prometheus_tsdb_head_series.timestamp ASC NULLS FIRST [tag_0:Utf8, tag_1:Utf8, tag_2:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N, field_1:Float64;N, field_2:Float64;N]\
\n Filter: prometheus_tsdb_head_series.tag_1 ~ Utf8(\"^(?:(10.0.160.237:8080|10.0.160.237:9090))$\") AND prometheus_tsdb_head_series.timestamp >= TimestampMillisecond(-999, None) AND prometheus_tsdb_head_series.timestamp <= TimestampMillisecond(100000000, None) [tag_0:Utf8, tag_1:Utf8, tag_2:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N, field_1:Float64;N, field_2:Float64;N]\
\n TableScan: prometheus_tsdb_head_series [tag_0:Utf8, tag_1:Utf8, tag_2:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N, field_1:Float64;N, field_2:Float64;N]";
let expected = "Sort: prometheus_tsdb_head_series.timestamp ASC NULLS LAST [timestamp:Timestamp(ms), sum(prometheus_tsdb_head_series.field_0):Float64;N, sum(prometheus_tsdb_head_series.field_1):Float64;N, sum(prometheus_tsdb_head_series.field_2):Float64;N]\
\n Aggregate: groupBy=[[prometheus_tsdb_head_series.timestamp]], aggr=[[sum(prometheus_tsdb_head_series.field_0), sum(prometheus_tsdb_head_series.field_1), sum(prometheus_tsdb_head_series.field_2)]] [timestamp:Timestamp(ms), sum(prometheus_tsdb_head_series.field_0):Float64;N, sum(prometheus_tsdb_head_series.field_1):Float64;N, sum(prometheus_tsdb_head_series.field_2):Float64;N]\
\n PromInstantManipulate: range=[0..100000000], lookback=[1000], interval=[5000], time index=[timestamp] [tag_0:Utf8, tag_1:Utf8, tag_2:Utf8, timestamp:Timestamp(ms), field_0:Float64;N, field_1:Float64;N, field_2:Float64;N]\
\n PromSeriesDivide: tags=[\"tag_0\", \"tag_1\", \"tag_2\"] [tag_0:Utf8, tag_1:Utf8, tag_2:Utf8, timestamp:Timestamp(ms), field_0:Float64;N, field_1:Float64;N, field_2:Float64;N]\
\n Sort: prometheus_tsdb_head_series.tag_0 ASC NULLS FIRST, prometheus_tsdb_head_series.tag_1 ASC NULLS FIRST, prometheus_tsdb_head_series.tag_2 ASC NULLS FIRST, prometheus_tsdb_head_series.timestamp ASC NULLS FIRST [tag_0:Utf8, tag_1:Utf8, tag_2:Utf8, timestamp:Timestamp(ms), field_0:Float64;N, field_1:Float64;N, field_2:Float64;N]\
\n Filter: prometheus_tsdb_head_series.tag_1 ~ Utf8(\"^(?:(10.0.160.237:8080|10.0.160.237:9090))$\") AND prometheus_tsdb_head_series.timestamp >= TimestampMillisecond(-999, None) AND prometheus_tsdb_head_series.timestamp <= TimestampMillisecond(100000000, None) [tag_0:Utf8, tag_1:Utf8, tag_2:Utf8, timestamp:Timestamp(ms), field_0:Float64;N, field_1:Float64;N, field_2:Float64;N]\
\n TableScan: prometheus_tsdb_head_series [tag_0:Utf8, tag_1:Utf8, tag_2:Utf8, timestamp:Timestamp(ms), field_0:Float64;N, field_1:Float64;N, field_2:Float64;N]";
assert_eq!(plan.display_indent_schema().to_string(), expected);
}
@@ -6108,17 +6108,17 @@ Filter: up.field_0 IS NOT NULL [timestamp:Timestamp(Millisecond, None), field_0:
PromPlanner::stmt_to_plan(table_provider, &eval_stmt, &build_query_engine_state())
.await
.unwrap();
let expected = "Projection: sum(prometheus_tsdb_head_series.greptime_value), prometheus_tsdb_head_series.ip, prometheus_tsdb_head_series.greptime_timestamp [sum(prometheus_tsdb_head_series.greptime_value):Float64;N, ip:Utf8, greptime_timestamp:Timestamp(Millisecond, None)]\
\n Sort: prometheus_tsdb_head_series.greptime_timestamp ASC NULLS LAST, row_number() PARTITION BY [prometheus_tsdb_head_series.greptime_timestamp] ORDER BY [sum(prometheus_tsdb_head_series.greptime_value) DESC NULLS FIRST, prometheus_tsdb_head_series.ip DESC NULLS FIRST] ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW ASC NULLS LAST [ip:Utf8, greptime_timestamp:Timestamp(Millisecond, None), sum(prometheus_tsdb_head_series.greptime_value):Float64;N, row_number() PARTITION BY [prometheus_tsdb_head_series.greptime_timestamp] ORDER BY [sum(prometheus_tsdb_head_series.greptime_value) DESC NULLS FIRST, prometheus_tsdb_head_series.ip DESC NULLS FIRST] ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW:UInt64]\
\n Filter: row_number() PARTITION BY [prometheus_tsdb_head_series.greptime_timestamp] ORDER BY [sum(prometheus_tsdb_head_series.greptime_value) DESC NULLS FIRST, prometheus_tsdb_head_series.ip DESC NULLS FIRST] ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW <= Float64(10) [ip:Utf8, greptime_timestamp:Timestamp(Millisecond, None), sum(prometheus_tsdb_head_series.greptime_value):Float64;N, row_number() PARTITION BY [prometheus_tsdb_head_series.greptime_timestamp] ORDER BY [sum(prometheus_tsdb_head_series.greptime_value) DESC NULLS FIRST, prometheus_tsdb_head_series.ip DESC NULLS FIRST] ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW:UInt64]\
\n WindowAggr: windowExpr=[[row_number() PARTITION BY [prometheus_tsdb_head_series.greptime_timestamp] ORDER BY [sum(prometheus_tsdb_head_series.greptime_value) DESC NULLS FIRST, prometheus_tsdb_head_series.ip DESC NULLS FIRST] ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW]] [ip:Utf8, greptime_timestamp:Timestamp(Millisecond, None), sum(prometheus_tsdb_head_series.greptime_value):Float64;N, row_number() PARTITION BY [prometheus_tsdb_head_series.greptime_timestamp] ORDER BY [sum(prometheus_tsdb_head_series.greptime_value) DESC NULLS FIRST, prometheus_tsdb_head_series.ip DESC NULLS FIRST] ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW:UInt64]\
\n Sort: prometheus_tsdb_head_series.ip ASC NULLS LAST, prometheus_tsdb_head_series.greptime_timestamp ASC NULLS LAST [ip:Utf8, greptime_timestamp:Timestamp(Millisecond, None), sum(prometheus_tsdb_head_series.greptime_value):Float64;N]\
\n Aggregate: groupBy=[[prometheus_tsdb_head_series.ip, prometheus_tsdb_head_series.greptime_timestamp]], aggr=[[sum(prometheus_tsdb_head_series.greptime_value)]] [ip:Utf8, greptime_timestamp:Timestamp(Millisecond, None), sum(prometheus_tsdb_head_series.greptime_value):Float64;N]\
\n PromInstantManipulate: range=[0..100000000], lookback=[1000], interval=[5000], time index=[greptime_timestamp] [ip:Utf8, greptime_timestamp:Timestamp(Millisecond, None), greptime_value:Float64;N]\
\n PromSeriesDivide: tags=[\"ip\"] [ip:Utf8, greptime_timestamp:Timestamp(Millisecond, None), greptime_value:Float64;N]\
\n Sort: prometheus_tsdb_head_series.ip ASC NULLS FIRST, prometheus_tsdb_head_series.greptime_timestamp ASC NULLS FIRST [ip:Utf8, greptime_timestamp:Timestamp(Millisecond, None), greptime_value:Float64;N]\
\n Filter: prometheus_tsdb_head_series.ip ~ Utf8(\"^(?:(10.0.160.237:8080|10.0.160.237:9090))$\") AND prometheus_tsdb_head_series.greptime_timestamp >= TimestampMillisecond(-999, None) AND prometheus_tsdb_head_series.greptime_timestamp <= TimestampMillisecond(100000000, None) [ip:Utf8, greptime_timestamp:Timestamp(Millisecond, None), greptime_value:Float64;N]\
\n TableScan: prometheus_tsdb_head_series [ip:Utf8, greptime_timestamp:Timestamp(Millisecond, None), greptime_value:Float64;N]";
let expected = "Projection: sum(prometheus_tsdb_head_series.greptime_value), prometheus_tsdb_head_series.ip, prometheus_tsdb_head_series.greptime_timestamp [sum(prometheus_tsdb_head_series.greptime_value):Float64;N, ip:Utf8, greptime_timestamp:Timestamp(ms)]\
\n Sort: prometheus_tsdb_head_series.greptime_timestamp ASC NULLS LAST, row_number() PARTITION BY [prometheus_tsdb_head_series.greptime_timestamp] ORDER BY [sum(prometheus_tsdb_head_series.greptime_value) DESC NULLS FIRST, prometheus_tsdb_head_series.ip DESC NULLS FIRST] ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW ASC NULLS LAST [ip:Utf8, greptime_timestamp:Timestamp(ms), sum(prometheus_tsdb_head_series.greptime_value):Float64;N, row_number() PARTITION BY [prometheus_tsdb_head_series.greptime_timestamp] ORDER BY [sum(prometheus_tsdb_head_series.greptime_value) DESC NULLS FIRST, prometheus_tsdb_head_series.ip DESC NULLS FIRST] ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW:UInt64]\
\n Filter: row_number() PARTITION BY [prometheus_tsdb_head_series.greptime_timestamp] ORDER BY [sum(prometheus_tsdb_head_series.greptime_value) DESC NULLS FIRST, prometheus_tsdb_head_series.ip DESC NULLS FIRST] ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW <= Float64(10) [ip:Utf8, greptime_timestamp:Timestamp(ms), sum(prometheus_tsdb_head_series.greptime_value):Float64;N, row_number() PARTITION BY [prometheus_tsdb_head_series.greptime_timestamp] ORDER BY [sum(prometheus_tsdb_head_series.greptime_value) DESC NULLS FIRST, prometheus_tsdb_head_series.ip DESC NULLS FIRST] ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW:UInt64]\
\n WindowAggr: windowExpr=[[row_number() PARTITION BY [prometheus_tsdb_head_series.greptime_timestamp] ORDER BY [sum(prometheus_tsdb_head_series.greptime_value) DESC NULLS FIRST, prometheus_tsdb_head_series.ip DESC NULLS FIRST] ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW]] [ip:Utf8, greptime_timestamp:Timestamp(ms), sum(prometheus_tsdb_head_series.greptime_value):Float64;N, row_number() PARTITION BY [prometheus_tsdb_head_series.greptime_timestamp] ORDER BY [sum(prometheus_tsdb_head_series.greptime_value) DESC NULLS FIRST, prometheus_tsdb_head_series.ip DESC NULLS FIRST] ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW:UInt64]\
\n Sort: prometheus_tsdb_head_series.ip ASC NULLS LAST, prometheus_tsdb_head_series.greptime_timestamp ASC NULLS LAST [ip:Utf8, greptime_timestamp:Timestamp(ms), sum(prometheus_tsdb_head_series.greptime_value):Float64;N]\
\n Aggregate: groupBy=[[prometheus_tsdb_head_series.ip, prometheus_tsdb_head_series.greptime_timestamp]], aggr=[[sum(prometheus_tsdb_head_series.greptime_value)]] [ip:Utf8, greptime_timestamp:Timestamp(ms), sum(prometheus_tsdb_head_series.greptime_value):Float64;N]\
\n PromInstantManipulate: range=[0..100000000], lookback=[1000], interval=[5000], time index=[greptime_timestamp] [ip:Utf8, greptime_timestamp:Timestamp(ms), greptime_value:Float64;N]\
\n PromSeriesDivide: tags=[\"ip\"] [ip:Utf8, greptime_timestamp:Timestamp(ms), greptime_value:Float64;N]\
\n Sort: prometheus_tsdb_head_series.ip ASC NULLS FIRST, prometheus_tsdb_head_series.greptime_timestamp ASC NULLS FIRST [ip:Utf8, greptime_timestamp:Timestamp(ms), greptime_value:Float64;N]\
\n Filter: prometheus_tsdb_head_series.ip ~ Utf8(\"^(?:(10.0.160.237:8080|10.0.160.237:9090))$\") AND prometheus_tsdb_head_series.greptime_timestamp >= TimestampMillisecond(-999, None) AND prometheus_tsdb_head_series.greptime_timestamp <= TimestampMillisecond(100000000, None) [ip:Utf8, greptime_timestamp:Timestamp(ms), greptime_value:Float64;N]\
\n TableScan: prometheus_tsdb_head_series [ip:Utf8, greptime_timestamp:Timestamp(ms), greptime_value:Float64;N]";
assert_eq!(plan.display_indent_schema().to_string(), expected);
}
@@ -6157,15 +6157,15 @@ Filter: up.field_0 IS NOT NULL [timestamp:Timestamp(Millisecond, None), field_0:
PromPlanner::stmt_to_plan(table_provider, &eval_stmt, &build_query_engine_state())
.await
.unwrap();
let expected = "Projection: count(prometheus_tsdb_head_series.greptime_value), prometheus_tsdb_head_series.ip, prometheus_tsdb_head_series.greptime_timestamp, series [count(prometheus_tsdb_head_series.greptime_value):Int64, ip:Utf8, greptime_timestamp:Timestamp(Millisecond, None), series:Float64;N]\
\n Sort: prometheus_tsdb_head_series.ip ASC NULLS LAST, prometheus_tsdb_head_series.greptime_timestamp ASC NULLS LAST, prometheus_tsdb_head_series.greptime_value ASC NULLS LAST [count(prometheus_tsdb_head_series.greptime_value):Int64, ip:Utf8, greptime_timestamp:Timestamp(Millisecond, None), series:Float64;N, greptime_value:Float64;N]\
\n Projection: count(prometheus_tsdb_head_series.greptime_value), prometheus_tsdb_head_series.ip, prometheus_tsdb_head_series.greptime_timestamp, prometheus_tsdb_head_series.greptime_value AS series, prometheus_tsdb_head_series.greptime_value [count(prometheus_tsdb_head_series.greptime_value):Int64, ip:Utf8, greptime_timestamp:Timestamp(Millisecond, None), series:Float64;N, greptime_value:Float64;N]\
\n Aggregate: groupBy=[[prometheus_tsdb_head_series.ip, prometheus_tsdb_head_series.greptime_timestamp, prometheus_tsdb_head_series.greptime_value]], aggr=[[count(prometheus_tsdb_head_series.greptime_value)]] [ip:Utf8, greptime_timestamp:Timestamp(Millisecond, None), greptime_value:Float64;N, count(prometheus_tsdb_head_series.greptime_value):Int64]\
\n PromInstantManipulate: range=[0..100000000], lookback=[1000], interval=[5000], time index=[greptime_timestamp] [ip:Utf8, greptime_timestamp:Timestamp(Millisecond, None), greptime_value:Float64;N]\
\n PromSeriesDivide: tags=[\"ip\"] [ip:Utf8, greptime_timestamp:Timestamp(Millisecond, None), greptime_value:Float64;N]\
\n Sort: prometheus_tsdb_head_series.ip ASC NULLS FIRST, prometheus_tsdb_head_series.greptime_timestamp ASC NULLS FIRST [ip:Utf8, greptime_timestamp:Timestamp(Millisecond, None), greptime_value:Float64;N]\
\n Filter: prometheus_tsdb_head_series.ip ~ Utf8(\"^(?:(10.0.160.237:8080|10.0.160.237:9090))$\") AND prometheus_tsdb_head_series.greptime_timestamp >= TimestampMillisecond(-999, None) AND prometheus_tsdb_head_series.greptime_timestamp <= TimestampMillisecond(100000000, None) [ip:Utf8, greptime_timestamp:Timestamp(Millisecond, None), greptime_value:Float64;N]\
\n TableScan: prometheus_tsdb_head_series [ip:Utf8, greptime_timestamp:Timestamp(Millisecond, None), greptime_value:Float64;N]";
let expected = "Projection: count(prometheus_tsdb_head_series.greptime_value), prometheus_tsdb_head_series.ip, prometheus_tsdb_head_series.greptime_timestamp, series [count(prometheus_tsdb_head_series.greptime_value):Int64, ip:Utf8, greptime_timestamp:Timestamp(ms), series:Float64;N]\
\n Sort: prometheus_tsdb_head_series.ip ASC NULLS LAST, prometheus_tsdb_head_series.greptime_timestamp ASC NULLS LAST, prometheus_tsdb_head_series.greptime_value ASC NULLS LAST [count(prometheus_tsdb_head_series.greptime_value):Int64, ip:Utf8, greptime_timestamp:Timestamp(ms), series:Float64;N, greptime_value:Float64;N]\
\n Projection: count(prometheus_tsdb_head_series.greptime_value), prometheus_tsdb_head_series.ip, prometheus_tsdb_head_series.greptime_timestamp, prometheus_tsdb_head_series.greptime_value AS series, prometheus_tsdb_head_series.greptime_value [count(prometheus_tsdb_head_series.greptime_value):Int64, ip:Utf8, greptime_timestamp:Timestamp(ms), series:Float64;N, greptime_value:Float64;N]\
\n Aggregate: groupBy=[[prometheus_tsdb_head_series.ip, prometheus_tsdb_head_series.greptime_timestamp, prometheus_tsdb_head_series.greptime_value]], aggr=[[count(prometheus_tsdb_head_series.greptime_value)]] [ip:Utf8, greptime_timestamp:Timestamp(ms), greptime_value:Float64;N, count(prometheus_tsdb_head_series.greptime_value):Int64]\
\n PromInstantManipulate: range=[0..100000000], lookback=[1000], interval=[5000], time index=[greptime_timestamp] [ip:Utf8, greptime_timestamp:Timestamp(ms), greptime_value:Float64;N]\
\n PromSeriesDivide: tags=[\"ip\"] [ip:Utf8, greptime_timestamp:Timestamp(ms), greptime_value:Float64;N]\
\n Sort: prometheus_tsdb_head_series.ip ASC NULLS FIRST, prometheus_tsdb_head_series.greptime_timestamp ASC NULLS FIRST [ip:Utf8, greptime_timestamp:Timestamp(ms), greptime_value:Float64;N]\
\n Filter: prometheus_tsdb_head_series.ip ~ Utf8(\"^(?:(10.0.160.237:8080|10.0.160.237:9090))$\") AND prometheus_tsdb_head_series.greptime_timestamp >= TimestampMillisecond(-999, None) AND prometheus_tsdb_head_series.greptime_timestamp <= TimestampMillisecond(100000000, None) [ip:Utf8, greptime_timestamp:Timestamp(ms), greptime_value:Float64;N]\
\n TableScan: prometheus_tsdb_head_series [ip:Utf8, greptime_timestamp:Timestamp(ms), greptime_value:Float64;N]";
assert_eq!(plan.display_indent_schema().to_string(), expected);
}
@@ -6206,16 +6206,16 @@ Filter: up.field_0 IS NOT NULL [timestamp:Timestamp(Millisecond, None), field_0:
.await
.unwrap();
let expected = r#"
Projection: count(prometheus_tsdb_head_series.greptime_value) AS my_series, prometheus_tsdb_head_series.ip, prometheus_tsdb_head_series.greptime_timestamp [my_series:Int64, ip:Utf8, greptime_timestamp:Timestamp(Millisecond, None)]
Projection: count(prometheus_tsdb_head_series.greptime_value), prometheus_tsdb_head_series.ip, prometheus_tsdb_head_series.greptime_timestamp, series [count(prometheus_tsdb_head_series.greptime_value):Int64, ip:Utf8, greptime_timestamp:Timestamp(Millisecond, None), series:Float64;N]
Sort: prometheus_tsdb_head_series.ip ASC NULLS LAST, prometheus_tsdb_head_series.greptime_timestamp ASC NULLS LAST, prometheus_tsdb_head_series.greptime_value ASC NULLS LAST [count(prometheus_tsdb_head_series.greptime_value):Int64, ip:Utf8, greptime_timestamp:Timestamp(Millisecond, None), series:Float64;N, greptime_value:Float64;N]
Projection: count(prometheus_tsdb_head_series.greptime_value), prometheus_tsdb_head_series.ip, prometheus_tsdb_head_series.greptime_timestamp, prometheus_tsdb_head_series.greptime_value AS series, prometheus_tsdb_head_series.greptime_value [count(prometheus_tsdb_head_series.greptime_value):Int64, ip:Utf8, greptime_timestamp:Timestamp(Millisecond, None), series:Float64;N, greptime_value:Float64;N]
Aggregate: groupBy=[[prometheus_tsdb_head_series.ip, prometheus_tsdb_head_series.greptime_timestamp, prometheus_tsdb_head_series.greptime_value]], aggr=[[count(prometheus_tsdb_head_series.greptime_value)]] [ip:Utf8, greptime_timestamp:Timestamp(Millisecond, None), greptime_value:Float64;N, count(prometheus_tsdb_head_series.greptime_value):Int64]
PromInstantManipulate: range=[0..100000000], lookback=[1000], interval=[5000], time index=[greptime_timestamp] [ip:Utf8, greptime_timestamp:Timestamp(Millisecond, None), greptime_value:Float64;N]
PromSeriesDivide: tags=["ip"] [ip:Utf8, greptime_timestamp:Timestamp(Millisecond, None), greptime_value:Float64;N]
Sort: prometheus_tsdb_head_series.ip ASC NULLS FIRST, prometheus_tsdb_head_series.greptime_timestamp ASC NULLS FIRST [ip:Utf8, greptime_timestamp:Timestamp(Millisecond, None), greptime_value:Float64;N]
Filter: prometheus_tsdb_head_series.ip ~ Utf8("^(?:(10.0.160.237:8080|10.0.160.237:9090))$") AND prometheus_tsdb_head_series.greptime_timestamp >= TimestampMillisecond(-999, None) AND prometheus_tsdb_head_series.greptime_timestamp <= TimestampMillisecond(100000000, None) [ip:Utf8, greptime_timestamp:Timestamp(Millisecond, None), greptime_value:Float64;N]
TableScan: prometheus_tsdb_head_series [ip:Utf8, greptime_timestamp:Timestamp(Millisecond, None), greptime_value:Float64;N]"#;
Projection: count(prometheus_tsdb_head_series.greptime_value) AS my_series, prometheus_tsdb_head_series.ip, prometheus_tsdb_head_series.greptime_timestamp [my_series:Int64, ip:Utf8, greptime_timestamp:Timestamp(ms)]
Projection: count(prometheus_tsdb_head_series.greptime_value), prometheus_tsdb_head_series.ip, prometheus_tsdb_head_series.greptime_timestamp, series [count(prometheus_tsdb_head_series.greptime_value):Int64, ip:Utf8, greptime_timestamp:Timestamp(ms), series:Float64;N]
Sort: prometheus_tsdb_head_series.ip ASC NULLS LAST, prometheus_tsdb_head_series.greptime_timestamp ASC NULLS LAST, prometheus_tsdb_head_series.greptime_value ASC NULLS LAST [count(prometheus_tsdb_head_series.greptime_value):Int64, ip:Utf8, greptime_timestamp:Timestamp(ms), series:Float64;N, greptime_value:Float64;N]
Projection: count(prometheus_tsdb_head_series.greptime_value), prometheus_tsdb_head_series.ip, prometheus_tsdb_head_series.greptime_timestamp, prometheus_tsdb_head_series.greptime_value AS series, prometheus_tsdb_head_series.greptime_value [count(prometheus_tsdb_head_series.greptime_value):Int64, ip:Utf8, greptime_timestamp:Timestamp(ms), series:Float64;N, greptime_value:Float64;N]
Aggregate: groupBy=[[prometheus_tsdb_head_series.ip, prometheus_tsdb_head_series.greptime_timestamp, prometheus_tsdb_head_series.greptime_value]], aggr=[[count(prometheus_tsdb_head_series.greptime_value)]] [ip:Utf8, greptime_timestamp:Timestamp(ms), greptime_value:Float64;N, count(prometheus_tsdb_head_series.greptime_value):Int64]
PromInstantManipulate: range=[0..100000000], lookback=[1000], interval=[5000], time index=[greptime_timestamp] [ip:Utf8, greptime_timestamp:Timestamp(ms), greptime_value:Float64;N]
PromSeriesDivide: tags=["ip"] [ip:Utf8, greptime_timestamp:Timestamp(ms), greptime_value:Float64;N]
Sort: prometheus_tsdb_head_series.ip ASC NULLS FIRST, prometheus_tsdb_head_series.greptime_timestamp ASC NULLS FIRST [ip:Utf8, greptime_timestamp:Timestamp(ms), greptime_value:Float64;N]
Filter: prometheus_tsdb_head_series.ip ~ Utf8("^(?:(10.0.160.237:8080|10.0.160.237:9090))$") AND prometheus_tsdb_head_series.greptime_timestamp >= TimestampMillisecond(-999, None) AND prometheus_tsdb_head_series.greptime_timestamp <= TimestampMillisecond(100000000, None) [ip:Utf8, greptime_timestamp:Timestamp(ms), greptime_value:Float64;N]
TableScan: prometheus_tsdb_head_series [ip:Utf8, greptime_timestamp:Timestamp(ms), greptime_value:Float64;N]"#;
assert_eq!(format!("\n{}", plan.display_indent_schema()), expected);
}
@@ -6253,15 +6253,15 @@ Projection: count(prometheus_tsdb_head_series.greptime_value) AS my_series, prom
PromPlanner::stmt_to_plan(table_provider, &eval_stmt, &build_query_engine_state())
.await
.unwrap();
let expected = "Sort: prometheus_tsdb_head_series.greptime_timestamp ASC NULLS LAST [greptime_timestamp:Timestamp(Millisecond, None), quantile(Float64(0.3),sum(prometheus_tsdb_head_series.greptime_value)):Float64;N]\
\n Aggregate: groupBy=[[prometheus_tsdb_head_series.greptime_timestamp]], aggr=[[quantile(Float64(0.3), sum(prometheus_tsdb_head_series.greptime_value))]] [greptime_timestamp:Timestamp(Millisecond, None), quantile(Float64(0.3),sum(prometheus_tsdb_head_series.greptime_value)):Float64;N]\
\n Sort: prometheus_tsdb_head_series.ip ASC NULLS LAST, prometheus_tsdb_head_series.greptime_timestamp ASC NULLS LAST [ip:Utf8, greptime_timestamp:Timestamp(Millisecond, None), sum(prometheus_tsdb_head_series.greptime_value):Float64;N]\
\n Aggregate: groupBy=[[prometheus_tsdb_head_series.ip, prometheus_tsdb_head_series.greptime_timestamp]], aggr=[[sum(prometheus_tsdb_head_series.greptime_value)]] [ip:Utf8, greptime_timestamp:Timestamp(Millisecond, None), sum(prometheus_tsdb_head_series.greptime_value):Float64;N]\
\n PromInstantManipulate: range=[0..100000000], lookback=[1000], interval=[5000], time index=[greptime_timestamp] [ip:Utf8, greptime_timestamp:Timestamp(Millisecond, None), greptime_value:Float64;N]\
\n PromSeriesDivide: tags=[\"ip\"] [ip:Utf8, greptime_timestamp:Timestamp(Millisecond, None), greptime_value:Float64;N]\
\n Sort: prometheus_tsdb_head_series.ip ASC NULLS FIRST, prometheus_tsdb_head_series.greptime_timestamp ASC NULLS FIRST [ip:Utf8, greptime_timestamp:Timestamp(Millisecond, None), greptime_value:Float64;N]\
\n Filter: prometheus_tsdb_head_series.ip ~ Utf8(\"^(?:(10.0.160.237:8080|10.0.160.237:9090))$\") AND prometheus_tsdb_head_series.greptime_timestamp >= TimestampMillisecond(-999, None) AND prometheus_tsdb_head_series.greptime_timestamp <= TimestampMillisecond(100000000, None) [ip:Utf8, greptime_timestamp:Timestamp(Millisecond, None), greptime_value:Float64;N]\
\n TableScan: prometheus_tsdb_head_series [ip:Utf8, greptime_timestamp:Timestamp(Millisecond, None), greptime_value:Float64;N]";
let expected = "Sort: prometheus_tsdb_head_series.greptime_timestamp ASC NULLS LAST [greptime_timestamp:Timestamp(ms), quantile(Float64(0.3),sum(prometheus_tsdb_head_series.greptime_value)):Float64;N]\
\n Aggregate: groupBy=[[prometheus_tsdb_head_series.greptime_timestamp]], aggr=[[quantile(Float64(0.3), sum(prometheus_tsdb_head_series.greptime_value))]] [greptime_timestamp:Timestamp(ms), quantile(Float64(0.3),sum(prometheus_tsdb_head_series.greptime_value)):Float64;N]\
\n Sort: prometheus_tsdb_head_series.ip ASC NULLS LAST, prometheus_tsdb_head_series.greptime_timestamp ASC NULLS LAST [ip:Utf8, greptime_timestamp:Timestamp(ms), sum(prometheus_tsdb_head_series.greptime_value):Float64;N]\
\n Aggregate: groupBy=[[prometheus_tsdb_head_series.ip, prometheus_tsdb_head_series.greptime_timestamp]], aggr=[[sum(prometheus_tsdb_head_series.greptime_value)]] [ip:Utf8, greptime_timestamp:Timestamp(ms), sum(prometheus_tsdb_head_series.greptime_value):Float64;N]\
\n PromInstantManipulate: range=[0..100000000], lookback=[1000], interval=[5000], time index=[greptime_timestamp] [ip:Utf8, greptime_timestamp:Timestamp(ms), greptime_value:Float64;N]\
\n PromSeriesDivide: tags=[\"ip\"] [ip:Utf8, greptime_timestamp:Timestamp(ms), greptime_value:Float64;N]\
\n Sort: prometheus_tsdb_head_series.ip ASC NULLS FIRST, prometheus_tsdb_head_series.greptime_timestamp ASC NULLS FIRST [ip:Utf8, greptime_timestamp:Timestamp(ms), greptime_value:Float64;N]\
\n Filter: prometheus_tsdb_head_series.ip ~ Utf8(\"^(?:(10.0.160.237:8080|10.0.160.237:9090))$\") AND prometheus_tsdb_head_series.greptime_timestamp >= TimestampMillisecond(-999, None) AND prometheus_tsdb_head_series.greptime_timestamp <= TimestampMillisecond(100000000, None) [ip:Utf8, greptime_timestamp:Timestamp(ms), greptime_value:Float64;N]\
\n TableScan: prometheus_tsdb_head_series [ip:Utf8, greptime_timestamp:Timestamp(ms), greptime_value:Float64;N]";
assert_eq!(plan.display_indent_schema().to_string(), expected);
}
@@ -6291,22 +6291,22 @@ Projection: count(prometheus_tsdb_head_series.greptime_value) AS my_series, prom
PromPlanner::stmt_to_plan(table_provider, &eval_stmt, &build_query_engine_state())
.await
.unwrap();
let expected = r#"UnionDistinctOn: on col=[["job"]], ts_col=[greptime_timestamp] [greptime_timestamp:Timestamp(Millisecond, None), job:Utf8, sum(metric_exists.greptime_value):Float64;N]
SubqueryAlias: metric_exists [greptime_timestamp:Timestamp(Millisecond, None), job:Utf8, sum(metric_exists.greptime_value):Float64;N]
Projection: metric_exists.greptime_timestamp, metric_exists.job, sum(metric_exists.greptime_value) [greptime_timestamp:Timestamp(Millisecond, None), job:Utf8, sum(metric_exists.greptime_value):Float64;N]
Sort: metric_exists.job ASC NULLS LAST, metric_exists.greptime_timestamp ASC NULLS LAST [job:Utf8, greptime_timestamp:Timestamp(Millisecond, None), sum(metric_exists.greptime_value):Float64;N]
Aggregate: groupBy=[[metric_exists.job, metric_exists.greptime_timestamp]], aggr=[[sum(metric_exists.greptime_value)]] [job:Utf8, greptime_timestamp:Timestamp(Millisecond, None), sum(metric_exists.greptime_value):Float64;N]
PromInstantManipulate: range=[0..100000000], lookback=[1000], interval=[5000], time index=[greptime_timestamp] [job:Utf8, greptime_timestamp:Timestamp(Millisecond, None), greptime_value:Float64;N]
PromSeriesDivide: tags=["job"] [job:Utf8, greptime_timestamp:Timestamp(Millisecond, None), greptime_value:Float64;N]
Sort: metric_exists.job ASC NULLS FIRST, metric_exists.greptime_timestamp ASC NULLS FIRST [job:Utf8, greptime_timestamp:Timestamp(Millisecond, None), greptime_value:Float64;N]
Filter: metric_exists.greptime_timestamp >= TimestampMillisecond(-999, None) AND metric_exists.greptime_timestamp <= TimestampMillisecond(100000000, None) [job:Utf8, greptime_timestamp:Timestamp(Millisecond, None), greptime_value:Float64;N]
TableScan: metric_exists [job:Utf8, greptime_timestamp:Timestamp(Millisecond, None), greptime_value:Float64;N]
SubqueryAlias: [greptime_timestamp:Timestamp(Millisecond, None), job:Utf8;N, sum(.value):Float64;N]
Projection: .time AS greptime_timestamp, Utf8(NULL) AS job, sum(.value) [greptime_timestamp:Timestamp(Millisecond, None), job:Utf8;N, sum(.value):Float64;N]
Sort: .time ASC NULLS LAST [time:Timestamp(Millisecond, None), sum(.value):Float64;N]
Aggregate: groupBy=[[.time]], aggr=[[sum(.value)]] [time:Timestamp(Millisecond, None), sum(.value):Float64;N]
EmptyMetric: range=[0..-1], interval=[5000] [time:Timestamp(Millisecond, None), value:Float64;N]
TableScan: dummy [time:Timestamp(Millisecond, None), value:Float64;N]"#;
let expected = r#"UnionDistinctOn: on col=[["job"]], ts_col=[greptime_timestamp] [greptime_timestamp:Timestamp(ms), job:Utf8, sum(metric_exists.greptime_value):Float64;N]
SubqueryAlias: metric_exists [greptime_timestamp:Timestamp(ms), job:Utf8, sum(metric_exists.greptime_value):Float64;N]
Projection: metric_exists.greptime_timestamp, metric_exists.job, sum(metric_exists.greptime_value) [greptime_timestamp:Timestamp(ms), job:Utf8, sum(metric_exists.greptime_value):Float64;N]
Sort: metric_exists.job ASC NULLS LAST, metric_exists.greptime_timestamp ASC NULLS LAST [job:Utf8, greptime_timestamp:Timestamp(ms), sum(metric_exists.greptime_value):Float64;N]
Aggregate: groupBy=[[metric_exists.job, metric_exists.greptime_timestamp]], aggr=[[sum(metric_exists.greptime_value)]] [job:Utf8, greptime_timestamp:Timestamp(ms), sum(metric_exists.greptime_value):Float64;N]
PromInstantManipulate: range=[0..100000000], lookback=[1000], interval=[5000], time index=[greptime_timestamp] [job:Utf8, greptime_timestamp:Timestamp(ms), greptime_value:Float64;N]
PromSeriesDivide: tags=["job"] [job:Utf8, greptime_timestamp:Timestamp(ms), greptime_value:Float64;N]
Sort: metric_exists.job ASC NULLS FIRST, metric_exists.greptime_timestamp ASC NULLS FIRST [job:Utf8, greptime_timestamp:Timestamp(ms), greptime_value:Float64;N]
Filter: metric_exists.greptime_timestamp >= TimestampMillisecond(-999, None) AND metric_exists.greptime_timestamp <= TimestampMillisecond(100000000, None) [job:Utf8, greptime_timestamp:Timestamp(ms), greptime_value:Float64;N]
TableScan: metric_exists [job:Utf8, greptime_timestamp:Timestamp(ms), greptime_value:Float64;N]
SubqueryAlias: [greptime_timestamp:Timestamp(ms), job:Utf8;N, sum(.value):Float64;N]
Projection: .time AS greptime_timestamp, Utf8(NULL) AS job, sum(.value) [greptime_timestamp:Timestamp(ms), job:Utf8;N, sum(.value):Float64;N]
Sort: .time ASC NULLS LAST [time:Timestamp(ms), sum(.value):Float64;N]
Aggregate: groupBy=[[.time]], aggr=[[sum(.value)]] [time:Timestamp(ms), sum(.value):Float64;N]
EmptyMetric: range=[0..-1], interval=[5000] [time:Timestamp(ms), value:Float64;N]
TableScan: dummy [time:Timestamp(ms), value:Float64;N]"#;
assert_eq!(plan.display_indent_schema().to_string(), expected);
}

14
src/query/src/range_select/plan.rs
View File

@@ -414,7 +414,7 @@ impl RangeSelect {
.iter()
.map(|i| {
let f = schema_before_project.qualified_field(*i);
(f.0.cloned(), Arc::new(f.1.clone()))
(f.0.cloned(), f.1.clone())
})
.collect();
Arc::new(DFSchema::new_with_metadata(
@@ -688,12 +688,12 @@ impl RangeSelect {
schema_before_project.clone()
};
let by = self.create_physical_expr_list(false, &self.by, input_dfschema, session_state)?;
let cache = PlanProperties::new(
let cache = Arc::new(PlanProperties::new(
EquivalenceProperties::new(schema.clone()),
Partitioning::UnknownPartitioning(1),
EmissionType::Incremental,
Boundedness::Bounded,
);
));
Ok(Arc::new(RangeSelectExec {
input: exec_input,
range_exec,
@@ -760,7 +760,7 @@ pub struct RangeSelectExec {
metric: ExecutionPlanMetricsSet,
schema_project: Option<Vec<usize>>,
schema_before_project: SchemaRef,
cache: PlanProperties,
cache: Arc<PlanProperties>,
}
impl DisplayAs for RangeSelectExec {
@@ -801,7 +801,7 @@ impl ExecutionPlan for RangeSelectExec {
vec![Distribution::SinglePartition]
}
fn properties(&self) -> &PlanProperties {
fn properties(&self) -> &Arc<PlanProperties> {
&self.cache
}
@@ -1340,12 +1340,12 @@ mod test {
Field::new(TIME_INDEX_COLUMN, TimestampMillisecondType::DATA_TYPE, true),
Field::new("host", DataType::Utf8, true),
]));
let cache = PlanProperties::new(
let cache = Arc::new(PlanProperties::new(
EquivalenceProperties::new(schema.clone()),
Partitioning::UnknownPartitioning(1),
EmissionType::Incremental,
Boundedness::Bounded,
);
));
let input_schema = memory_exec.schema().clone();
let range_select_exec = Arc::new(RangeSelectExec {
input: memory_exec,

51
src/query/src/range_select/plan_rewrite.rs
View File

@@ -19,7 +19,6 @@ use std::time::Duration;
use arrow_schema::DataType;
use async_recursion::async_recursion;
use catalog::table_source::DfTableSourceProvider;
use chrono::Utc;
use common_time::interval::{MS_PER_DAY, NANOS_PER_MILLI};
use common_time::timestamp::TimeUnit;
use common_time::{IntervalDayTime, IntervalMonthDayNano, IntervalYearMonth, Timestamp, Timezone};
@@ -28,7 +27,6 @@ use datafusion::prelude::Column;
use datafusion::scalar::ScalarValue;
use datafusion_common::tree_node::{Transformed, TreeNode, TreeNodeRecursion, TreeNodeRewriter};
use datafusion_common::{DFSchema, DataFusionError, Result as DFResult};
use datafusion_expr::execution_props::ExecutionProps;
use datafusion_expr::expr::WildcardOptions;
use datafusion_expr::simplify::SimplifyContext;
use datafusion_expr::{
@@ -146,8 +144,7 @@ fn evaluate_expr_to_millisecond(args: &[Expr], i: usize, interval_only: bool) ->
if interval_only && !interval_only_in_expr(expr) {
return Err(dispose_parse_error(Some(expr)));
}
let execution_props = ExecutionProps::new().with_query_execution_start_time(Utc::now());
let info = SimplifyContext::new(&execution_props).with_schema(Arc::new(DFSchema::empty()));
let info = SimplifyContext::default().with_current_time();
let simplify_expr = ExprSimplifier::new(info).simplify(expr.clone())?;
match simplify_expr {
Expr::Literal(ScalarValue::TimestampNanosecond(ts_nanos, _), _)
@@ -702,8 +699,8 @@ mod test {
async fn range_no_project() {
let query = r#"SELECT timestamp, tag_0, tag_1, avg(field_0 + field_1) RANGE '5m' FROM test ALIGN '1h' by (tag_0,tag_1);"#;
let expected = String::from(
"RangeSelect: range_exprs=[avg(test.field_0 + test.field_1) RANGE 5m], align=3600000ms, align_to=0ms, align_by=[test.tag_0, test.tag_1], time_index=timestamp [timestamp:Timestamp(Millisecond, None), tag_0:Utf8, tag_1:Utf8, avg(test.field_0 + test.field_1) RANGE 5m:Float64;N]\
\n TableScan: test [tag_0:Utf8, tag_1:Utf8, tag_2:Utf8, tag_3:Utf8, tag_4:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N, field_1:Float64;N, field_2:Float64;N, field_3:Float64;N, field_4:Float64;N]",
"RangeSelect: range_exprs=[avg(test.field_0 + test.field_1) RANGE 5m], align=3600000ms, align_to=0ms, align_by=[test.tag_0, test.tag_1], time_index=timestamp [timestamp:Timestamp(ms), tag_0:Utf8, tag_1:Utf8, avg(test.field_0 + test.field_1) RANGE 5m:Float64;N]\
\n TableScan: test [tag_0:Utf8, tag_1:Utf8, tag_2:Utf8, tag_3:Utf8, tag_4:Utf8, timestamp:Timestamp(ms), field_0:Float64;N, field_1:Float64;N, field_2:Float64;N, field_3:Float64;N, field_4:Float64;N]",
);
query_plan_compare(query, expected).await;
}
@@ -713,8 +710,8 @@ mod test {
let query = r#"SELECT (avg(field_0 + field_1)/4) RANGE '5m' FROM test ALIGN '1h' by (tag_0,tag_1);"#;
let expected = String::from(
"Projection: avg(test.field_0 + test.field_1) RANGE 5m / Int64(4) [avg(test.field_0 + test.field_1) RANGE 5m / Int64(4):Float64;N]\
\n RangeSelect: range_exprs=[avg(test.field_0 + test.field_1) RANGE 5m], align=3600000ms, align_to=0ms, align_by=[test.tag_0, test.tag_1], time_index=timestamp [avg(test.field_0 + test.field_1) RANGE 5m:Float64;N, timestamp:Timestamp(Millisecond, None), tag_0:Utf8, tag_1:Utf8]\
\n TableScan: test [tag_0:Utf8, tag_1:Utf8, tag_2:Utf8, tag_3:Utf8, tag_4:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N, field_1:Float64;N, field_2:Float64;N, field_3:Float64;N, field_4:Float64;N]",
\n RangeSelect: range_exprs=[avg(test.field_0 + test.field_1) RANGE 5m], align=3600000ms, align_to=0ms, align_by=[test.tag_0, test.tag_1], time_index=timestamp [avg(test.field_0 + test.field_1) RANGE 5m:Float64;N, timestamp:Timestamp(ms), tag_0:Utf8, tag_1:Utf8]\
\n TableScan: test [tag_0:Utf8, tag_1:Utf8, tag_2:Utf8, tag_3:Utf8, tag_4:Utf8, timestamp:Timestamp(ms), field_0:Float64;N, field_1:Float64;N, field_2:Float64;N, field_3:Float64;N, field_4:Float64;N]",
);
query_plan_compare(query, expected).await;
}
@@ -725,8 +722,8 @@ mod test {
r#"SELECT (covar(field_0 + field_1, field_1)/4) RANGE '5m' FROM test ALIGN '1h';"#;
let expected = String::from(
"Projection: covar_samp(test.field_0 + test.field_1,test.field_1) RANGE 5m / Int64(4) [covar_samp(test.field_0 + test.field_1,test.field_1) RANGE 5m / Int64(4):Float64;N]\
\n RangeSelect: range_exprs=[covar_samp(test.field_0 + test.field_1,test.field_1) RANGE 5m], align=3600000ms, align_to=0ms, align_by=[test.tag_0, test.tag_1, test.tag_2, test.tag_3, test.tag_4], time_index=timestamp [covar_samp(test.field_0 + test.field_1,test.field_1) RANGE 5m:Float64;N, timestamp:Timestamp(Millisecond, None), tag_0:Utf8, tag_1:Utf8, tag_2:Utf8, tag_3:Utf8, tag_4:Utf8]\
\n TableScan: test [tag_0:Utf8, tag_1:Utf8, tag_2:Utf8, tag_3:Utf8, tag_4:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N, field_1:Float64;N, field_2:Float64;N, field_3:Float64;N, field_4:Float64;N]",
\n RangeSelect: range_exprs=[covar_samp(test.field_0 + test.field_1,test.field_1) RANGE 5m], align=3600000ms, align_to=0ms, align_by=[test.tag_0, test.tag_1, test.tag_2, test.tag_3, test.tag_4], time_index=timestamp [covar_samp(test.field_0 + test.field_1,test.field_1) RANGE 5m:Float64;N, timestamp:Timestamp(ms), tag_0:Utf8, tag_1:Utf8, tag_2:Utf8, tag_3:Utf8, tag_4:Utf8]\
\n TableScan: test [tag_0:Utf8, tag_1:Utf8, tag_2:Utf8, tag_3:Utf8, tag_4:Utf8, timestamp:Timestamp(ms), field_0:Float64;N, field_1:Float64;N, field_2:Float64;N, field_3:Float64;N, field_4:Float64;N]",
);
query_plan_compare(query, expected).await;
}
@@ -736,8 +733,8 @@ mod test {
let query = r#"SELECT ((avg(field_0)+sum(field_1))/4) RANGE '5m' FROM test ALIGN '1h' by (tag_0,tag_1) FILL NULL;"#;
let expected = String::from(
"Projection: (avg(test.field_0) RANGE 5m FILL NULL + sum(test.field_1) RANGE 5m FILL NULL) / Int64(4) [avg(test.field_0) RANGE 5m FILL NULL + sum(test.field_1) RANGE 5m FILL NULL / Int64(4):Float64;N]\
\n RangeSelect: range_exprs=[avg(test.field_0) RANGE 5m FILL NULL, sum(test.field_1) RANGE 5m FILL NULL], align=3600000ms, align_to=0ms, align_by=[test.tag_0, test.tag_1], time_index=timestamp [avg(test.field_0) RANGE 5m FILL NULL:Float64;N, sum(test.field_1) RANGE 5m FILL NULL:Float64;N, timestamp:Timestamp(Millisecond, None), tag_0:Utf8, tag_1:Utf8]\
\n TableScan: test [tag_0:Utf8, tag_1:Utf8, tag_2:Utf8, tag_3:Utf8, tag_4:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N, field_1:Float64;N, field_2:Float64;N, field_3:Float64;N, field_4:Float64;N]",
\n RangeSelect: range_exprs=[avg(test.field_0) RANGE 5m FILL NULL, sum(test.field_1) RANGE 5m FILL NULL], align=3600000ms, align_to=0ms, align_by=[test.tag_0, test.tag_1], time_index=timestamp [avg(test.field_0) RANGE 5m FILL NULL:Float64;N, sum(test.field_1) RANGE 5m FILL NULL:Float64;N, timestamp:Timestamp(ms), tag_0:Utf8, tag_1:Utf8]\
\n TableScan: test [tag_0:Utf8, tag_1:Utf8, tag_2:Utf8, tag_3:Utf8, tag_4:Utf8, timestamp:Timestamp(ms), field_0:Float64;N, field_1:Float64;N, field_2:Float64;N, field_3:Float64;N, field_4:Float64;N]",
);
query_plan_compare(query, expected).await;
}
@@ -749,8 +746,8 @@ mod test {
"Projection: foo + Int64(1) [foo + Int64(1):Float64;N]\
\n Filter: foo > Int64(1) [foo:Float64;N]\
\n Projection: (avg(test.field_0) RANGE 5m FILL NULL + sum(test.field_1) RANGE 5m FILL NULL) / Int64(4) AS foo [foo:Float64;N]\
\n RangeSelect: range_exprs=[avg(test.field_0) RANGE 5m FILL NULL, sum(test.field_1) RANGE 5m FILL NULL], align=3600000ms, align_to=0ms, align_by=[test.tag_0, test.tag_1], time_index=timestamp [avg(test.field_0) RANGE 5m FILL NULL:Float64;N, sum(test.field_1) RANGE 5m FILL NULL:Float64;N, timestamp:Timestamp(Millisecond, None), tag_0:Utf8, tag_1:Utf8]\
\n TableScan: test [tag_0:Utf8, tag_1:Utf8, tag_2:Utf8, tag_3:Utf8, tag_4:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N, field_1:Float64;N, field_2:Float64;N, field_3:Float64;N, field_4:Float64;N]",
\n RangeSelect: range_exprs=[avg(test.field_0) RANGE 5m FILL NULL, sum(test.field_1) RANGE 5m FILL NULL], align=3600000ms, align_to=0ms, align_by=[test.tag_0, test.tag_1], time_index=timestamp [avg(test.field_0) RANGE 5m FILL NULL:Float64;N, sum(test.field_1) RANGE 5m FILL NULL:Float64;N, timestamp:Timestamp(ms), tag_0:Utf8, tag_1:Utf8]\
\n TableScan: test [tag_0:Utf8, tag_1:Utf8, tag_2:Utf8, tag_3:Utf8, tag_4:Utf8, timestamp:Timestamp(ms), field_0:Float64;N, field_1:Float64;N, field_2:Float64;N, field_3:Float64;N, field_4:Float64;N]",
);
query_plan_compare(query, expected).await;
}
@@ -760,10 +757,10 @@ mod test {
let query = r#"SELECT ((avg(a)+sum(b))/4) RANGE '5m' FROM (SELECT field_0 as a, field_1 as b, tag_0 as c, tag_1 as d, timestamp from test where field_0 > 1.0) ALIGN '1h' by (c, d) FILL NULL;"#;
let expected = String::from(
"Projection: (avg(a) RANGE 5m FILL NULL + sum(b) RANGE 5m FILL NULL) / Int64(4) [avg(a) RANGE 5m FILL NULL + sum(b) RANGE 5m FILL NULL / Int64(4):Float64;N]\
\n RangeSelect: range_exprs=[avg(a) RANGE 5m FILL NULL, sum(b) RANGE 5m FILL NULL], align=3600000ms, align_to=0ms, align_by=[c, d], time_index=timestamp [avg(a) RANGE 5m FILL NULL:Float64;N, sum(b) RANGE 5m FILL NULL:Float64;N, timestamp:Timestamp(Millisecond, None), c:Utf8, d:Utf8]\
\n Projection: test.field_0 AS a, test.field_1 AS b, test.tag_0 AS c, test.tag_1 AS d, test.timestamp [a:Float64;N, b:Float64;N, c:Utf8, d:Utf8, timestamp:Timestamp(Millisecond, None)]\
\n Filter: test.field_0 > Float64(1) [tag_0:Utf8, tag_1:Utf8, tag_2:Utf8, tag_3:Utf8, tag_4:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N, field_1:Float64;N, field_2:Float64;N, field_3:Float64;N, field_4:Float64;N]\
\n TableScan: test [tag_0:Utf8, tag_1:Utf8, tag_2:Utf8, tag_3:Utf8, tag_4:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N, field_1:Float64;N, field_2:Float64;N, field_3:Float64;N, field_4:Float64;N]",
\n RangeSelect: range_exprs=[avg(a) RANGE 5m FILL NULL, sum(b) RANGE 5m FILL NULL], align=3600000ms, align_to=0ms, align_by=[c, d], time_index=timestamp [avg(a) RANGE 5m FILL NULL:Float64;N, sum(b) RANGE 5m FILL NULL:Float64;N, timestamp:Timestamp(ms), c:Utf8, d:Utf8]\
\n Projection: test.field_0 AS a, test.field_1 AS b, test.tag_0 AS c, test.tag_1 AS d, test.timestamp [a:Float64;N, b:Float64;N, c:Utf8, d:Utf8, timestamp:Timestamp(ms)]\
\n Filter: test.field_0 > Float64(1) [tag_0:Utf8, tag_1:Utf8, tag_2:Utf8, tag_3:Utf8, tag_4:Utf8, timestamp:Timestamp(ms), field_0:Float64;N, field_1:Float64;N, field_2:Float64;N, field_3:Float64;N, field_4:Float64;N]\
\n TableScan: test [tag_0:Utf8, tag_1:Utf8, tag_2:Utf8, tag_3:Utf8, tag_4:Utf8, timestamp:Timestamp(ms), field_0:Float64;N, field_1:Float64;N, field_2:Float64;N, field_3:Float64;N, field_4:Float64;N]",
);
query_plan_compare(query, expected).await;
}
@@ -773,8 +770,8 @@ mod test {
let query = r#"SELECT sin(avg(field_0 + field_1) RANGE '5m' + 1) FROM test ALIGN '1h' by (tag_0,tag_1);"#;
let expected = String::from(
"Projection: sin(avg(test.field_0 + test.field_1) RANGE 5m + Int64(1)) [sin(avg(test.field_0 + test.field_1) RANGE 5m + Int64(1)):Float64;N]\
\n RangeSelect: range_exprs=[avg(test.field_0 + test.field_1) RANGE 5m], align=3600000ms, align_to=0ms, align_by=[test.tag_0, test.tag_1], time_index=timestamp [avg(test.field_0 + test.field_1) RANGE 5m:Float64;N, timestamp:Timestamp(Millisecond, None), tag_0:Utf8, tag_1:Utf8]\
\n TableScan: test [tag_0:Utf8, tag_1:Utf8, tag_2:Utf8, tag_3:Utf8, tag_4:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N, field_1:Float64;N, field_2:Float64;N, field_3:Float64;N, field_4:Float64;N]",
\n RangeSelect: range_exprs=[avg(test.field_0 + test.field_1) RANGE 5m], align=3600000ms, align_to=0ms, align_by=[test.tag_0, test.tag_1], time_index=timestamp [avg(test.field_0 + test.field_1) RANGE 5m:Float64;N, timestamp:Timestamp(ms), tag_0:Utf8, tag_1:Utf8]\
\n TableScan: test [tag_0:Utf8, tag_1:Utf8, tag_2:Utf8, tag_3:Utf8, tag_4:Utf8, timestamp:Timestamp(ms), field_0:Float64;N, field_1:Float64;N, field_2:Float64;N, field_3:Float64;N, field_4:Float64;N]",
);
query_plan_compare(query, expected).await;
}
@@ -784,8 +781,8 @@ mod test {
let query = r#"SELECT avg(field_0) RANGE '5m' FILL 6.0 + avg(field_0) RANGE '5m' FILL 6.0 FROM test ALIGN '1h' by (tag_0,tag_1);"#;
let expected = String::from(
"Projection: avg(test.field_0) RANGE 5m FILL 6 + avg(test.field_0) RANGE 5m FILL 6 [avg(test.field_0) RANGE 5m FILL 6 + avg(test.field_0) RANGE 5m FILL 6:Float64]\
\n RangeSelect: range_exprs=[avg(test.field_0) RANGE 5m FILL 6], align=3600000ms, align_to=0ms, align_by=[test.tag_0, test.tag_1], time_index=timestamp [avg(test.field_0) RANGE 5m FILL 6:Float64, timestamp:Timestamp(Millisecond, None), tag_0:Utf8, tag_1:Utf8]\
\n TableScan: test [tag_0:Utf8, tag_1:Utf8, tag_2:Utf8, tag_3:Utf8, tag_4:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N, field_1:Float64;N, field_2:Float64;N, field_3:Float64;N, field_4:Float64;N]",
\n RangeSelect: range_exprs=[avg(test.field_0) RANGE 5m FILL 6], align=3600000ms, align_to=0ms, align_by=[test.tag_0, test.tag_1], time_index=timestamp [avg(test.field_0) RANGE 5m FILL 6:Float64, timestamp:Timestamp(ms), tag_0:Utf8, tag_1:Utf8]\
\n TableScan: test [tag_0:Utf8, tag_1:Utf8, tag_2:Utf8, tag_3:Utf8, tag_4:Utf8, timestamp:Timestamp(ms), field_0:Float64;N, field_1:Float64;N, field_2:Float64;N, field_3:Float64;N, field_4:Float64;N]",
);
query_plan_compare(query, expected).await;
}
@@ -795,8 +792,8 @@ mod test {
let query = r#"SELECT round(sin(avg(field_0 + field_1) RANGE '5m' + 1)) FROM test ALIGN '1h' by (tag_0,tag_1);"#;
let expected = String::from(
"Projection: round(sin(avg(test.field_0 + test.field_1) RANGE 5m + Int64(1))) [round(sin(avg(test.field_0 + test.field_1) RANGE 5m + Int64(1))):Float64;N]\
\n RangeSelect: range_exprs=[avg(test.field_0 + test.field_1) RANGE 5m], align=3600000ms, align_to=0ms, align_by=[test.tag_0, test.tag_1], time_index=timestamp [avg(test.field_0 + test.field_1) RANGE 5m:Float64;N, timestamp:Timestamp(Millisecond, None), tag_0:Utf8, tag_1:Utf8]\
\n TableScan: test [tag_0:Utf8, tag_1:Utf8, tag_2:Utf8, tag_3:Utf8, tag_4:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N, field_1:Float64;N, field_2:Float64;N, field_3:Float64;N, field_4:Float64;N]",
\n RangeSelect: range_exprs=[avg(test.field_0 + test.field_1) RANGE 5m], align=3600000ms, align_to=0ms, align_by=[test.tag_0, test.tag_1], time_index=timestamp [avg(test.field_0 + test.field_1) RANGE 5m:Float64;N, timestamp:Timestamp(ms), tag_0:Utf8, tag_1:Utf8]\
\n TableScan: test [tag_0:Utf8, tag_1:Utf8, tag_2:Utf8, tag_3:Utf8, tag_4:Utf8, timestamp:Timestamp(ms), field_0:Float64;N, field_1:Float64;N, field_2:Float64;N, field_3:Float64;N, field_4:Float64;N]",
);
query_plan_compare(query, expected).await;
}
@@ -806,8 +803,8 @@ mod test {
let query = r#"SELECT gcd(CAST(max(field_0 + 1) Range '5m' FILL NULL AS Int64), CAST(tag_0 AS Int64)) + round(max(field_2+1) Range '6m' FILL NULL + 1) + max(field_2+3) Range '10m' FILL NULL * CAST(tag_1 AS Float64) + 1 FROM test ALIGN '1h' by (tag_0, tag_1);"#;
let expected = String::from(
"Projection: gcd(arrow_cast(max(test.field_0 + Int64(1)) RANGE 5m FILL NULL, Utf8(\"Int64\")), arrow_cast(test.tag_0, Utf8(\"Int64\"))) + round(max(test.field_2 + Int64(1)) RANGE 6m FILL NULL + Int64(1)) + max(test.field_2 + Int64(3)) RANGE 10m FILL NULL * arrow_cast(test.tag_1, Utf8(\"Float64\")) + Int64(1) [gcd(arrow_cast(max(test.field_0 + Int64(1)) RANGE 5m FILL NULL,Utf8(\"Int64\")),arrow_cast(test.tag_0,Utf8(\"Int64\"))) + round(max(test.field_2 + Int64(1)) RANGE 6m FILL NULL + Int64(1)) + max(test.field_2 + Int64(3)) RANGE 10m FILL NULL * arrow_cast(test.tag_1,Utf8(\"Float64\")) + Int64(1):Float64;N]\
\n RangeSelect: range_exprs=[max(test.field_0 + Int64(1)) RANGE 5m FILL NULL, max(test.field_2 + Int64(1)) RANGE 6m FILL NULL, max(test.field_2 + Int64(3)) RANGE 10m FILL NULL], align=3600000ms, align_to=0ms, align_by=[test.tag_0, test.tag_1], time_index=timestamp [max(test.field_0 + Int64(1)) RANGE 5m FILL NULL:Float64;N, max(test.field_2 + Int64(1)) RANGE 6m FILL NULL:Float64;N, max(test.field_2 + Int64(3)) RANGE 10m FILL NULL:Float64;N, timestamp:Timestamp(Millisecond, None), tag_0:Utf8, tag_1:Utf8]\
\n TableScan: test [tag_0:Utf8, tag_1:Utf8, tag_2:Utf8, tag_3:Utf8, tag_4:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N, field_1:Float64;N, field_2:Float64;N, field_3:Float64;N, field_4:Float64;N]",
\n RangeSelect: range_exprs=[max(test.field_0 + Int64(1)) RANGE 5m FILL NULL, max(test.field_2 + Int64(1)) RANGE 6m FILL NULL, max(test.field_2 + Int64(3)) RANGE 10m FILL NULL], align=3600000ms, align_to=0ms, align_by=[test.tag_0, test.tag_1], time_index=timestamp [max(test.field_0 + Int64(1)) RANGE 5m FILL NULL:Float64;N, max(test.field_2 + Int64(1)) RANGE 6m FILL NULL:Float64;N, max(test.field_2 + Int64(3)) RANGE 10m FILL NULL:Float64;N, timestamp:Timestamp(ms), tag_0:Utf8, tag_1:Utf8]\
\n TableScan: test [tag_0:Utf8, tag_1:Utf8, tag_2:Utf8, tag_3:Utf8, tag_4:Utf8, timestamp:Timestamp(ms), field_0:Float64;N, field_1:Float64;N, field_2:Float64;N, field_3:Float64;N, field_4:Float64;N]",
);
query_plan_compare(query, expected).await;
}
@@ -817,7 +814,7 @@ mod test {
let query = r#"SELECT min(CAST(field_0 AS Int64) + CAST(field_1 AS Int64)) RANGE '5m' FILL LINEAR FROM test ALIGN '1h' by (tag_0,tag_1);"#;
let expected = String::from(
"RangeSelect: range_exprs=[min(arrow_cast(test.field_0,Utf8(\"Int64\")) + arrow_cast(test.field_1,Utf8(\"Int64\"))) RANGE 5m FILL LINEAR], align=3600000ms, align_to=0ms, align_by=[test.tag_0, test.tag_1], time_index=timestamp [min(arrow_cast(test.field_0,Utf8(\"Int64\")) + arrow_cast(test.field_1,Utf8(\"Int64\"))) RANGE 5m FILL LINEAR:Float64;N]\
\n TableScan: test [tag_0:Utf8, tag_1:Utf8, tag_2:Utf8, tag_3:Utf8, tag_4:Utf8, timestamp:Timestamp(Millisecond, None), field_0:Float64;N, field_1:Float64;N, field_2:Float64;N, field_3:Float64;N, field_4:Float64;N]",
\n TableScan: test [tag_0:Utf8, tag_1:Utf8, tag_2:Utf8, tag_3:Utf8, tag_4:Utf8, timestamp:Timestamp(ms), field_0:Float64;N, field_1:Float64;N, field_2:Float64;N, field_3:Float64;N, field_4:Float64;N]",
);
query_plan_compare(query, expected).await;
}

8
src/query/src/test_util.rs
View File

@@ -49,19 +49,19 @@ pub fn new_ts_array(unit: TimeUnit, arr: Vec<i64>) -> ArrayRef {
pub struct MockInputExec {
input: Vec<Vec<DfRecordBatch>>,
schema: SchemaRef,
properties: PlanProperties,
properties: Arc<PlanProperties>,
metrics: ExecutionPlanMetricsSet,
}
impl MockInputExec {
pub fn new(input: Vec<Vec<DfRecordBatch>>, schema: SchemaRef) -> Self {
Self {
properties: PlanProperties::new(
properties: Arc::new(PlanProperties::new(
EquivalenceProperties::new(schema.clone()),
Partitioning::UnknownPartitioning(1),
EmissionType::Incremental,
Boundedness::Bounded,
),
)),
input,
schema,
metrics: ExecutionPlanMetricsSet::new(),
@@ -84,7 +84,7 @@ impl ExecutionPlan for MockInputExec {
self
}
fn properties(&self) -> &PlanProperties {
fn properties(&self) -> &Arc<PlanProperties> {
&self.properties
}

8
src/query/src/window_sort.rs
View File

@@ -81,7 +81,7 @@ pub struct WindowedSortExec {
input: Arc<dyn ExecutionPlan>,
/// Execution metrics
metrics: ExecutionPlanMetricsSet,
properties: PlanProperties,
properties: Arc<PlanProperties>,
}
/// Checks that partition ranges are sorted correctly for the given sort direction.
@@ -130,12 +130,12 @@ impl WindowedSortExec {
eq_properties.reorder(vec![expression.clone()])?;
let properties = input.properties();
let properties = PlanProperties::new(
let properties = Arc::new(PlanProperties::new(
eq_properties,
input.output_partitioning().clone(),
properties.emission_type,
properties.boundedness,
);
));
let mut all_avail_working_range = Vec::with_capacity(ranges.len());
for r in &ranges {
@@ -202,7 +202,7 @@ impl ExecutionPlan for WindowedSortExec {
self.input.schema()
}
fn properties(&self) -> &PlanProperties {
fn properties(&self) -> &Arc<PlanProperties> {
&self.properties
}

27
src/sql/src/parsers/create_parser.rs
View File

@@ -25,7 +25,10 @@ use datatypes::arrow::datatypes::{DataType as ArrowDataType, IntervalUnit};
use datatypes::data_type::ConcreteDataType;
use itertools::Itertools;
use snafu::{OptionExt, ResultExt, ensure};
use sqlparser::ast::{ColumnOption, ColumnOptionDef, DataType, Expr};
use sqlparser::ast::{
ColumnOption, ColumnOptionDef, DataType, Expr, KeyOrIndexDisplay, NullsDistinctOption,
PrimaryKeyConstraint, UniqueConstraint,
};
use sqlparser::dialect::keywords::Keyword;
use sqlparser::keywords::ALL_KEYWORDS;
use sqlparser::parser::IsOptional::Mandatory;
@@ -717,15 +720,25 @@ impl<'a> ParserContext<'a> {
parser.parse_expr().context(SyntaxSnafu)?,
)))
} else if parser.parse_keywords(&[Keyword::PRIMARY, Keyword::KEY]) {
Ok(Some(ColumnOption::Unique {
is_primary: true,
Ok(Some(ColumnOption::PrimaryKey(PrimaryKeyConstraint {
name: None,
index_name: None,
index_type: None,
columns: vec![],
index_options: vec![],
characteristics: None,
}))
})))
} else if parser.parse_keyword(Keyword::UNIQUE) {
Ok(Some(ColumnOption::Unique {
is_primary: false,
Ok(Some(ColumnOption::Unique(UniqueConstraint {
name: None,
index_name: None,
index_type_display: KeyOrIndexDisplay::None,
index_type: None,
columns: vec![],
index_options: vec![],
characteristics: None,
}))
nulls_distinct: NullsDistinctOption::None,
})))
} else if parser.parse_keywords(&[Keyword::TIME, Keyword::INDEX]) {
// Use a DialectSpecific option for time index
Ok(Some(ColumnOption::DialectSpecific(vec![

7
src/sql/src/parsers/delete_parser.rs
View File

@@ -23,8 +23,11 @@ use crate::statements::statement::Statement;
/// DELETE statement parser implementation
impl ParserContext<'_> {
pub(crate) fn parse_delete(&mut self) -> Result<Statement> {
let _ = self.parser.next_token();
let spstatement = self.parser.parse_delete().context(error::SyntaxSnafu)?;
let token = self.parser.next_token();
let spstatement = self
.parser
.parse_delete(token)
.context(error::SyntaxSnafu)?;
match spstatement {
SpStatement::Delete { .. } => {

4
src/sql/src/parsers/explain_parser.rs
View File

@@ -69,6 +69,7 @@ mod tests {
let select = sqlparser::ast::Select {
distinct: None,
select_modifiers: None,
top: None,
projection: vec![sqlparser::ast::SelectItem::Wildcard(
WildcardAdditionalOptions::default(),
@@ -103,9 +104,10 @@ mod tests {
top_before_distinct: false,
prewhere: None,
window_before_qualify: false,
connect_by: None,
connect_by: vec![],
select_token: AttachedToken::empty(),
flavor: SelectFlavor::Standard,
optimizer_hint: None,
};
let sp_query = Box::new(

14
src/sql/src/parsers/insert_parser.rs
View File

@@ -23,8 +23,11 @@ use crate::statements::statement::Statement;
/// INSERT/REPLACE statement parser implementation
impl ParserContext<'_> {
pub(crate) fn parse_insert(&mut self) -> Result<Statement> {
let _ = self.parser.next_token();
let spstatement = self.parser.parse_insert().context(error::SyntaxSnafu)?;
let token = self.parser.next_token();
let spstatement = self
.parser
.parse_insert(token)
.context(error::SyntaxSnafu)?;
match spstatement {
SpStatement::Insert { .. } => {
@@ -38,8 +41,11 @@ impl ParserContext<'_> {
}
pub(crate) fn parse_replace(&mut self) -> Result<Statement> {
let _ = self.parser.next_token();
let spstatement = self.parser.parse_insert().context(error::SyntaxSnafu)?;
let token = self.parser.next_token();
let spstatement = self
.parser
.parse_insert(token)
.context(error::SyntaxSnafu)?;
match spstatement {
SpStatement::Insert(mut insert_stmt) => {

13
src/sql/src/parsers/utils.rs
View File

@@ -15,7 +15,6 @@
use std::collections::HashMap;
use std::sync::Arc;
use chrono::Utc;
use datafusion::config::ConfigOptions;
use datafusion::error::Result as DfResult;
use datafusion::execution::SessionStateBuilder;
@@ -23,7 +22,6 @@ use datafusion::execution::context::SessionState;
use datafusion::optimizer::simplify_expressions::ExprSimplifier;
use datafusion_common::tree_node::{TreeNode, TreeNodeVisitor};
use datafusion_common::{DFSchema, ScalarValue};
use datafusion_expr::execution_props::ExecutionProps;
use datafusion_expr::simplify::SimplifyContext;
use datafusion_expr::{AggregateUDF, Expr, ScalarUDF, TableSource, WindowUDF};
use datafusion_sql::TableReference;
@@ -130,10 +128,7 @@ pub fn parser_expr_to_scalar_value_literal(
}
// 2. simplify logical expr
let execution_props = ExecutionProps::new().with_query_execution_start_time(Utc::now());
let info =
SimplifyContext::new(&execution_props).with_schema(Arc::new(empty_df_schema.clone()));
let info = SimplifyContext::default().with_current_time();
let simplifier = ExprSimplifier::new(info);
// Coerce the logical expression so simplifier can handle it correctly. This is necessary for const eval with possible type mismatch. i.e.: `now() - now() + '15s'::interval` which is `TimestampNanosecond - TimestampNanosecond + IntervalMonthDayNano`.
@@ -293,8 +288,6 @@ pub fn parse_with_options(parser: &mut Parser) -> Result<OptionMap> {
#[cfg(test)]
mod tests {
use std::sync::Arc;
use chrono::DateTime;
use datafusion::functions::datetime::expr_fn::now;
use datafusion_expr::lit;
@@ -343,9 +336,7 @@ mod tests {
),
];
let execution_props = ExecutionProps::new().with_query_execution_start_time(now_time);
let info = SimplifyContext::new(&execution_props).with_schema(Arc::new(DFSchema::empty()));
let info = SimplifyContext::default().with_query_execution_start_time(Some(now_time));
let simplifier = ExprSimplifier::new(info);
for (expr, expected) in testcases {
let expr_name = expr.schema_name().to_string();

1
src/sql/src/parsers/with_tql_parser.rs
View File

@@ -114,6 +114,7 @@ impl ParserContext<'_> {
match cte.content {
CteContent::Sql(body) => sql_cte_tables.push(Cte {
alias: TableAlias {
explicit: false,
name: cte.name,
columns: cte
.columns

40
src/sql/src/statements.rs
View File

@@ -91,10 +91,7 @@ pub fn has_primary_key_option(column_def: &ColumnDef) -> bool {
column_def
.options
.iter()
.any(|options| match options.option {
ColumnOption::Unique { is_primary, .. } => is_primary,
_ => false,
})
.any(|options| matches!(options.option, ColumnOption::PrimaryKey(..)))
}
/// Create a `ColumnSchema` from `Column`.
@@ -198,15 +195,10 @@ pub fn sql_column_def_to_grpc_column_def(
.context(ConvertToGrpcDataTypeSnafu)?
.to_parts();
let is_primary_key = col.options.iter().any(|o| {
matches!(
o.option,
ColumnOption::Unique {
is_primary: true,
..
}
)
});
let is_primary_key = col
.options
.iter()
.any(|o| matches!(o.option, ColumnOption::PrimaryKey(..)));
let semantic_type = if is_primary_key {
SemanticType::Tag
@@ -375,7 +367,7 @@ mod tests {
use datatypes::schema::{
COLUMN_FULLTEXT_OPT_KEY_ANALYZER, COLUMN_FULLTEXT_OPT_KEY_CASE_SENSITIVE, FulltextAnalyzer,
};
use sqlparser::ast::{ColumnOptionDef, Expr};
use sqlparser::ast::{ColumnOptionDef, Expr, PrimaryKeyConstraint};
use super::*;
use crate::ast::TimezoneInfo;
@@ -505,10 +497,14 @@ mod tests {
data_type: SqlDataType::Double(ExactNumberInfo::None),
options: vec![ColumnOptionDef {
name: None,
option: ColumnOption::Unique {
is_primary: true,
option: ColumnOption::PrimaryKey(PrimaryKeyConstraint {
name: None,
index_name: None,
index_type: None,
columns: vec![],
index_options: vec![],
characteristics: None,
},
}),
}],
};
@@ -583,10 +579,14 @@ mod tests {
data_type: SqlDataType::Double(ExactNumberInfo::None),
options: vec![ColumnOptionDef {
name: None,
option: ColumnOption::Unique {
is_primary: true,
option: ColumnOption::PrimaryKey(PrimaryKeyConstraint {
name: None,
index_name: None,
index_type: None,
columns: vec![],
index_options: vec![],
characteristics: None,
},
}),
}],
};
assert!(has_primary_key_option(&column_def));

6
src/sql/src/statements/transform/expand_interval.rs
View File

@@ -111,6 +111,7 @@ impl TransformRule for ExpandIntervalTransformRule {
Expr::Cast {
expr: cast_exp,
data_type,
array,
kind,
format,
} => {
@@ -130,6 +131,7 @@ impl TransformRule for ExpandIntervalTransformRule {
kind: kind.clone(),
expr: single_quoted_string_expr(interval_value),
data_type: data_type.clone(),
array: *array,
format: std::mem::take(format),
}
}
@@ -396,6 +398,7 @@ mod tests {
fields: None,
precision: None,
},
array: false,
format: None,
kind: sqlparser::ast::CastKind::Cast,
};
@@ -414,6 +417,7 @@ mod tests {
fields: None,
precision: None,
},
array: false,
format: None,
}
);
@@ -421,6 +425,7 @@ mod tests {
let mut cast_to_i64_expr = Expr::Cast {
expr: single_quoted_string_expr("5".to_string()),
data_type: DataType::Int64,
array: false,
format: None,
kind: sqlparser::ast::CastKind::Cast,
};
@@ -431,6 +436,7 @@ mod tests {
Expr::Cast {
expr: single_quoted_string_expr("5".to_string()),
data_type: DataType::Int64,
array: false,
format: None,
kind: sqlparser::ast::CastKind::Cast,
}

12
src/table/src/table/scan.rs
View File

@@ -59,7 +59,7 @@ pub struct RegionScanExec {
/// The expected output ordering for the plan.
output_ordering: Option<Vec<PhysicalSortExpr>>,
metric: ExecutionPlanMetricsSet,
properties: PlanProperties,
properties: Arc<PlanProperties>,
append_mode: bool,
total_rows: usize,
is_partition_set: bool,
@@ -206,12 +206,12 @@ impl RegionScanExec {
}
};
let properties = PlanProperties::new(
let properties = Arc::new(PlanProperties::new(
eq_props,
partitioning,
EmissionType::Incremental,
Boundedness::Bounded,
);
));
let append_mode = scanner_props.append_mode();
let total_rows = scanner_props.total_rows();
Ok(Self {
@@ -269,7 +269,7 @@ impl RegionScanExec {
warn!("Setting partition ranges more than once for RegionScanExec");
}
let mut properties = self.properties.clone();
let mut properties = self.properties.as_ref().clone();
let new_partitioning = match properties.partitioning {
Partitioning::Hash(ref columns, _) => {
Partitioning::Hash(columns.clone(), target_partitions)
@@ -292,7 +292,7 @@ impl RegionScanExec {
arrow_schema: self.arrow_schema.clone(),
output_ordering: self.output_ordering.clone(),
metric: self.metric.clone(),
properties,
properties: Arc::new(properties),
append_mode: self.append_mode,
total_rows: self.total_rows,
is_partition_set: true,
@@ -349,7 +349,7 @@ impl ExecutionPlan for RegionScanExec {
self.arrow_schema.clone()
}
fn properties(&self) -> &PlanProperties {
fn properties(&self) -> &Arc<PlanProperties> {
&self.properties
}

1
tests/cases/distributed/explain/analyze.result
View File

@@ -45,7 +45,6 @@ explain analyze SELECT count(*) FROM system_metrics;
|_|_|_AggregateExec: mode=Final, gby=[], aggr=[count(system_REDACTED
|_|_|_CoalescePartitionsExec REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[], aggr=[count(system_REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":{"count":1, "mem_ranges":1, "files":0, "file_ranges":0} REDACTED
|_|_|_|
|_|_| Total rows: 1_|

31
tests/cases/distributed/explain/join_10_tables.result
View File

@@ -117,67 +117,36 @@ limit 1;
|_| ]]_|
| physical_plan | SortPreservingMergeExec: [ts@0 DESC], fetch=1_|
|_|_SortExec: TopK(fetch=1), expr=[ts@0 DESC], preserve_partitioning=[true]_|
|_|_CoalesceBatchesExec: target_batch_size=8192_|
|_|_REDACTED
|_|_CoalesceBatchesExec: target_batch_size=8192_|
|_|_REDACTED
|_|_CoalesceBatchesExec: target_batch_size=8192_|
|_|_REDACTED
|_|_CoalesceBatchesExec: target_batch_size=8192_|
|_|_REDACTED
|_|_CoalesceBatchesExec: target_batch_size=8192_|
|_|_REDACTED
|_|_CoalesceBatchesExec: target_batch_size=8192_|
|_|_REDACTED
|_|_CoalesceBatchesExec: target_batch_size=8192_|
|_|_REDACTED
|_|_CoalesceBatchesExec: target_batch_size=8192_|
|_|_REDACTED
|_|_CoalesceBatchesExec: target_batch_size=8192_|
|_|_REDACTED
|_|_CoalesceBatchesExec: target_batch_size=8192_|
|_|_RepartitionExec: partitioning=REDACTED
|_|_CoalesceBatchesExec: target_batch_size=8192_|
|_|_FilterExec: vin@1 IS NOT NULL_|
|_|_CooperativeExec_|
|_|_MergeScanExec: REDACTED
|_|_CoalesceBatchesExec: target_batch_size=8192_|
|_|_RepartitionExec: partitioning=REDACTED
|_|_CoalesceBatchesExec: target_batch_size=8192_|
|_|_FilterExec: vin@1 IS NOT NULL_|
|_|_CooperativeExec_|
|_|_MergeScanExec: REDACTED
|_|_CoalesceBatchesExec: target_batch_size=8192_|
|_|_RepartitionExec: partitioning=REDACTED
|_|_CooperativeExec_|
|_|_MergeScanExec: REDACTED
|_|_CoalesceBatchesExec: target_batch_size=8192_|
|_|_RepartitionExec: partitioning=REDACTED
|_|_CooperativeExec_|
|_|_MergeScanExec: REDACTED
|_|_CoalesceBatchesExec: target_batch_size=8192_|
|_|_RepartitionExec: partitioning=REDACTED
|_|_CooperativeExec_|
|_|_MergeScanExec: REDACTED
|_|_CoalesceBatchesExec: target_batch_size=8192_|
|_|_RepartitionExec: partitioning=REDACTED
|_|_CooperativeExec_|
|_|_MergeScanExec: REDACTED
|_|_CoalesceBatchesExec: target_batch_size=8192_|
|_|_RepartitionExec: partitioning=REDACTED
|_|_CooperativeExec_|
|_|_MergeScanExec: REDACTED
|_|_CoalesceBatchesExec: target_batch_size=8192_|
|_|_RepartitionExec: partitioning=REDACTED
|_|_CooperativeExec_|
|_|_MergeScanExec: REDACTED
|_|_CoalesceBatchesExec: target_batch_size=8192_|
|_|_RepartitionExec: partitioning=REDACTED
|_|_CooperativeExec_|
|_|_MergeScanExec: REDACTED
|_|_CoalesceBatchesExec: target_batch_size=8192_|
|_|_RepartitionExec: partitioning=REDACTED
|_|_CooperativeExec_|
|_|_MergeScanExec: REDACTED
|_|_|
+-+-+

2
tests/cases/distributed/explain/multi_partitions.result
View File

@@ -31,8 +31,6 @@ explain SELECT * FROM multi_partitions_test_table WHERE ts > cast(1000000000 as
|_|_TableScan: multi_partitions_test_table_|
|_| ]]_|
| physical_plan | SortPreservingMergeExec: [host@0 ASC NULLS LAST]_|
|_|_CooperativeExec_|
|_|_CooperativeExec_|
|_|_MergeScanExec: REDACTED
|_|_|
+-+-+

2
tests/cases/distributed/explain/order_by.result
View File

@@ -129,7 +129,6 @@ EXPLAIN ANALYZE SELECT i, t AS alias_ts FROM test_pk ORDER BY t DESC LIMIT 5;
|_|_|_WindowedSortExec: expr=t@1 DESC num_ranges=REDACTED fetch=5 REDACTED
|_|_|_PartSortExec: expr=t@1 DESC num_ranges=REDACTED limit=5 REDACTED
|_|_|_ProjectionExec: expr=[i@0 as i, t@1 as t, t@1 as test_pk.t__temp__0] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":{"count":1, "mem_ranges":1, "files":0, "file_ranges":0} REDACTED
|_|_|_|
|_|_| Total rows: 5_|
@@ -153,7 +152,6 @@ EXPLAIN ANALYZE SELECT i, t AS alias_ts FROM test_pk ORDER BY alias_ts DESC LIMI
|_|_|_SortPreservingMergeExec: [t@1 DESC], fetch=5 REDACTED
|_|_|_WindowedSortExec: expr=t@1 DESC num_ranges=REDACTED fetch=5 REDACTED
|_|_|_PartSortExec: expr=t@1 DESC num_ranges=REDACTED limit=5 REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":{"count":1, "mem_ranges":1, "files":0, "file_ranges":0} REDACTED
|_|_|_|
|_|_| Total rows: 5_|

30
tests/cases/distributed/explain/step_aggr.result
View File

@@ -67,7 +67,6 @@ FROM
|_|_AggregateExec: mode=Final, gby=[], aggr=[count(integers.i), sum(integers.i), uddsketch_state(Int64(128),Float64(0.01),integers.i), hll(integers.i)]_|
|_|_CoalescePartitionsExec_|
|_|_AggregateExec: mode=Partial, gby=[], aggr=[count(integers.i), sum(integers.i), uddsketch_state(Int64(128),Float64(0.01),integers.i), hll(integers.i)]_|
|_|_CooperativeExec_|
|_|_MergeScanExec: REDACTED
|_|_|
+-+-+
@@ -97,25 +96,21 @@ FROM
|_|_|_AggregateExec: mode=Final, gby=[], aggr=[count(integers.i), sum(integers.i), uddsketch_state(Int64(128),Float64(0.01),integers.i), hll(integers.i)] REDACTED
|_|_|_CoalescePartitionsExec REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[], aggr=[count(integers.i), sum(integers.i), uddsketch_state(Int64(128),Float64(0.01),integers.i), hll(integers.i)] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_MergeScanExec: REDACTED
|_|_|_|
| 1_| 0_|_AggregateExec: mode=Final, gby=[], aggr=[__count_state(integers.i), __sum_state(integers.i), __uddsketch_state_state(Int64(128),Float64(0.01),integers.i), __hll_state(integers.i)] REDACTED
|_|_|_CoalescePartitionsExec REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[], aggr=[__count_state(integers.i), __sum_state(integers.i), __uddsketch_state_state(Int64(128),Float64(0.01),integers.i), __hll_state(integers.i)] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
| 1_| 1_|_AggregateExec: mode=Final, gby=[], aggr=[__count_state(integers.i), __sum_state(integers.i), __uddsketch_state_state(Int64(128),Float64(0.01),integers.i), __hll_state(integers.i)] REDACTED
|_|_|_CoalescePartitionsExec REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[], aggr=[__count_state(integers.i), __sum_state(integers.i), __uddsketch_state_state(Int64(128),Float64(0.01),integers.i), __hll_state(integers.i)] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
| 1_| 2_|_AggregateExec: mode=Final, gby=[], aggr=[__count_state(integers.i), __sum_state(integers.i), __uddsketch_state_state(Int64(128),Float64(0.01),integers.i), __hll_state(integers.i)] REDACTED
|_|_|_CoalescePartitionsExec REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[], aggr=[__count_state(integers.i), __sum_state(integers.i), __uddsketch_state_state(Int64(128),Float64(0.01),integers.i), __hll_state(integers.i)] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
|_|_| Total rows: 1_|
@@ -153,7 +148,6 @@ FROM
| physical_plan | AggregateExec: mode=Final, gby=[], aggr=[avg(integers.i)]_|
|_|_CoalescePartitionsExec_|
|_|_AggregateExec: mode=Partial, gby=[], aggr=[avg(integers.i)]_|
|_|_CooperativeExec_|
|_|_MergeScanExec: REDACTED
|_|_|
+-+-+
@@ -178,25 +172,21 @@ FROM
| 0_| 0_|_AggregateExec: mode=Final, gby=[], aggr=[avg(integers.i)] REDACTED
|_|_|_CoalescePartitionsExec REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[], aggr=[avg(integers.i)] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_MergeScanExec: REDACTED
|_|_|_|
| 1_| 0_|_AggregateExec: mode=Final, gby=[], aggr=[__avg_state(integers.i)] REDACTED
|_|_|_CoalescePartitionsExec REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[], aggr=[__avg_state(integers.i)] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
| 1_| 1_|_AggregateExec: mode=Final, gby=[], aggr=[__avg_state(integers.i)] REDACTED
|_|_|_CoalescePartitionsExec REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[], aggr=[__avg_state(integers.i)] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
| 1_| 2_|_AggregateExec: mode=Final, gby=[], aggr=[__avg_state(integers.i)] REDACTED
|_|_|_CoalescePartitionsExec REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[], aggr=[__avg_state(integers.i)] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
|_|_| Total rows: 1_|
@@ -257,10 +247,8 @@ ORDER BY
|_|_SortExec: expr=[ts@0 ASC NULLS LAST], preserve_partitioning=[true]_|
|_|_ProjectionExec: expr=[ts@0 as ts, count(integers.i)@1 as count(integers.i), sum(integers.i)@2 as sum(integers.i), uddsketch_calc(0.5, uddsketch_state(Int64(128),Float64(0.01),integers.i)@3) as uddsketch_calc(Float64(0.5),uddsketch_state(Int64(128),Float64(0.01),integers.i)), hll_count(hll(integers.i)@4) as hll_count(hll(integers.i))]_|
|_|_AggregateExec: mode=FinalPartitioned, gby=[ts@0 as ts], aggr=[count(integers.i), sum(integers.i), uddsketch_state(Int64(128),Float64(0.01),integers.i), hll(integers.i)]_|
|_|_CoalesceBatchesExec: target_batch_size=8192_|
|_|_RepartitionExec: partitioning=REDACTED
|_|_AggregateExec: mode=Partial, gby=[ts@0 as ts], aggr=[count(integers.i), sum(integers.i), uddsketch_state(Int64(128),Float64(0.01),integers.i), hll(integers.i)]_|
|_|_CooperativeExec_|
|_|_MergeScanExec: REDACTED
|_|_|
+-+-+
@@ -295,31 +283,23 @@ ORDER BY
|_|_|_SortExec: expr=[ts@0 ASC NULLS LAST], preserve_partitioning=[true] REDACTED
|_|_|_ProjectionExec: expr=[ts@0 as ts, count(integers.i)@1 as count(integers.i), sum(integers.i)@2 as sum(integers.i), uddsketch_calc(0.5, uddsketch_state(Int64(128),Float64(0.01),integers.i)@3) as uddsketch_calc(Float64(0.5),uddsketch_state(Int64(128),Float64(0.01),integers.i)), hll_count(hll(integers.i)@4) as hll_count(hll(integers.i))] REDACTED
|_|_|_AggregateExec: mode=FinalPartitioned, gby=[ts@0 as ts], aggr=[count(integers.i), sum(integers.i), uddsketch_state(Int64(128),Float64(0.01),integers.i), hll(integers.i)] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: partitioning=REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[ts@0 as ts], aggr=[count(integers.i), sum(integers.i), uddsketch_state(Int64(128),Float64(0.01),integers.i), hll(integers.i)] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_MergeScanExec: REDACTED
|_|_|_|
| 1_| 0_|_AggregateExec: mode=FinalPartitioned, gby=[ts@0 as ts], aggr=[__count_state(integers.i), __sum_state(integers.i), __uddsketch_state_state(Int64(128),Float64(0.01),integers.i), __hll_state(integers.i)] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: partitioning=REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[ts@1 as ts], aggr=[__count_state(integers.i), __sum_state(integers.i), __uddsketch_state_state(Int64(128),Float64(0.01),integers.i), __hll_state(integers.i)] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
| 1_| 1_|_AggregateExec: mode=FinalPartitioned, gby=[ts@0 as ts], aggr=[__count_state(integers.i), __sum_state(integers.i), __uddsketch_state_state(Int64(128),Float64(0.01),integers.i), __hll_state(integers.i)] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: partitioning=REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[ts@1 as ts], aggr=[__count_state(integers.i), __sum_state(integers.i), __uddsketch_state_state(Int64(128),Float64(0.01),integers.i), __hll_state(integers.i)] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
| 1_| 2_|_AggregateExec: mode=FinalPartitioned, gby=[ts@0 as ts], aggr=[__count_state(integers.i), __sum_state(integers.i), __uddsketch_state_state(Int64(128),Float64(0.01),integers.i), __hll_state(integers.i)] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: partitioning=REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[ts@1 as ts], aggr=[__count_state(integers.i), __sum_state(integers.i), __uddsketch_state_state(Int64(128),Float64(0.01),integers.i), __hll_state(integers.i)] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
|_|_| Total rows: 4_|
@@ -380,10 +360,8 @@ ORDER BY
|_|_SortExec: expr=[time_window@0 ASC NULLS LAST], preserve_partitioning=[true]_|
|_|_ProjectionExec: expr=[date_bin(Utf8("2 seconds"),integers.ts)@0 as time_window, count(integers.i)@1 as count(integers.i), sum(integers.i)@2 as sum(integers.i), uddsketch_calc(0.5, uddsketch_state(Int64(128),Float64(0.01),integers.i)@3) as uddsketch_calc(Float64(0.5),uddsketch_state(Int64(128),Float64(0.01),integers.i)), hll_count(hll(integers.i)@4) as hll_count(hll(integers.i))]_|
|_|_AggregateExec: mode=FinalPartitioned, gby=[date_bin(Utf8("2 seconds"),integers.ts)@0 as date_bin(Utf8("2 seconds"),integers.ts)], aggr=[count(integers.i), sum(integers.i), uddsketch_state(Int64(128),Float64(0.01),integers.i), hll(integers.i)]_|
|_|_CoalesceBatchesExec: target_batch_size=8192_|
|_|_RepartitionExec: partitioning=REDACTED
|_|_AggregateExec: mode=Partial, gby=[date_bin(Utf8("2 seconds"),integers.ts)@0 as date_bin(Utf8("2 seconds"),integers.ts)], aggr=[count(integers.i), sum(integers.i), uddsketch_state(Int64(128),Float64(0.01),integers.i), hll(integers.i)]_|
|_|_CooperativeExec_|
|_|_MergeScanExec: REDACTED
|_|_|
+-+-+
@@ -418,31 +396,23 @@ ORDER BY
|_|_|_SortExec: expr=[time_window@0 ASC NULLS LAST], preserve_partitioning=[true] REDACTED
|_|_|_ProjectionExec: expr=[date_bin(Utf8("2 seconds"),integers.ts)@0 as time_window, count(integers.i)@1 as count(integers.i), sum(integers.i)@2 as sum(integers.i), uddsketch_calc(0.5, uddsketch_state(Int64(128),Float64(0.01),integers.i)@3) as uddsketch_calc(Float64(0.5),uddsketch_state(Int64(128),Float64(0.01),integers.i)), hll_count(hll(integers.i)@4) as hll_count(hll(integers.i))] REDACTED
|_|_|_AggregateExec: mode=FinalPartitioned, gby=[date_bin(Utf8("2 seconds"),integers.ts)@0 as date_bin(Utf8("2 seconds"),integers.ts)], aggr=[count(integers.i), sum(integers.i), uddsketch_state(Int64(128),Float64(0.01),integers.i), hll(integers.i)] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: partitioning=REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[date_bin(Utf8("2 seconds"),integers.ts)@0 as date_bin(Utf8("2 seconds"),integers.ts)], aggr=[count(integers.i), sum(integers.i), uddsketch_state(Int64(128),Float64(0.01),integers.i), hll(integers.i)] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_MergeScanExec: REDACTED
|_|_|_|
| 1_| 0_|_AggregateExec: mode=FinalPartitioned, gby=[date_bin(Utf8("2 seconds"),integers.ts)@0 as date_bin(Utf8("2 seconds"),integers.ts)], aggr=[__count_state(integers.i), __sum_state(integers.i), __uddsketch_state_state(Int64(128),Float64(0.01),integers.i), __hll_state(integers.i)] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: partitioning=REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[date_bin(IntervalMonthDayNano { months: 0, days: 0, nanoseconds: 2000000000 }, ts@1) as date_bin(Utf8("2 seconds"),integers.ts)], aggr=[__count_state(integers.i), __sum_state(integers.i), __uddsketch_state_state(Int64(128),Float64(0.01),integers.i), __hll_state(integers.i)] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
| 1_| 1_|_AggregateExec: mode=FinalPartitioned, gby=[date_bin(Utf8("2 seconds"),integers.ts)@0 as date_bin(Utf8("2 seconds"),integers.ts)], aggr=[__count_state(integers.i), __sum_state(integers.i), __uddsketch_state_state(Int64(128),Float64(0.01),integers.i), __hll_state(integers.i)] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: partitioning=REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[date_bin(IntervalMonthDayNano { months: 0, days: 0, nanoseconds: 2000000000 }, ts@1) as date_bin(Utf8("2 seconds"),integers.ts)], aggr=[__count_state(integers.i), __sum_state(integers.i), __uddsketch_state_state(Int64(128),Float64(0.01),integers.i), __hll_state(integers.i)] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
| 1_| 2_|_AggregateExec: mode=FinalPartitioned, gby=[date_bin(Utf8("2 seconds"),integers.ts)@0 as date_bin(Utf8("2 seconds"),integers.ts)], aggr=[__count_state(integers.i), __sum_state(integers.i), __uddsketch_state_state(Int64(128),Float64(0.01),integers.i), __hll_state(integers.i)] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: partitioning=REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[date_bin(IntervalMonthDayNano { months: 0, days: 0, nanoseconds: 2000000000 }, ts@1) as date_bin(Utf8("2 seconds"),integers.ts)], aggr=[__count_state(integers.i), __sum_state(integers.i), __uddsketch_state_state(Int64(128),Float64(0.01),integers.i), __hll_state(integers.i)] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
|_|_| Total rows: 4_|

186
tests/cases/distributed/explain/step_aggr_advance.result
View File

@@ -38,9 +38,7 @@ tql explain (1752591864, 1752592164, '30s') max by (a, b, c) (max_over_time(aggr
| | TableScan: aggr_optimize_not |
| | ]] |
| physical_plan | SortPreservingMergeExec: [a@0 ASC NULLS LAST, b@1 ASC NULLS LAST, c@2 ASC NULLS LAST, greptime_timestamp@3 ASC NULLS LAST] |
| | CooperativeExec |
| | CooperativeExec |
| | MergeScanExec: REDACTED
| | MergeScanExec: REDACTED
| | |
+---------------+-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
@@ -57,38 +55,30 @@ tql analyze (1752591864, 1752592164, '30s') max by (a, b, c) (max_over_time(aggr
| stage | node | plan_|
+-+-+-+
| 0_| 0_|_SortPreservingMergeExec: [a@0 ASC NULLS LAST, b@1 ASC NULLS LAST, c@2 ASC NULLS LAST, greptime_timestamp@3 ASC NULLS LAST] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_MergeScanExec: REDACTED
|_|_|_|
| 1_| 0_|_SortPreservingMergeExec: [a@0 ASC NULLS LAST, b@1 ASC NULLS LAST, c@2 ASC NULLS LAST, greptime_timestamp@3 ASC NULLS LAST] REDACTED
|_|_|_SortExec: expr=[a@0 ASC NULLS LAST, b@1 ASC NULLS LAST, c@2 ASC NULLS LAST, greptime_timestamp@3 ASC NULLS LAST], preserve_partitioning=[true] REDACTED
|_|_|_AggregateExec: mode=FinalPartitioned, gby=[a@0 as a, b@1 as b, c@2 as c, greptime_timestamp@3 as greptime_timestamp], aggr=[max(prom_max_over_time(greptime_timestamp_range,greptime_value))] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: partitioning=REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[a@2 as a, b@3 as b, c@4 as c, greptime_timestamp@0 as greptime_timestamp], aggr=[max(prom_max_over_time(greptime_timestamp_range,greptime_value))] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_FilterExec: prom_max_over_time(greptime_timestamp_range,greptime_value)@1 IS NOT NULL REDACTED
|_|_|_ProjectionExec: expr=[greptime_timestamp@4 as greptime_timestamp, prom_max_over_time(greptime_timestamp_range@6, greptime_value@5) as prom_max_over_time(greptime_timestamp_range,greptime_value), a@0 as a, b@1 as b, c@2 as c] REDACTED
|_|_|_PromRangeManipulateExec: req range=[1752591864000..1752592164000], interval=[30000], eval range=[120000], time index=[greptime_timestamp] REDACTED
|_|_|_PromSeriesNormalizeExec: offset=[0], time index=[greptime_timestamp], filter NaN: [true] REDACTED
|_|_|_PromSeriesDivideExec: tags=["a", "b", "c", "d"] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeriesScan: region=REDACTED, "partition_count":{"count":0, "mem_ranges":0, "files":0, "file_ranges":0}, "distribution":"PerSeries" REDACTED
|_|_|_|
| 1_| 1_|_SortPreservingMergeExec: [a@0 ASC NULLS LAST, b@1 ASC NULLS LAST, c@2 ASC NULLS LAST, greptime_timestamp@3 ASC NULLS LAST] REDACTED
|_|_|_SortExec: expr=[a@0 ASC NULLS LAST, b@1 ASC NULLS LAST, c@2 ASC NULLS LAST, greptime_timestamp@3 ASC NULLS LAST], preserve_partitioning=[true] REDACTED
|_|_|_AggregateExec: mode=FinalPartitioned, gby=[a@0 as a, b@1 as b, c@2 as c, greptime_timestamp@3 as greptime_timestamp], aggr=[max(prom_max_over_time(greptime_timestamp_range,greptime_value))] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: partitioning=REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[a@2 as a, b@3 as b, c@4 as c, greptime_timestamp@0 as greptime_timestamp], aggr=[max(prom_max_over_time(greptime_timestamp_range,greptime_value))] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_FilterExec: prom_max_over_time(greptime_timestamp_range,greptime_value)@1 IS NOT NULL REDACTED
|_|_|_ProjectionExec: expr=[greptime_timestamp@4 as greptime_timestamp, prom_max_over_time(greptime_timestamp_range@6, greptime_value@5) as prom_max_over_time(greptime_timestamp_range,greptime_value), a@0 as a, b@1 as b, c@2 as c] REDACTED
|_|_|_PromRangeManipulateExec: req range=[1752591864000..1752592164000], interval=[30000], eval range=[120000], time index=[greptime_timestamp] REDACTED
|_|_|_PromSeriesNormalizeExec: offset=[0], time index=[greptime_timestamp], filter NaN: [true] REDACTED
|_|_|_PromSeriesDivideExec: tags=["a", "b", "c", "d"] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeriesScan: region=REDACTED, "partition_count":{"count":0, "mem_ranges":0, "files":0, "file_ranges":0}, "distribution":"PerSeries" REDACTED
|_|_|_|
|_|_| Total rows: 0_|
@@ -118,12 +108,8 @@ tql explain (1752591864, 1752592164, '30s') sum by (a, b) (max_over_time(aggr_op
| | ]] |
| physical_plan | SortPreservingMergeExec: [a@0 ASC NULLS LAST, b@1 ASC NULLS LAST, greptime_timestamp@2 ASC NULLS LAST] |
| | SortExec: expr=[a@0 ASC NULLS LAST, b@1 ASC NULLS LAST, greptime_timestamp@2 ASC NULLS LAST], preserve_partitioning=[true] |
| | AggregateExec: mode=FinalPartitioned, gby=[a@0 as a, b@1 as b, greptime_timestamp@2 as greptime_timestamp], aggr=[sum(prom_max_over_time(greptime_timestamp_range,greptime_value))] |
| | CoalesceBatchesExec: target_batch_size=8192 |
| | RepartitionExec: partitioning=REDACTED
| | AggregateExec: mode=Partial, gby=[a@0 as a, b@1 as b, greptime_timestamp@2 as greptime_timestamp], aggr=[sum(prom_max_over_time(greptime_timestamp_range,greptime_value))] |
| | CooperativeExec |
| | MergeScanExec: REDACTED
| | AggregateExec: mode=SinglePartitioned, gby=[a@0 as a, b@1 as b, greptime_timestamp@2 as greptime_timestamp], aggr=[sum(prom_max_over_time(greptime_timestamp_range,greptime_value))] |
| | MergeScanExec: REDACTED
| | |
+---------------+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
@@ -141,37 +127,27 @@ tql analyze (1752591864, 1752592164, '30s') sum by (a, b) (max_over_time(aggr_op
+-+-+-+
| 0_| 0_|_SortPreservingMergeExec: [a@0 ASC NULLS LAST, b@1 ASC NULLS LAST, greptime_timestamp@2 ASC NULLS LAST] REDACTED
|_|_|_SortExec: expr=[a@0 ASC NULLS LAST, b@1 ASC NULLS LAST, greptime_timestamp@2 ASC NULLS LAST], preserve_partitioning=[true] REDACTED
|_|_|_AggregateExec: mode=FinalPartitioned, gby=[a@0 as a, b@1 as b, greptime_timestamp@2 as greptime_timestamp], aggr=[sum(prom_max_over_time(greptime_timestamp_range,greptime_value))] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: partitioning=REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[a@0 as a, b@1 as b, greptime_timestamp@2 as greptime_timestamp], aggr=[sum(prom_max_over_time(greptime_timestamp_range,greptime_value))] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_AggregateExec: mode=SinglePartitioned, gby=[a@0 as a, b@1 as b, greptime_timestamp@2 as greptime_timestamp], aggr=[sum(prom_max_over_time(greptime_timestamp_range,greptime_value))] REDACTED
|_|_|_MergeScanExec: REDACTED
|_|_|_|
| 1_| 0_|_AggregateExec: mode=FinalPartitioned, gby=[a@0 as a, b@1 as b, greptime_timestamp@2 as greptime_timestamp], aggr=[__sum_state(prom_max_over_time(greptime_timestamp_range,greptime_value))] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: partitioning=REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[a@2 as a, b@3 as b, greptime_timestamp@0 as greptime_timestamp], aggr=[__sum_state(prom_max_over_time(greptime_timestamp_range,greptime_value))] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_FilterExec: prom_max_over_time(greptime_timestamp_range,greptime_value)@1 IS NOT NULL REDACTED
|_|_|_ProjectionExec: expr=[greptime_timestamp@4 as greptime_timestamp, prom_max_over_time(greptime_timestamp_range@6, greptime_value@5) as prom_max_over_time(greptime_timestamp_range,greptime_value), a@0 as a, b@1 as b] REDACTED
|_|_|_PromRangeManipulateExec: req range=[1752591864000..1752592164000], interval=[30000], eval range=[120000], time index=[greptime_timestamp] REDACTED
|_|_|_PromSeriesNormalizeExec: offset=[0], time index=[greptime_timestamp], filter NaN: [true] REDACTED
|_|_|_PromSeriesDivideExec: tags=["a", "b", "c", "d"] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeriesScan: region=REDACTED, "partition_count":{"count":0, "mem_ranges":0, "files":0, "file_ranges":0}, "distribution":"PerSeries" REDACTED
|_|_|_|
| 1_| 1_|_AggregateExec: mode=FinalPartitioned, gby=[a@0 as a, b@1 as b, greptime_timestamp@2 as greptime_timestamp], aggr=[__sum_state(prom_max_over_time(greptime_timestamp_range,greptime_value))] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: partitioning=REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[a@2 as a, b@3 as b, greptime_timestamp@0 as greptime_timestamp], aggr=[__sum_state(prom_max_over_time(greptime_timestamp_range,greptime_value))] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_FilterExec: prom_max_over_time(greptime_timestamp_range,greptime_value)@1 IS NOT NULL REDACTED
|_|_|_ProjectionExec: expr=[greptime_timestamp@4 as greptime_timestamp, prom_max_over_time(greptime_timestamp_range@6, greptime_value@5) as prom_max_over_time(greptime_timestamp_range,greptime_value), a@0 as a, b@1 as b] REDACTED
|_|_|_PromRangeManipulateExec: req range=[1752591864000..1752592164000], interval=[30000], eval range=[120000], time index=[greptime_timestamp] REDACTED
|_|_|_PromSeriesNormalizeExec: offset=[0], time index=[greptime_timestamp], filter NaN: [true] REDACTED
|_|_|_PromSeriesDivideExec: tags=["a", "b", "c", "d"] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeriesScan: region=REDACTED, "partition_count":{"count":0, "mem_ranges":0, "files":0, "file_ranges":0}, "distribution":"PerSeries" REDACTED
|_|_|_|
|_|_| Total rows: 0_|
@@ -201,12 +177,8 @@ tql explain (1752591864, 1752592164, '30s') avg by (a) (max_over_time(aggr_optim
| | ]] |
| physical_plan | SortPreservingMergeExec: [a@0 ASC NULLS LAST, greptime_timestamp@1 ASC NULLS LAST] |
| | SortExec: expr=[a@0 ASC NULLS LAST, greptime_timestamp@1 ASC NULLS LAST], preserve_partitioning=[true] |
| | AggregateExec: mode=FinalPartitioned, gby=[a@0 as a, greptime_timestamp@1 as greptime_timestamp], aggr=[avg(prom_max_over_time(greptime_timestamp_range,greptime_value))] |
| | CoalesceBatchesExec: target_batch_size=8192 |
| | RepartitionExec: partitioning=REDACTED
| | AggregateExec: mode=Partial, gby=[a@0 as a, greptime_timestamp@1 as greptime_timestamp], aggr=[avg(prom_max_over_time(greptime_timestamp_range,greptime_value))] |
| | CooperativeExec |
| | MergeScanExec: REDACTED
| | AggregateExec: mode=SinglePartitioned, gby=[a@0 as a, greptime_timestamp@1 as greptime_timestamp], aggr=[avg(prom_max_over_time(greptime_timestamp_range,greptime_value))] |
| | MergeScanExec: REDACTED
| | |
+---------------+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
@@ -224,37 +196,27 @@ tql analyze (1752591864, 1752592164, '30s') avg by (a) (max_over_time(aggr_optim
+-+-+-+
| 0_| 0_|_SortPreservingMergeExec: [a@0 ASC NULLS LAST, greptime_timestamp@1 ASC NULLS LAST] REDACTED
|_|_|_SortExec: expr=[a@0 ASC NULLS LAST, greptime_timestamp@1 ASC NULLS LAST], preserve_partitioning=[true] REDACTED
|_|_|_AggregateExec: mode=FinalPartitioned, gby=[a@0 as a, greptime_timestamp@1 as greptime_timestamp], aggr=[avg(prom_max_over_time(greptime_timestamp_range,greptime_value))] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: partitioning=REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[a@0 as a, greptime_timestamp@1 as greptime_timestamp], aggr=[avg(prom_max_over_time(greptime_timestamp_range,greptime_value))] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_AggregateExec: mode=SinglePartitioned, gby=[a@0 as a, greptime_timestamp@1 as greptime_timestamp], aggr=[avg(prom_max_over_time(greptime_timestamp_range,greptime_value))] REDACTED
|_|_|_MergeScanExec: REDACTED
|_|_|_|
| 1_| 0_|_AggregateExec: mode=FinalPartitioned, gby=[a@0 as a, greptime_timestamp@1 as greptime_timestamp], aggr=[__avg_state(prom_max_over_time(greptime_timestamp_range,greptime_value))] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: partitioning=REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[a@2 as a, greptime_timestamp@0 as greptime_timestamp], aggr=[__avg_state(prom_max_over_time(greptime_timestamp_range,greptime_value))] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_FilterExec: prom_max_over_time(greptime_timestamp_range,greptime_value)@1 IS NOT NULL REDACTED
|_|_|_ProjectionExec: expr=[greptime_timestamp@4 as greptime_timestamp, prom_max_over_time(greptime_timestamp_range@6, greptime_value@5) as prom_max_over_time(greptime_timestamp_range,greptime_value), a@0 as a] REDACTED
|_|_|_PromRangeManipulateExec: req range=[1752591864000..1752592164000], interval=[30000], eval range=[120000], time index=[greptime_timestamp] REDACTED
|_|_|_PromSeriesNormalizeExec: offset=[0], time index=[greptime_timestamp], filter NaN: [true] REDACTED
|_|_|_PromSeriesDivideExec: tags=["a", "b", "c", "d"] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeriesScan: region=REDACTED, "partition_count":{"count":0, "mem_ranges":0, "files":0, "file_ranges":0}, "distribution":"PerSeries" REDACTED
|_|_|_|
| 1_| 1_|_AggregateExec: mode=FinalPartitioned, gby=[a@0 as a, greptime_timestamp@1 as greptime_timestamp], aggr=[__avg_state(prom_max_over_time(greptime_timestamp_range,greptime_value))] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: partitioning=REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[a@2 as a, greptime_timestamp@0 as greptime_timestamp], aggr=[__avg_state(prom_max_over_time(greptime_timestamp_range,greptime_value))] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_FilterExec: prom_max_over_time(greptime_timestamp_range,greptime_value)@1 IS NOT NULL REDACTED
|_|_|_ProjectionExec: expr=[greptime_timestamp@4 as greptime_timestamp, prom_max_over_time(greptime_timestamp_range@6, greptime_value@5) as prom_max_over_time(greptime_timestamp_range,greptime_value), a@0 as a] REDACTED
|_|_|_PromRangeManipulateExec: req range=[1752591864000..1752592164000], interval=[30000], eval range=[120000], time index=[greptime_timestamp] REDACTED
|_|_|_PromSeriesNormalizeExec: offset=[0], time index=[greptime_timestamp], filter NaN: [true] REDACTED
|_|_|_PromSeriesDivideExec: tags=["a", "b", "c", "d"] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeriesScan: region=REDACTED, "partition_count":{"count":0, "mem_ranges":0, "files":0, "file_ranges":0}, "distribution":"PerSeries" REDACTED
|_|_|_|
|_|_| Total rows: 0_|
@@ -283,9 +245,7 @@ tql explain (1752591864, 1752592164, '30s') count by (a, b, c, d) (max_over_time
| | TableScan: aggr_optimize_not |
| | ]] |
| physical_plan | SortPreservingMergeExec: [a@0 ASC NULLS LAST, b@1 ASC NULLS LAST, c@2 ASC NULLS LAST, d@3 ASC NULLS LAST, greptime_timestamp@4 ASC NULLS LAST] |
| | CooperativeExec |
| | CooperativeExec |
| | MergeScanExec: REDACTED
| | MergeScanExec: REDACTED
| | |
+---------------+-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
@@ -302,38 +262,26 @@ tql analyze (1752591864, 1752592164, '30s') count by (a, b, c, d) (max_over_time
| stage | node | plan_|
+-+-+-+
| 0_| 0_|_SortPreservingMergeExec: [a@0 ASC NULLS LAST, b@1 ASC NULLS LAST, c@2 ASC NULLS LAST, d@3 ASC NULLS LAST, greptime_timestamp@4 ASC NULLS LAST] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_MergeScanExec: REDACTED
|_|_|_|
| 1_| 0_|_SortPreservingMergeExec: [a@0 ASC NULLS LAST, b@1 ASC NULLS LAST, c@2 ASC NULLS LAST, d@3 ASC NULLS LAST, greptime_timestamp@4 ASC NULLS LAST] REDACTED
|_|_|_SortExec: expr=[a@0 ASC NULLS LAST, b@1 ASC NULLS LAST, c@2 ASC NULLS LAST, d@3 ASC NULLS LAST, greptime_timestamp@4 ASC NULLS LAST], preserve_partitioning=[true] REDACTED
|_|_|_AggregateExec: mode=FinalPartitioned, gby=[a@0 as a, b@1 as b, c@2 as c, d@3 as d, greptime_timestamp@4 as greptime_timestamp], aggr=[count(prom_max_over_time(greptime_timestamp_range,greptime_value))] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: partitioning=REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[a@2 as a, b@3 as b, c@4 as c, d@5 as d, greptime_timestamp@0 as greptime_timestamp], aggr=[count(prom_max_over_time(greptime_timestamp_range,greptime_value))] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_AggregateExec: mode=SinglePartitioned, gby=[a@2 as a, b@3 as b, c@4 as c, d@5 as d, greptime_timestamp@0 as greptime_timestamp], aggr=[count(prom_max_over_time(greptime_timestamp_range,greptime_value))] REDACTED
|_|_|_FilterExec: prom_max_over_time(greptime_timestamp_range,greptime_value)@1 IS NOT NULL REDACTED
|_|_|_ProjectionExec: expr=[greptime_timestamp@4 as greptime_timestamp, prom_max_over_time(greptime_timestamp_range@6, greptime_value@5) as prom_max_over_time(greptime_timestamp_range,greptime_value), a@0 as a, b@1 as b, c@2 as c, d@3 as d] REDACTED
|_|_|_PromRangeManipulateExec: req range=[1752591864000..1752592164000], interval=[30000], eval range=[120000], time index=[greptime_timestamp] REDACTED
|_|_|_PromSeriesNormalizeExec: offset=[0], time index=[greptime_timestamp], filter NaN: [true] REDACTED
|_|_|_PromSeriesDivideExec: tags=["a", "b", "c", "d"] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeriesScan: region=REDACTED, "partition_count":{"count":0, "mem_ranges":0, "files":0, "file_ranges":0}, "distribution":"PerSeries" REDACTED
|_|_|_|
| 1_| 1_|_SortPreservingMergeExec: [a@0 ASC NULLS LAST, b@1 ASC NULLS LAST, c@2 ASC NULLS LAST, d@3 ASC NULLS LAST, greptime_timestamp@4 ASC NULLS LAST] REDACTED
|_|_|_SortExec: expr=[a@0 ASC NULLS LAST, b@1 ASC NULLS LAST, c@2 ASC NULLS LAST, d@3 ASC NULLS LAST, greptime_timestamp@4 ASC NULLS LAST], preserve_partitioning=[true] REDACTED
|_|_|_AggregateExec: mode=FinalPartitioned, gby=[a@0 as a, b@1 as b, c@2 as c, d@3 as d, greptime_timestamp@4 as greptime_timestamp], aggr=[count(prom_max_over_time(greptime_timestamp_range,greptime_value))] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: partitioning=REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[a@2 as a, b@3 as b, c@4 as c, d@5 as d, greptime_timestamp@0 as greptime_timestamp], aggr=[count(prom_max_over_time(greptime_timestamp_range,greptime_value))] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_AggregateExec: mode=SinglePartitioned, gby=[a@2 as a, b@3 as b, c@4 as c, d@5 as d, greptime_timestamp@0 as greptime_timestamp], aggr=[count(prom_max_over_time(greptime_timestamp_range,greptime_value))] REDACTED
|_|_|_FilterExec: prom_max_over_time(greptime_timestamp_range,greptime_value)@1 IS NOT NULL REDACTED
|_|_|_ProjectionExec: expr=[greptime_timestamp@4 as greptime_timestamp, prom_max_over_time(greptime_timestamp_range@6, greptime_value@5) as prom_max_over_time(greptime_timestamp_range,greptime_value), a@0 as a, b@1 as b, c@2 as c, d@3 as d] REDACTED
|_|_|_PromRangeManipulateExec: req range=[1752591864000..1752592164000], interval=[30000], eval range=[120000], time index=[greptime_timestamp] REDACTED
|_|_|_PromSeriesNormalizeExec: offset=[0], time index=[greptime_timestamp], filter NaN: [true] REDACTED
|_|_|_PromSeriesDivideExec: tags=["a", "b", "c", "d"] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeriesScan: region=REDACTED, "partition_count":{"count":0, "mem_ranges":0, "files":0, "file_ranges":0}, "distribution":"PerSeries" REDACTED
|_|_|_|
|_|_| Total rows: 0_|
@@ -363,12 +311,8 @@ tql explain (1752591864, 1752592164, '30s') min by (b, c, d) (max_over_time(aggr
| | ]] |
| physical_plan | SortPreservingMergeExec: [b@0 ASC NULLS LAST, c@1 ASC NULLS LAST, d@2 ASC NULLS LAST, greptime_timestamp@3 ASC NULLS LAST] |
| | SortExec: expr=[b@0 ASC NULLS LAST, c@1 ASC NULLS LAST, d@2 ASC NULLS LAST, greptime_timestamp@3 ASC NULLS LAST], preserve_partitioning=[true] |
| | AggregateExec: mode=FinalPartitioned, gby=[b@0 as b, c@1 as c, d@2 as d, greptime_timestamp@3 as greptime_timestamp], aggr=[min(prom_max_over_time(greptime_timestamp_range,greptime_value))] |
| | CoalesceBatchesExec: target_batch_size=8192 |
| | RepartitionExec: partitioning=REDACTED
| | AggregateExec: mode=Partial, gby=[b@0 as b, c@1 as c, d@2 as d, greptime_timestamp@3 as greptime_timestamp], aggr=[min(prom_max_over_time(greptime_timestamp_range,greptime_value))] |
| | CooperativeExec |
| | MergeScanExec: REDACTED
| | AggregateExec: mode=SinglePartitioned, gby=[b@0 as b, c@1 as c, d@2 as d, greptime_timestamp@3 as greptime_timestamp], aggr=[min(prom_max_over_time(greptime_timestamp_range,greptime_value))] |
| | MergeScanExec: REDACTED
| | |
+---------------+--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
@@ -386,37 +330,27 @@ tql analyze (1752591864, 1752592164, '30s') min by (b, c, d) (max_over_time(aggr
+-+-+-+
| 0_| 0_|_SortPreservingMergeExec: [b@0 ASC NULLS LAST, c@1 ASC NULLS LAST, d@2 ASC NULLS LAST, greptime_timestamp@3 ASC NULLS LAST] REDACTED
|_|_|_SortExec: expr=[b@0 ASC NULLS LAST, c@1 ASC NULLS LAST, d@2 ASC NULLS LAST, greptime_timestamp@3 ASC NULLS LAST], preserve_partitioning=[true] REDACTED
|_|_|_AggregateExec: mode=FinalPartitioned, gby=[b@0 as b, c@1 as c, d@2 as d, greptime_timestamp@3 as greptime_timestamp], aggr=[min(prom_max_over_time(greptime_timestamp_range,greptime_value))] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: partitioning=REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[b@0 as b, c@1 as c, d@2 as d, greptime_timestamp@3 as greptime_timestamp], aggr=[min(prom_max_over_time(greptime_timestamp_range,greptime_value))] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_AggregateExec: mode=SinglePartitioned, gby=[b@0 as b, c@1 as c, d@2 as d, greptime_timestamp@3 as greptime_timestamp], aggr=[min(prom_max_over_time(greptime_timestamp_range,greptime_value))] REDACTED
|_|_|_MergeScanExec: REDACTED
|_|_|_|
| 1_| 0_|_AggregateExec: mode=FinalPartitioned, gby=[b@0 as b, c@1 as c, d@2 as d, greptime_timestamp@3 as greptime_timestamp], aggr=[__min_state(prom_max_over_time(greptime_timestamp_range,greptime_value))] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: partitioning=REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[b@2 as b, c@3 as c, d@4 as d, greptime_timestamp@0 as greptime_timestamp], aggr=[__min_state(prom_max_over_time(greptime_timestamp_range,greptime_value))] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_FilterExec: prom_max_over_time(greptime_timestamp_range,greptime_value)@1 IS NOT NULL REDACTED
|_|_|_ProjectionExec: expr=[greptime_timestamp@4 as greptime_timestamp, prom_max_over_time(greptime_timestamp_range@6, greptime_value@5) as prom_max_over_time(greptime_timestamp_range,greptime_value), b@1 as b, c@2 as c, d@3 as d] REDACTED
|_|_|_PromRangeManipulateExec: req range=[1752591864000..1752592164000], interval=[30000], eval range=[120000], time index=[greptime_timestamp] REDACTED
|_|_|_PromSeriesNormalizeExec: offset=[0], time index=[greptime_timestamp], filter NaN: [true] REDACTED
|_|_|_PromSeriesDivideExec: tags=["a", "b", "c", "d"] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeriesScan: region=REDACTED, "partition_count":{"count":0, "mem_ranges":0, "files":0, "file_ranges":0}, "distribution":"PerSeries" REDACTED
|_|_|_|
| 1_| 1_|_AggregateExec: mode=FinalPartitioned, gby=[b@0 as b, c@1 as c, d@2 as d, greptime_timestamp@3 as greptime_timestamp], aggr=[__min_state(prom_max_over_time(greptime_timestamp_range,greptime_value))] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: partitioning=REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[b@2 as b, c@3 as c, d@4 as d, greptime_timestamp@0 as greptime_timestamp], aggr=[__min_state(prom_max_over_time(greptime_timestamp_range,greptime_value))] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_FilterExec: prom_max_over_time(greptime_timestamp_range,greptime_value)@1 IS NOT NULL REDACTED
|_|_|_ProjectionExec: expr=[greptime_timestamp@4 as greptime_timestamp, prom_max_over_time(greptime_timestamp_range@6, greptime_value@5) as prom_max_over_time(greptime_timestamp_range,greptime_value), b@1 as b, c@2 as c, d@3 as d] REDACTED
|_|_|_PromRangeManipulateExec: req range=[1752591864000..1752592164000], interval=[30000], eval range=[120000], time index=[greptime_timestamp] REDACTED
|_|_|_PromSeriesNormalizeExec: offset=[0], time index=[greptime_timestamp], filter NaN: [true] REDACTED
|_|_|_PromSeriesDivideExec: tags=["a", "b", "c", "d"] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeriesScan: region=REDACTED, "partition_count":{"count":0, "mem_ranges":0, "files":0, "file_ranges":0}, "distribution":"PerSeries" REDACTED
|_|_|_|
|_|_| Total rows: 0_|
@@ -444,11 +378,9 @@ tql explain sum(aggr_optimize_not);
| physical_plan | SortPreservingMergeExec: [greptime_timestamp@0 ASC NULLS LAST] |
| | SortExec: expr=[greptime_timestamp@0 ASC NULLS LAST], preserve_partitioning=[true] |
| | AggregateExec: mode=FinalPartitioned, gby=[greptime_timestamp@0 as greptime_timestamp], aggr=[sum(aggr_optimize_not.greptime_value)] |
| | CoalesceBatchesExec: target_batch_size=8192 |
| | RepartitionExec: partitioning=REDACTED
| | AggregateExec: mode=Partial, gby=[greptime_timestamp@0 as greptime_timestamp], aggr=[sum(aggr_optimize_not.greptime_value)] |
| | CooperativeExec |
| | MergeScanExec: REDACTED
| | RepartitionExec: partitioning=REDACTED
| | AggregateExec: mode=Partial, gby=[greptime_timestamp@0 as greptime_timestamp], aggr=[sum(aggr_optimize_not.greptime_value)] |
| | MergeScanExec: REDACTED
| | |
+---------------+----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
@@ -467,30 +399,24 @@ tql analyze sum(aggr_optimize_not);
| 0_| 0_|_SortPreservingMergeExec: [greptime_timestamp@0 ASC NULLS LAST] REDACTED
|_|_|_SortExec: expr=[greptime_timestamp@0 ASC NULLS LAST], preserve_partitioning=[true] REDACTED
|_|_|_AggregateExec: mode=FinalPartitioned, gby=[greptime_timestamp@0 as greptime_timestamp], aggr=[sum(aggr_optimize_not.greptime_value)] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: partitioning=REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[greptime_timestamp@0 as greptime_timestamp], aggr=[sum(aggr_optimize_not.greptime_value)] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_MergeScanExec: REDACTED
|_|_|_|
| 1_| 0_|_AggregateExec: mode=FinalPartitioned, gby=[greptime_timestamp@0 as greptime_timestamp], aggr=[__sum_state(aggr_optimize_not.greptime_value)] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: partitioning=REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[greptime_timestamp@0 as greptime_timestamp], aggr=[__sum_state(aggr_optimize_not.greptime_value)] REDACTED
|_|_|_ProjectionExec: expr=[greptime_timestamp@4 as greptime_timestamp, greptime_value@5 as greptime_value] REDACTED
|_|_|_PromInstantManipulateExec: range=[0..0], lookback=[300000], interval=[300000], time index=[greptime_timestamp] REDACTED
|_|_|_PromSeriesDivideExec: tags=["a", "b", "c", "d"] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeriesScan: region=REDACTED, "partition_count":{"count":0, "mem_ranges":0, "files":0, "file_ranges":0}, "distribution":"PerSeries" REDACTED
|_|_|_|
| 1_| 1_|_AggregateExec: mode=FinalPartitioned, gby=[greptime_timestamp@0 as greptime_timestamp], aggr=[__sum_state(aggr_optimize_not.greptime_value)] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: partitioning=REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[greptime_timestamp@0 as greptime_timestamp], aggr=[__sum_state(aggr_optimize_not.greptime_value)] REDACTED
|_|_|_ProjectionExec: expr=[greptime_timestamp@4 as greptime_timestamp, greptime_value@5 as greptime_value] REDACTED
|_|_|_PromInstantManipulateExec: range=[0..0], lookback=[300000], interval=[300000], time index=[greptime_timestamp] REDACTED
|_|_|_PromSeriesDivideExec: tags=["a", "b", "c", "d"] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeriesScan: region=REDACTED, "partition_count":{"count":0, "mem_ranges":0, "files":0, "file_ranges":0}, "distribution":"PerSeries" REDACTED
|_|_|_|
|_|_| Total rows: 0_|
@@ -549,28 +475,19 @@ tql explain (1752591864, 1752592164, '30s') sum by (a, b, c) (rate(aggr_optimize
| | TableScan: aggr_optimize_not_count |
| | ]] |
| physical_plan | ProjectionExec: expr=[a@0 as a, b@1 as b, c@2 as c, greptime_timestamp@3 as greptime_timestamp, sum(prom_rate(greptime_timestamp_range,greptime_value,greptime_timestamp,Int64(120000)))@5 / sum(prom_rate(greptime_timestamp_range,greptime_value,greptime_timestamp,Int64(120000)))@4 as aggr_optimize_not.sum(prom_rate(greptime_timestamp_range,greptime_value,greptime_timestamp,Int64(120000))) / aggr_optimize_not_count.sum(prom_rate(greptime_timestamp_range,greptime_value,greptime_timestamp,Int64(120000)))] |
| | CoalesceBatchesExec: target_batch_size=8192 |
| | REDACTED
| | CoalescePartitionsExec |
| | AggregateExec: mode=FinalPartitioned, gby=[a@0 as a, b@1 as b, c@2 as c, greptime_timestamp@3 as greptime_timestamp], aggr=[sum(prom_rate(greptime_timestamp_range,greptime_value,greptime_timestamp,Int64(120000)))] |
| | CoalesceBatchesExec: target_batch_size=8192 |
| | RepartitionExec: partitioning=REDACTED
| | AggregateExec: mode=Partial, gby=[a@2 as a, b@3 as b, c@4 as c, greptime_timestamp@0 as greptime_timestamp], aggr=[sum(prom_rate(greptime_timestamp_range,greptime_value,greptime_timestamp,Int64(120000)))] |
| | CoalesceBatchesExec: target_batch_size=8192 |
| | FilterExec: prom_rate(greptime_timestamp_range,greptime_value,greptime_timestamp,Int64(120000))@1 IS NOT NULL |
| | ProjectionExec: expr=[greptime_timestamp@4 as greptime_timestamp, prom_rate(greptime_timestamp_range@6, greptime_value@5, greptime_timestamp@4, 120000) as prom_rate(greptime_timestamp_range,greptime_value,greptime_timestamp,Int64(120000)), a@0 as a, b@1 as b, c@2 as c] |
| | PromRangeManipulateExec: req range=[1752591864000..1752592164000], interval=[30000], eval range=[120000], time index=[greptime_timestamp] |
| | PromSeriesNormalizeExec: offset=[0], time index=[greptime_timestamp], filter NaN: [true] |
| | PromSeriesDivideExec: tags=["a", "b", "c", "d"] |
| | SortExec: expr=[a@0 ASC, b@1 ASC, c@2 ASC, d@3 ASC, greptime_timestamp@4 ASC], preserve_partitioning=[true] |
| | CoalesceBatchesExec: target_batch_size=8192 |
| | RepartitionExec: partitioning=REDACTED
| | CooperativeExec |
| | MergeScanExec: REDACTED
| | REDACTED
| | CoalescePartitionsExec |
| | AggregateExec: mode=SinglePartitioned, gby=[a@2 as a, b@3 as b, c@4 as c, greptime_timestamp@0 as greptime_timestamp], aggr=[sum(prom_rate(greptime_timestamp_range,greptime_value,greptime_timestamp,Int64(120000)))] |
| | FilterExec: prom_rate(greptime_timestamp_range,greptime_value,greptime_timestamp,Int64(120000))@1 IS NOT NULL |
| | ProjectionExec: expr=[greptime_timestamp@4 as greptime_timestamp, prom_rate(greptime_timestamp_range@6, greptime_value@5, greptime_timestamp@4, 120000) as prom_rate(greptime_timestamp_range,greptime_value,greptime_timestamp,Int64(120000)), a@0 as a, b@1 as b, c@2 as c] |
| | PromRangeManipulateExec: req range=[1752591864000..1752592164000], interval=[30000], eval range=[120000], time index=[greptime_timestamp] |
| | PromSeriesNormalizeExec: offset=[0], time index=[greptime_timestamp], filter NaN: [true] |
| | PromSeriesDivideExec: tags=["a", "b", "c", "d"] |
| | SortExec: expr=[a@0 ASC, b@1 ASC, c@2 ASC, d@3 ASC, greptime_timestamp@4 ASC], preserve_partitioning=[true] |
| | MergeScanExec: REDACTED
| | SortExec: expr=[a@0 ASC NULLS LAST, b@1 ASC NULLS LAST, c@2 ASC NULLS LAST, greptime_timestamp@3 ASC NULLS LAST], preserve_partitioning=[true] |
| | CooperativeExec |
| | SortExec: expr=[a@0 ASC NULLS LAST, b@1 ASC NULLS LAST, c@2 ASC NULLS LAST, greptime_timestamp@3 ASC NULLS LAST], preserve_partitioning=[true] |
| | CooperativeExec |
| | MergeScanExec: REDACTED
| | MergeScanExec: REDACTED
| | |
+---------------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
@@ -587,25 +504,16 @@ tql analyze (1752591864, 1752592164, '30s') sum by (a, b, c) (rate(aggr_optimize
| stage | node | plan_|
+-+-+-+
| 0_| 0_|_ProjectionExec: expr=[a@0 as a, b@1 as b, c@2 as c, greptime_timestamp@3 as greptime_timestamp, sum(prom_rate(greptime_timestamp_range,greptime_value,greptime_timestamp,Int64(120000)))@5 / sum(prom_rate(greptime_timestamp_range,greptime_value,greptime_timestamp,Int64(120000)))@4 as aggr_optimize_not.sum(prom_rate(greptime_timestamp_range,greptime_value,greptime_timestamp,Int64(120000))) / aggr_optimize_not_count.sum(prom_rate(greptime_timestamp_range,greptime_value,greptime_timestamp,Int64(120000)))] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_REDACTED
|_|_|_CoalescePartitionsExec REDACTED
|_|_|_AggregateExec: mode=FinalPartitioned, gby=[a@0 as a, b@1 as b, c@2 as c, greptime_timestamp@3 as greptime_timestamp], aggr=[sum(prom_rate(greptime_timestamp_range,greptime_value,greptime_timestamp,Int64(120000)))] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: partitioning=REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[a@2 as a, b@3 as b, c@4 as c, greptime_timestamp@0 as greptime_timestamp], aggr=[sum(prom_rate(greptime_timestamp_range,greptime_value,greptime_timestamp,Int64(120000)))] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_AggregateExec: mode=SinglePartitioned, gby=[a@2 as a, b@3 as b, c@4 as c, greptime_timestamp@0 as greptime_timestamp], aggr=[sum(prom_rate(greptime_timestamp_range,greptime_value,greptime_timestamp,Int64(120000)))] REDACTED
|_|_|_FilterExec: prom_rate(greptime_timestamp_range,greptime_value,greptime_timestamp,Int64(120000))@1 IS NOT NULL REDACTED
|_|_|_ProjectionExec: expr=[greptime_timestamp@4 as greptime_timestamp, prom_rate(greptime_timestamp_range@6, greptime_value@5, greptime_timestamp@4, 120000) as prom_rate(greptime_timestamp_range,greptime_value,greptime_timestamp,Int64(120000)), a@0 as a, b@1 as b, c@2 as c] REDACTED
|_|_|_PromRangeManipulateExec: req range=[1752591864000..1752592164000], interval=[30000], eval range=[120000], time index=[greptime_timestamp] REDACTED
|_|_|_PromSeriesNormalizeExec: offset=[0], time index=[greptime_timestamp], filter NaN: [true] REDACTED
|_|_|_PromSeriesDivideExec: tags=["a", "b", "c", "d"] REDACTED
|_|_|_SortExec: expr=[a@0 ASC, b@1 ASC, c@2 ASC, d@3 ASC, greptime_timestamp@4 ASC], preserve_partitioning=[true] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: partitioning=REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_MergeScanExec: REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SortExec: expr=[a@0 ASC NULLS LAST, b@1 ASC NULLS LAST, c@2 ASC NULLS LAST, greptime_timestamp@3 ASC NULLS LAST], preserve_partitioning=[true] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_MergeScanExec: REDACTED
@@ -620,32 +528,26 @@ tql analyze (1752591864, 1752592164, '30s') sum by (a, b, c) (rate(aggr_optimize
|_|_|_SortPreservingMergeExec: [a@0 ASC NULLS LAST, b@1 ASC NULLS LAST, c@2 ASC NULLS LAST, greptime_timestamp@3 ASC NULLS LAST] REDACTED
|_|_|_SortExec: expr=[a@0 ASC NULLS LAST, b@1 ASC NULLS LAST, c@2 ASC NULLS LAST, greptime_timestamp@3 ASC NULLS LAST], preserve_partitioning=[true] REDACTED
|_|_|_AggregateExec: mode=FinalPartitioned, gby=[a@0 as a, b@1 as b, c@2 as c, greptime_timestamp@3 as greptime_timestamp], aggr=[sum(prom_rate(greptime_timestamp_range,greptime_value,aggr_optimize_not.greptime_timestamp,Int64(120000)))] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: partitioning=REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[a@2 as a, b@3 as b, c@4 as c, greptime_timestamp@0 as greptime_timestamp], aggr=[sum(prom_rate(greptime_timestamp_range,greptime_value,aggr_optimize_not.greptime_timestamp,Int64(120000)))] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_FilterExec: prom_rate(greptime_timestamp_range,greptime_value,aggr_optimize_not.greptime_timestamp,Int64(120000))@1 IS NOT NULL REDACTED
|_|_|_ProjectionExec: expr=[greptime_timestamp@4 as greptime_timestamp, prom_rate(greptime_timestamp_range@6, greptime_value@5, greptime_timestamp@4, 120000) as prom_rate(greptime_timestamp_range,greptime_value,aggr_optimize_not.greptime_timestamp,Int64(120000)), a@0 as a, b@1 as b, c@2 as c] REDACTED
|_|_|_PromRangeManipulateExec: req range=[1752591864000..1752592164000], interval=[30000], eval range=[120000], time index=[greptime_timestamp] REDACTED
|_|_|_PromSeriesNormalizeExec: offset=[0], time index=[greptime_timestamp], filter NaN: [true] REDACTED
|_|_|_PromSeriesDivideExec: tags=["a", "b", "c", "d"] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeriesScan: region=REDACTED, "partition_count":{"count":0, "mem_ranges":0, "files":0, "file_ranges":0}, "distribution":"PerSeries" REDACTED
|_|_|_|
| 1_| 1_|_ProjectionExec: expr=[a@0 as a, b@1 as b, c@2 as c, greptime_timestamp@3 as greptime_timestamp, sum(prom_rate(greptime_timestamp_range,greptime_value,aggr_optimize_not.greptime_timestamp,Int64(120000)))@4 as sum(prom_rate(greptime_timestamp_range,greptime_value,greptime_timestamp,Int64(120000)))] REDACTED
|_|_|_SortPreservingMergeExec: [a@0 ASC NULLS LAST, b@1 ASC NULLS LAST, c@2 ASC NULLS LAST, greptime_timestamp@3 ASC NULLS LAST] REDACTED
|_|_|_SortExec: expr=[a@0 ASC NULLS LAST, b@1 ASC NULLS LAST, c@2 ASC NULLS LAST, greptime_timestamp@3 ASC NULLS LAST], preserve_partitioning=[true] REDACTED
|_|_|_AggregateExec: mode=FinalPartitioned, gby=[a@0 as a, b@1 as b, c@2 as c, greptime_timestamp@3 as greptime_timestamp], aggr=[sum(prom_rate(greptime_timestamp_range,greptime_value,aggr_optimize_not.greptime_timestamp,Int64(120000)))] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: partitioning=REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[a@2 as a, b@3 as b, c@4 as c, greptime_timestamp@0 as greptime_timestamp], aggr=[sum(prom_rate(greptime_timestamp_range,greptime_value,aggr_optimize_not.greptime_timestamp,Int64(120000)))] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_FilterExec: prom_rate(greptime_timestamp_range,greptime_value,aggr_optimize_not.greptime_timestamp,Int64(120000))@1 IS NOT NULL REDACTED
|_|_|_ProjectionExec: expr=[greptime_timestamp@4 as greptime_timestamp, prom_rate(greptime_timestamp_range@6, greptime_value@5, greptime_timestamp@4, 120000) as prom_rate(greptime_timestamp_range,greptime_value,aggr_optimize_not.greptime_timestamp,Int64(120000)), a@0 as a, b@1 as b, c@2 as c] REDACTED
|_|_|_PromRangeManipulateExec: req range=[1752591864000..1752592164000], interval=[30000], eval range=[120000], time index=[greptime_timestamp] REDACTED
|_|_|_PromSeriesNormalizeExec: offset=[0], time index=[greptime_timestamp], filter NaN: [true] REDACTED
|_|_|_PromSeriesDivideExec: tags=["a", "b", "c", "d"] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeriesScan: region=REDACTED, "partition_count":{"count":0, "mem_ranges":0, "files":0, "file_ranges":0}, "distribution":"PerSeries" REDACTED
|_|_|_|
|_|_| Total rows: 0_|
@@ -703,18 +605,14 @@ GROUP BY
|_|_|_|
| 1_| 0_|_ProjectionExec: expr=[min(aggr_optimize_not.greptime_value)@3 as min(aggr_optimize_not.greptime_value)] REDACTED
|_|_|_AggregateExec: mode=FinalPartitioned, gby=[a@0 as a, b@1 as b, c@2 as c], aggr=[min(aggr_optimize_not.greptime_value)] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: partitioning=REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[a@0 as a, b@1 as b, c@2 as c], aggr=[min(aggr_optimize_not.greptime_value)] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":{"count":0, "mem_ranges":0, "files":0, "file_ranges":0} REDACTED
|_|_|_|
| 1_| 1_|_ProjectionExec: expr=[min(aggr_optimize_not.greptime_value)@3 as min(aggr_optimize_not.greptime_value)] REDACTED
|_|_|_AggregateExec: mode=FinalPartitioned, gby=[a@0 as a, b@1 as b, c@2 as c], aggr=[min(aggr_optimize_not.greptime_value)] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: partitioning=REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[a@0 as a, b@1 as b, c@2 as c], aggr=[min(aggr_optimize_not.greptime_value)] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":{"count":0, "mem_ranges":0, "files":0, "file_ranges":0} REDACTED
|_|_|_|
|_|_| Total rows: 0_|
@@ -774,18 +672,14 @@ GROUP BY
|_|_|_|
| 1_| 0_|_ProjectionExec: expr=[min(aggr_optimize_not.greptime_value)@4 as min(aggr_optimize_not.greptime_value)] REDACTED
|_|_|_AggregateExec: mode=FinalPartitioned, gby=[a@0 as a, b@1 as b, c@2 as c, d@3 as d], aggr=[min(aggr_optimize_not.greptime_value)] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: partitioning=REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[a@0 as a, b@1 as b, c@2 as c, d@3 as d], aggr=[min(aggr_optimize_not.greptime_value)] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":{"count":0, "mem_ranges":0, "files":0, "file_ranges":0} REDACTED
|_|_|_|
| 1_| 1_|_ProjectionExec: expr=[min(aggr_optimize_not.greptime_value)@4 as min(aggr_optimize_not.greptime_value)] REDACTED
|_|_|_AggregateExec: mode=FinalPartitioned, gby=[a@0 as a, b@1 as b, c@2 as c, d@3 as d], aggr=[min(aggr_optimize_not.greptime_value)] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: partitioning=REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[a@0 as a, b@1 as b, c@2 as c, d@3 as d], aggr=[min(aggr_optimize_not.greptime_value)] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":{"count":0, "mem_ranges":0, "files":0, "file_ranges":0} REDACTED
|_|_|_|
|_|_| Total rows: 0_|
@@ -845,17 +739,13 @@ GROUP BY
|_|_|_MergeScanExec: REDACTED
|_|_|_|
| 1_| 0_|_AggregateExec: mode=FinalPartitioned, gby=[a@0 as a, b@1 as b], aggr=[__min_state(aggr_optimize_not.greptime_value)] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: partitioning=REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[a@0 as a, b@1 as b], aggr=[__min_state(aggr_optimize_not.greptime_value)] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":{"count":0, "mem_ranges":0, "files":0, "file_ranges":0} REDACTED
|_|_|_|
| 1_| 1_|_AggregateExec: mode=FinalPartitioned, gby=[a@0 as a, b@1 as b], aggr=[__min_state(aggr_optimize_not.greptime_value)] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: partitioning=REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[a@0 as a, b@1 as b], aggr=[__min_state(aggr_optimize_not.greptime_value)] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":{"count":0, "mem_ranges":0, "files":0, "file_ranges":0} REDACTED
|_|_|_|
|_|_| Total rows: 0_|
@@ -915,17 +805,13 @@ GROUP BY
|_|_|_MergeScanExec: REDACTED
|_|_|_|
| 1_| 0_|_AggregateExec: mode=FinalPartitioned, gby=[a@0 as a, b@1 as b], aggr=[__min_state(aggr_optimize_not.greptime_value), __max_state(aggr_optimize_not.greptime_value)] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: partitioning=REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[a@0 as a, b@1 as b], aggr=[__min_state(aggr_optimize_not.greptime_value), __max_state(aggr_optimize_not.greptime_value)] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":{"count":0, "mem_ranges":0, "files":0, "file_ranges":0} REDACTED
|_|_|_|
| 1_| 1_|_AggregateExec: mode=FinalPartitioned, gby=[a@0 as a, b@1 as b], aggr=[__min_state(aggr_optimize_not.greptime_value), __max_state(aggr_optimize_not.greptime_value)] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: partitioning=REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[a@0 as a, b@1 as b], aggr=[__min_state(aggr_optimize_not.greptime_value), __max_state(aggr_optimize_not.greptime_value)] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":{"count":0, "mem_ranges":0, "files":0, "file_ranges":0} REDACTED
|_|_|_|
|_|_| Total rows: 0_|
@@ -1003,17 +889,13 @@ GROUP BY
|_|_|_MergeScanExec: REDACTED
|_|_|_|
| 1_| 0_|_AggregateExec: mode=FinalPartitioned, gby=[a@0 as a], aggr=[__min_state(aggr_optimize_not.greptime_value)] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: partitioning=REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[a@0 as a], aggr=[__min_state(aggr_optimize_not.greptime_value)] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":{"count":0, "mem_ranges":0, "files":0, "file_ranges":0} REDACTED
|_|_|_|
| 1_| 1_|_AggregateExec: mode=FinalPartitioned, gby=[a@0 as a], aggr=[__min_state(aggr_optimize_not.greptime_value)] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: partitioning=REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[a@0 as a], aggr=[__min_state(aggr_optimize_not.greptime_value)] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":{"count":0, "mem_ranges":0, "files":0, "file_ranges":0} REDACTED
|_|_|_|
|_|_| Total rows: 0_|
@@ -1093,8 +975,6 @@ EXPLAIN SELECT pk_col_1, pk_col_2, sum(val_col_1) FROM step_aggr_extended GROUP
|_|_TableScan: step_aggr_extended_|
|_| ]]_|
| physical_plan | SortPreservingMergeExec: [pk_col_1@0 ASC NULLS LAST, pk_col_2@1 ASC NULLS LAST]_|
|_|_CooperativeExec_|
|_|_CooperativeExec_|
|_|_MergeScanExec: REDACTED
|_|_|
+-+-+
@@ -1133,11 +1013,9 @@ EXPLAIN SELECT COUNT(DISTINCT val_col_1) FROM step_aggr_extended;
|_|_CoalescePartitionsExec_|
|_|_AggregateExec: mode=Partial, gby=[], aggr=[count(alias1)]_|
|_|_AggregateExec: mode=FinalPartitioned, gby=[alias1@0 as alias1], aggr=[]_|
|_|_CoalesceBatchesExec: target_batch_size=8192_|
|_|_RepartitionExec: partitioning=REDACTED
|_|_AggregateExec: mode=Partial, gby=[val_col_1@0 as alias1], aggr=[]_|
|_|_ProjectionExec: expr=[val_col_1@2 as val_col_1]_|
|_|_CooperativeExec_|
|_|_MergeScanExec: REDACTED
|_|_|
+-+-+
@@ -1176,13 +1054,10 @@ EXPLAIN SELECT pk_col_2, sum(val_col_1) FROM step_aggr_extended GROUP BY pk_col_
|_| ]]_|
| physical_plan | SortPreservingMergeExec: [pk_col_2@0 ASC NULLS LAST]_|
|_|_SortExec: expr=[pk_col_2@0 ASC NULLS LAST], preserve_partitioning=[true]_|
|_|_CoalesceBatchesExec: target_batch_size=8192_|
|_|_FilterExec: sum(step_aggr_extended.val_col_1)@1 > 300_|
|_|_AggregateExec: mode=FinalPartitioned, gby=[pk_col_2@0 as pk_col_2], aggr=[sum(step_aggr_extended.val_col_1)]_|
|_|_CoalesceBatchesExec: target_batch_size=8192_|
|_|_RepartitionExec: partitioning=REDACTED
|_|_AggregateExec: mode=Partial, gby=[pk_col_2@0 as pk_col_2], aggr=[sum(step_aggr_extended.val_col_1)]_|
|_|_CooperativeExec_|
|_|_MergeScanExec: REDACTED
|_|_|
+-+-+
@@ -1219,7 +1094,6 @@ EXPLAIN SELECT SUM(val_col_3), COUNT(val_col_2), COUNT(val_col_3), COUNT(*) FROM
|_|_AggregateExec: mode=Final, gby=[], aggr=[sum(step_aggr_extended.val_col_3), count(step_aggr_extended.val_col_2), count(step_aggr_extended.val_col_3), count(Int64(1))]_|
|_|_CoalescePartitionsExec_|
|_|_AggregateExec: mode=Partial, gby=[], aggr=[sum(step_aggr_extended.val_col_3), count(step_aggr_extended.val_col_2), count(step_aggr_extended.val_col_3), count(Int64(1))]_|
|_|_CooperativeExec_|
|_|_MergeScanExec: REDACTED
|_|_|
+-+-+
@@ -1254,7 +1128,6 @@ EXPLAIN SELECT MIN(pk_col_1), MAX(val_col_2) FROM step_aggr_extended;
| physical_plan | AggregateExec: mode=Final, gby=[], aggr=[min(step_aggr_extended.pk_col_1), max(step_aggr_extended.val_col_2)]_|
|_|_CoalescePartitionsExec_|
|_|_AggregateExec: mode=Partial, gby=[], aggr=[min(step_aggr_extended.pk_col_1), max(step_aggr_extended.val_col_2)]_|
|_|_CooperativeExec_|
|_|_MergeScanExec: REDACTED
|_|_|
+-+-+
@@ -1292,7 +1165,6 @@ EXPLAIN SELECT SUM(val_col_1), COUNT(*) FROM step_aggr_extended WHERE pk_col_1 =
|_|_AggregateExec: mode=Final, gby=[], aggr=[sum(step_aggr_extended.val_col_1), count(Int64(1))]_|
|_|_CoalescePartitionsExec_|
|_|_AggregateExec: mode=Partial, gby=[], aggr=[sum(step_aggr_extended.val_col_1), count(Int64(1))]_|
|_|_CooperativeExec_|
|_|_MergeScanExec: REDACTED
|_|_|
+-+-+

42
tests/cases/distributed/explain/step_aggr_basic.result
View File

@@ -60,7 +60,6 @@ FROM
| physical_plan | AggregateExec: mode=Final, gby=[], aggr=[count(integers.i)]_|
|_|_CoalescePartitionsExec_|
|_|_AggregateExec: mode=Partial, gby=[], aggr=[count(integers.i)]_|
|_|_CooperativeExec_|
|_|_MergeScanExec: REDACTED
|_|_|
+-+-+
@@ -86,25 +85,21 @@ FROM
| 0_| 0_|_AggregateExec: mode=Final, gby=[], aggr=[count(integers.i)] REDACTED
|_|_|_CoalescePartitionsExec REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[], aggr=[count(integers.i)] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_MergeScanExec: REDACTED
|_|_|_|
| 1_| 0_|_AggregateExec: mode=Final, gby=[], aggr=[__count_state(integers.i)] REDACTED
|_|_|_CoalescePartitionsExec REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[], aggr=[__count_state(integers.i)] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
| 1_| 1_|_AggregateExec: mode=Final, gby=[], aggr=[__count_state(integers.i)] REDACTED
|_|_|_CoalescePartitionsExec REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[], aggr=[__count_state(integers.i)] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
| 1_| 2_|_AggregateExec: mode=Final, gby=[], aggr=[__count_state(integers.i)] REDACTED
|_|_|_CoalescePartitionsExec REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[], aggr=[__count_state(integers.i)] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
|_|_| Total rows: 1_|
@@ -151,7 +146,7 @@ ORDER BY
| plan_type_| plan_|
+-+-+
| logical_plan_| Sort: integers.ts ASC NULLS LAST, count(integers.i) ASC NULLS LAST_|
|_|_Aggregate: groupBy=[[integers.ts]], aggr=[[__count_merge(__count_state(integers.i)) AS count(integers.i)]]_|
|_|_Aggregate: groupBy=[[integers.ts]], aggr=[[__count_merge(__count_state(integers.i)) AS count(integers.i)]] |
|_|_MergeScan [is_placeholder=false, remote_input=[_|
|_| Aggregate: groupBy=[[integers.ts]], aggr=[[__count_state(integers.i)]]_|
|_|_TableScan: integers_|
@@ -159,10 +154,8 @@ ORDER BY
| physical_plan | SortPreservingMergeExec: [ts@0 ASC NULLS LAST, count(integers.i)@1 ASC NULLS LAST]_|
|_|_SortExec: expr=[ts@0 ASC NULLS LAST, count(integers.i)@1 ASC NULLS LAST], preserve_partitioning=[true]_|
|_|_AggregateExec: mode=FinalPartitioned, gby=[ts@0 as ts], aggr=[count(integers.i)]_|
|_|_CoalesceBatchesExec: target_batch_size=8192_|
|_|_RepartitionExec: partitioning=REDACTED
|_|_AggregateExec: mode=Partial, gby=[ts@0 as ts], aggr=[count(integers.i)]_|
|_|_CooperativeExec_|
|_|_MergeScanExec: REDACTED
|_|_|
+-+-+
@@ -194,31 +187,23 @@ ORDER BY
| 0_| 0_|_SortPreservingMergeExec: [ts@0 ASC NULLS LAST, count(integers.i)@1 ASC NULLS LAST] REDACTED
|_|_|_SortExec: expr=[ts@0 ASC NULLS LAST, count(integers.i)@1 ASC NULLS LAST], preserve_partitioning=[true] REDACTED
|_|_|_AggregateExec: mode=FinalPartitioned, gby=[ts@0 as ts], aggr=[count(integers.i)] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: partitioning=REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[ts@0 as ts], aggr=[count(integers.i)] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_MergeScanExec: REDACTED
|_|_|_|
| 1_| 0_|_AggregateExec: mode=FinalPartitioned, gby=[ts@0 as ts], aggr=[__count_state(integers.i)] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: partitioning=REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[ts@1 as ts], aggr=[__count_state(integers.i)] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
| 1_| 1_|_AggregateExec: mode=FinalPartitioned, gby=[ts@0 as ts], aggr=[__count_state(integers.i)] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: partitioning=REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[ts@1 as ts], aggr=[__count_state(integers.i)] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
| 1_| 2_|_AggregateExec: mode=FinalPartitioned, gby=[ts@0 as ts], aggr=[__count_state(integers.i)] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: partitioning=REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[ts@1 as ts], aggr=[__count_state(integers.i)] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
|_|_| Total rows: 4_|
@@ -275,10 +260,8 @@ ORDER BY
|_|_SortExec: expr=[time_window@0 ASC NULLS LAST, count(integers.i)@1 ASC NULLS LAST], preserve_partitioning=[true]_|
|_|_ProjectionExec: expr=[date_bin(Utf8("1 hour"),integers.ts)@0 as time_window, count(integers.i)@1 as count(integers.i)]_|
|_|_AggregateExec: mode=FinalPartitioned, gby=[date_bin(Utf8("1 hour"),integers.ts)@0 as date_bin(Utf8("1 hour"),integers.ts)], aggr=[count(integers.i)]_|
|_|_CoalesceBatchesExec: target_batch_size=8192_|
|_|_RepartitionExec: partitioning=REDACTED
|_|_AggregateExec: mode=Partial, gby=[date_bin(Utf8("1 hour"),integers.ts)@0 as date_bin(Utf8("1 hour"),integers.ts)], aggr=[count(integers.i)]_|
|_|_CooperativeExec_|
|_|_MergeScanExec: REDACTED
|_|_|
+-+-+
@@ -311,31 +294,23 @@ ORDER BY
|_|_|_SortExec: expr=[time_window@0 ASC NULLS LAST, count(integers.i)@1 ASC NULLS LAST], preserve_partitioning=[true] REDACTED
|_|_|_ProjectionExec: expr=[date_bin(Utf8("1 hour"),integers.ts)@0 as time_window, count(integers.i)@1 as count(integers.i)] REDACTED
|_|_|_AggregateExec: mode=FinalPartitioned, gby=[date_bin(Utf8("1 hour"),integers.ts)@0 as date_bin(Utf8("1 hour"),integers.ts)], aggr=[count(integers.i)] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: partitioning=REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[date_bin(Utf8("1 hour"),integers.ts)@0 as date_bin(Utf8("1 hour"),integers.ts)], aggr=[count(integers.i)] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_MergeScanExec: REDACTED
|_|_|_|
| 1_| 0_|_AggregateExec: mode=FinalPartitioned, gby=[date_bin(Utf8("1 hour"),integers.ts)@0 as date_bin(Utf8("1 hour"),integers.ts)], aggr=[__count_state(integers.i)] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: partitioning=REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[date_bin(IntervalMonthDayNano { months: 0, days: 0, nanoseconds: 3600000000000 }, ts@1) as date_bin(Utf8("1 hour"),integers.ts)], aggr=[__count_state(integers.i)] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
| 1_| 1_|_AggregateExec: mode=FinalPartitioned, gby=[date_bin(Utf8("1 hour"),integers.ts)@0 as date_bin(Utf8("1 hour"),integers.ts)], aggr=[__count_state(integers.i)] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: partitioning=REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[date_bin(IntervalMonthDayNano { months: 0, days: 0, nanoseconds: 3600000000000 }, ts@1) as date_bin(Utf8("1 hour"),integers.ts)], aggr=[__count_state(integers.i)] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
| 1_| 2_|_AggregateExec: mode=FinalPartitioned, gby=[date_bin(Utf8("1 hour"),integers.ts)@0 as date_bin(Utf8("1 hour"),integers.ts)], aggr=[__count_state(integers.i)] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: partitioning=REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[date_bin(IntervalMonthDayNano { months: 0, days: 0, nanoseconds: 3600000000000 }, ts@1) as date_bin(Utf8("1 hour"),integers.ts)], aggr=[__count_state(integers.i)] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
|_|_| Total rows: 4_|
@@ -400,10 +375,8 @@ ORDER BY
| physical_plan | SortPreservingMergeExec: [integers.ts + Int64(1)@0 ASC NULLS LAST, integers.i / Int64(2)@1 ASC NULLS LAST]_|
|_|_SortExec: expr=[integers.ts + Int64(1)@0 ASC NULLS LAST, integers.i / Int64(2)@1 ASC NULLS LAST], preserve_partitioning=[true]_|
|_|_AggregateExec: mode=FinalPartitioned, gby=[integers.ts + Int64(1)@0 as integers.ts + Int64(1), integers.i / Int64(2)@1 as integers.i / Int64(2)], aggr=[count(integers.i)] |
|_|_CoalesceBatchesExec: target_batch_size=8192_|
|_|_RepartitionExec: partitioning=REDACTED
|_|_AggregateExec: mode=Partial, gby=[integers.ts + Int64(1)@0 as integers.ts + Int64(1), integers.i / Int64(2)@1 as integers.i / Int64(2)], aggr=[count(integers.i)]_|
|_|_CooperativeExec_|
|_|_MergeScanExec: REDACTED
|_|_|
+-+-+
@@ -438,31 +411,23 @@ ORDER BY
| 0_| 0_|_SortPreservingMergeExec: [integers.ts + Int64(1)@0 ASC NULLS LAST, integers.i / Int64(2)@1 ASC NULLS LAST] REDACTED
|_|_|_SortExec: expr=[integers.ts + Int64(1)@0 ASC NULLS LAST, integers.i / Int64(2)@1 ASC NULLS LAST], preserve_partitioning=[true] REDACTED
|_|_|_AggregateExec: mode=FinalPartitioned, gby=[integers.ts + Int64(1)@0 as integers.ts + Int64(1), integers.i / Int64(2)@1 as integers.i / Int64(2)], aggr=[count(integers.i)] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: partitioning=REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[integers.ts + Int64(1)@0 as integers.ts + Int64(1), integers.i / Int64(2)@1 as integers.i / Int64(2)], aggr=[count(integers.i)] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_MergeScanExec: REDACTED
|_|_|_|
| 1_| 0_|_AggregateExec: mode=FinalPartitioned, gby=[integers.ts + Int64(1)@0 as integers.ts + Int64(1), integers.i / Int64(2)@1 as integers.i / Int64(2)], aggr=[__count_state(integers.i)] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: partitioning=REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[CAST(ts@1 AS Int64) + 1 as integers.ts + Int64(1), i@0 / 2 as integers.i / Int64(2)], aggr=[__count_state(integers.i)] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
| 1_| 1_|_AggregateExec: mode=FinalPartitioned, gby=[integers.ts + Int64(1)@0 as integers.ts + Int64(1), integers.i / Int64(2)@1 as integers.i / Int64(2)], aggr=[__count_state(integers.i)] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: partitioning=REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[CAST(ts@1 AS Int64) + 1 as integers.ts + Int64(1), i@0 / 2 as integers.i / Int64(2)], aggr=[__count_state(integers.i)] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
| 1_| 2_|_AggregateExec: mode=FinalPartitioned, gby=[integers.ts + Int64(1)@0 as integers.ts + Int64(1), integers.i / Int64(2)@1 as integers.i / Int64(2)], aggr=[__count_state(integers.i)] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: partitioning=REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[CAST(ts@1 AS Int64) + 1 as integers.ts + Int64(1), i@0 / 2 as integers.i / Int64(2)], aggr=[__count_state(integers.i)] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
|_|_| Total rows: 8_|
@@ -535,7 +500,6 @@ FROM
|_|_AggregateExec: mode=Final, gby=[], aggr=[uddsketch_merge(Int64(128),Float64(0.01),sink_table.udd_state), hll_merge(sink_table.hll_state)]_|
|_|_CoalescePartitionsExec_|
|_|_AggregateExec: mode=Partial, gby=[], aggr=[uddsketch_merge(Int64(128),Float64(0.01),sink_table.udd_state), hll_merge(sink_table.hll_state)]_|
|_|_CooperativeExec_|
|_|_MergeScanExec: REDACTED
|_|_|
+-+-+
@@ -563,25 +527,21 @@ FROM
|_|_|_AggregateExec: mode=Final, gby=[], aggr=[uddsketch_merge(Int64(128),Float64(0.01),sink_table.udd_state), hll_merge(sink_table.hll_state)] REDACTED
|_|_|_CoalescePartitionsExec REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[], aggr=[uddsketch_merge(Int64(128),Float64(0.01),sink_table.udd_state), hll_merge(sink_table.hll_state)] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_MergeScanExec: REDACTED
|_|_|_|
| 1_| 0_|_AggregateExec: mode=Final, gby=[], aggr=[__uddsketch_merge_state(Int64(128),Float64(0.01),sink_table.udd_state), __hll_merge_state(sink_table.hll_state)] REDACTED
|_|_|_CoalescePartitionsExec REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[], aggr=[__uddsketch_merge_state(Int64(128),Float64(0.01),sink_table.udd_state), __hll_merge_state(sink_table.hll_state)] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
| 1_| 1_|_AggregateExec: mode=Final, gby=[], aggr=[__uddsketch_merge_state(Int64(128),Float64(0.01),sink_table.udd_state), __hll_merge_state(sink_table.hll_state)] REDACTED
|_|_|_CoalescePartitionsExec REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[], aggr=[__uddsketch_merge_state(Int64(128),Float64(0.01),sink_table.udd_state), __hll_merge_state(sink_table.hll_state)] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
| 1_| 2_|_AggregateExec: mode=Final, gby=[], aggr=[__uddsketch_merge_state(Int64(128),Float64(0.01),sink_table.udd_state), __hll_merge_state(sink_table.hll_state)] REDACTED
|_|_|_CoalescePartitionsExec REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[], aggr=[__uddsketch_merge_state(Int64(128),Float64(0.01),sink_table.udd_state), __hll_merge_state(sink_table.hll_state)] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
|_|_| Total rows: 1_|

102
tests/cases/distributed/explain/step_aggr_massive.result
View File

@@ -254,10 +254,8 @@ GROUP BY
|_| ]]_|
| physical_plan | ProjectionExec: expr=[env@0 as env, service_name@1 as service_name, city@2 as city, page@3 as page, uddsketch_state(Int64(128),Float64(0.01),CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE NULL END)@5 as lcp_state, max(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE NULL END)@6 as max_lcp, min(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE NULL END)@7 as min_lcp, uddsketch_state(Int64(128),Float64(0.01),CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE NULL END)@8 as fmp_state, max(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE NULL END)@9 as max_fmp, min(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE NULL END)@10 as min_fmp, uddsketch_state(Int64(128),Float64(0.01),CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE NULL END)@11 as fcp_state, max(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE NULL END)@12 as max_fcp, min(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE NULL END)@13 as min_fcp, uddsketch_state(Int64(128),Float64(0.01),CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE NULL END)@14 as fp_state, max(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE NULL END)@15 as max_fp, min(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE NULL END)@16 as min_fp, uddsketch_state(Int64(128),Float64(0.01),CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE NULL END)@17 as tti_state, max(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE NULL END)@18 as max_tti, min(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE NULL END)@19 as min_tti, uddsketch_state(Int64(128),Float64(0.01),CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE NULL END)@20 as fid_state, max(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE NULL END)@21 as max_fid, min(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE NULL END)@22 as min_fid, max(base_table.shard_key)@23 as shard_key, arrow_cast(date_bin(Utf8("60 seconds"),base_table.time),Utf8("Timestamp(s)"))@4 as arrow_cast(date_bin(Utf8("60 seconds"),base_table.time),Utf8("Timestamp(s)"))]_|
|_|_AggregateExec: mode=FinalPartitioned, gby=[env@0 as env, service_name@1 as service_name, city@2 as city, page@3 as page, arrow_cast(date_bin(Utf8("60 seconds"),base_table.time),Utf8("Timestamp(s)"))@4 as arrow_cast(date_bin(Utf8("60 seconds"),base_table.time),Utf8("Timestamp(s)"))], aggr=[uddsketch_state(Int64(128),Float64(0.01),CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE NULL END), max(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE NULL END), min(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE NULL END), uddsketch_state(Int64(128),Float64(0.01),CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE NULL END), max(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE NULL END), min(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE NULL END), uddsketch_state(Int64(128),Float64(0.01),CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE NULL END), max(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE NULL END), min(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE NULL END), uddsketch_state(Int64(128),Float64(0.01),CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE NULL END), max(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE NULL END), min(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE NULL END), uddsketch_state(Int64(128),Float64(0.01),CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE NULL END), max(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE NULL END), min(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE NULL END), uddsketch_state(Int64(128),Float64(0.01),CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE NULL END), max(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE NULL END), min(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE NULL END), max(base_table.shard_key)]_|
|_|_CoalesceBatchesExec: target_batch_size=8192_|
|_|_RepartitionExec: partitioning=REDACTED
|_|_AggregateExec: mode=Partial, gby=[env@0 as env, service_name@1 as service_name, city@2 as city, page@3 as page, arrow_cast(date_bin(Utf8("60 seconds"),base_table.time),Utf8("Timestamp(s)"))@4 as arrow_cast(date_bin(Utf8("60 seconds"),base_table.time),Utf8("Timestamp(s)"))], aggr=[uddsketch_state(Int64(128),Float64(0.01),CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE NULL END), max(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE NULL END), min(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE NULL END), uddsketch_state(Int64(128),Float64(0.01),CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE NULL END), max(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE NULL END), min(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE NULL END), uddsketch_state(Int64(128),Float64(0.01),CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE NULL END), max(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE NULL END), min(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE NULL END), uddsketch_state(Int64(128),Float64(0.01),CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE NULL END), max(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE NULL END), min(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE NULL END), uddsketch_state(Int64(128),Float64(0.01),CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE NULL END), max(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE NULL END), min(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE NULL END), uddsketch_state(Int64(128),Float64(0.01),CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE NULL END), max(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE NULL END), min(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE NULL END), max(base_table.shard_key)]_|
|_|_CooperativeExec_|
|_|_MergeScanExec: REDACTED
|_|_|
+-+-+
@@ -459,170 +457,120 @@ GROUP BY
+-+-+-+
| 0_| 0_|_ProjectionExec: expr=[env@0 as env, service_name@1 as service_name, city@2 as city, page@3 as page, uddsketch_state(Int64(128),Float64(0.01),CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE NULL END)@5 as lcp_state, max(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE NULL END)@6 as max_lcp, min(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE NULL END)@7 as min_lcp, uddsketch_state(Int64(128),Float64(0.01),CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE NULL END)@8 as fmp_state, max(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE NULL END)@9 as max_fmp, min(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE NULL END)@10 as min_fmp, uddsketch_state(Int64(128),Float64(0.01),CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE NULL END)@11 as fcp_state, max(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE NULL END)@12 as max_fcp, min(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE NULL END)@13 as min_fcp, uddsketch_state(Int64(128),Float64(0.01),CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE NULL END)@14 as fp_state, max(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE NULL END)@15 as max_fp, min(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE NULL END)@16 as min_fp, uddsketch_state(Int64(128),Float64(0.01),CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE NULL END)@17 as tti_state, max(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE NULL END)@18 as max_tti, min(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE NULL END)@19 as min_tti, uddsketch_state(Int64(128),Float64(0.01),CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE NULL END)@20 as fid_state, max(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE NULL END)@21 as max_fid, min(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE NULL END)@22 as min_fid, max(base_table.shard_key)@23 as shard_key, arrow_cast(date_bin(Utf8("60 seconds"),base_table.time),Utf8("Timestamp(s)"))@4 as arrow_cast(date_bin(Utf8("60 seconds"),base_table.time),Utf8("Timestamp(s)"))] REDACTED
|_|_|_AggregateExec: mode=FinalPartitioned, gby=[env@0 as env, service_name@1 as service_name, city@2 as city, page@3 as page, arrow_cast(date_bin(Utf8("60 seconds"),base_table.time),Utf8("Timestamp(s)"))@4 as arrow_cast(date_bin(Utf8("60 seconds"),base_table.time),Utf8("Timestamp(s)"))], aggr=[uddsketch_state(Int64(128),Float64(0.01),CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE NULL END), max(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE NULL END), min(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE NULL END), uddsketch_state(Int64(128),Float64(0.01),CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE NULL END), max(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE NULL END), min(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE NULL END), uddsketch_state(Int64(128),Float64(0.01),CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE NULL END), max(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE NULL END), min(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE NULL END), uddsketch_state(Int64(128),Float64(0.01),CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE NULL END), max(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE NULL END), min(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE NULL END), uddsketch_state(Int64(128),Float64(0.01),CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE NULL END), max(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE NULL END), min(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE NULL END), uddsketch_state(Int64(128),Float64(0.01),CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE NULL END), max(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE NULL END), min(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE NULL END), max(base_table.shard_key)] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: partitioning=REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[env@0 as env, service_name@1 as service_name, city@2 as city, page@3 as page, arrow_cast(date_bin(Utf8("60 seconds"),base_table.time),Utf8("Timestamp(s)"))@4 as arrow_cast(date_bin(Utf8("60 seconds"),base_table.time),Utf8("Timestamp(s)"))], aggr=[uddsketch_state(Int64(128),Float64(0.01),CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE NULL END), max(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE NULL END), min(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE NULL END), uddsketch_state(Int64(128),Float64(0.01),CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE NULL END), max(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE NULL END), min(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE NULL END), uddsketch_state(Int64(128),Float64(0.01),CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE NULL END), max(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE NULL END), min(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE NULL END), uddsketch_state(Int64(128),Float64(0.01),CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE NULL END), max(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE NULL END), min(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE NULL END), uddsketch_state(Int64(128),Float64(0.01),CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE NULL END), max(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE NULL END), min(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE NULL END), uddsketch_state(Int64(128),Float64(0.01),CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE NULL END), max(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE NULL END), min(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE NULL END), max(base_table.shard_key)] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_MergeScanExec: REDACTED
|_|_|_|
| 1_| 0_|_AggregateExec: mode=FinalPartitioned, gby=[env@0 as env, service_name@1 as service_name, city@2 as city, page@3 as page, arrow_cast(date_bin(Utf8("60 seconds"),base_table.time),Utf8("Timestamp(s)"))@4 as arrow_cast(date_bin(Utf8("60 seconds"),base_table.time),Utf8("Timestamp(s)"))], aggr=[__uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(base_table.shard_key)] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: partitioning=REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[env@7 as env, service_name@8 as service_name, city@9 as city, page@10 as page, CAST(date_bin(IntervalMonthDayNano { months: 0, days: 0, nanoseconds: 60000000000 }, time@6) AS Timestamp(Second, None)) as arrow_cast(date_bin(Utf8("60 seconds"),base_table.time),Utf8("Timestamp(s)"))], aggr=[__uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(base_table.shard_key)] REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[env@7 as env, service_name@8 as service_name, city@9 as city, page@10 as page, CAST(date_bin(IntervalMonthDayNano { months: 0, days: 0, nanoseconds: 60000000000 }, time@6) AS Timestamp(s)) as arrow_cast(date_bin(Utf8("60 seconds"),base_table.time),Utf8("Timestamp(s)"))], aggr=[__uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(base_table.shard_key)] REDACTED
|_|_|_ProjectionExec: expr=[CASE WHEN lcp@5 > 0 AND lcp@5 < 3000000 THEN lcp@5 END as __common_expr_1, CASE WHEN fmp@6 > 0 AND fmp@6 < 3000000 THEN fmp@6 END as __common_expr_2, CASE WHEN fcp@7 > 0 AND fcp@7 < 3000000 THEN fcp@7 END as __common_expr_3, CASE WHEN fp@8 > 0 AND fp@8 < 3000000 THEN fp@8 END as __common_expr_4, CASE WHEN tti@9 > 0 AND tti@9 < 3000000 THEN tti@9 END as __common_expr_5, CASE WHEN fid@10 > 0 AND fid@10 < 3000000 THEN fid@10 END as __common_expr_6, time@0 as time, env@1 as env, service_name@2 as service_name, city@3 as city, page@4 as page, shard_key@11 as shard_key] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_FilterExec: lcp@5 > 0 AND lcp@5 < 3000000 OR fmp@6 > 0 AND fmp@6 < 3000000 OR fcp@7 > 0 AND fcp@7 < 3000000 OR fp@8 > 0 AND fp@8 < 3000000 OR tti@9 > 0 AND tti@9 < 3000000 OR fid@10 > 0 AND fid@10 < 3000000 REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_UnorderedScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
| 1_| 1_|_AggregateExec: mode=FinalPartitioned, gby=[env@0 as env, service_name@1 as service_name, city@2 as city, page@3 as page, arrow_cast(date_bin(Utf8("60 seconds"),base_table.time),Utf8("Timestamp(s)"))@4 as arrow_cast(date_bin(Utf8("60 seconds"),base_table.time),Utf8("Timestamp(s)"))], aggr=[__uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(base_table.shard_key)] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: partitioning=REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[env@7 as env, service_name@8 as service_name, city@9 as city, page@10 as page, CAST(date_bin(IntervalMonthDayNano { months: 0, days: 0, nanoseconds: 60000000000 }, time@6) AS Timestamp(Second, None)) as arrow_cast(date_bin(Utf8("60 seconds"),base_table.time),Utf8("Timestamp(s)"))], aggr=[__uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(base_table.shard_key)] REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[env@7 as env, service_name@8 as service_name, city@9 as city, page@10 as page, CAST(date_bin(IntervalMonthDayNano { months: 0, days: 0, nanoseconds: 60000000000 }, time@6) AS Timestamp(s)) as arrow_cast(date_bin(Utf8("60 seconds"),base_table.time),Utf8("Timestamp(s)"))], aggr=[__uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(base_table.shard_key)] REDACTED
|_|_|_ProjectionExec: expr=[CASE WHEN lcp@5 > 0 AND lcp@5 < 3000000 THEN lcp@5 END as __common_expr_1, CASE WHEN fmp@6 > 0 AND fmp@6 < 3000000 THEN fmp@6 END as __common_expr_2, CASE WHEN fcp@7 > 0 AND fcp@7 < 3000000 THEN fcp@7 END as __common_expr_3, CASE WHEN fp@8 > 0 AND fp@8 < 3000000 THEN fp@8 END as __common_expr_4, CASE WHEN tti@9 > 0 AND tti@9 < 3000000 THEN tti@9 END as __common_expr_5, CASE WHEN fid@10 > 0 AND fid@10 < 3000000 THEN fid@10 END as __common_expr_6, time@0 as time, env@1 as env, service_name@2 as service_name, city@3 as city, page@4 as page, shard_key@11 as shard_key] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_FilterExec: lcp@5 > 0 AND lcp@5 < 3000000 OR fmp@6 > 0 AND fmp@6 < 3000000 OR fcp@7 > 0 AND fcp@7 < 3000000 OR fp@8 > 0 AND fp@8 < 3000000 OR tti@9 > 0 AND tti@9 < 3000000 OR fid@10 > 0 AND fid@10 < 3000000 REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_UnorderedScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
| 1_| 2_|_AggregateExec: mode=FinalPartitioned, gby=[env@0 as env, service_name@1 as service_name, city@2 as city, page@3 as page, arrow_cast(date_bin(Utf8("60 seconds"),base_table.time),Utf8("Timestamp(s)"))@4 as arrow_cast(date_bin(Utf8("60 seconds"),base_table.time),Utf8("Timestamp(s)"))], aggr=[__uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(base_table.shard_key)] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: partitioning=REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[env@7 as env, service_name@8 as service_name, city@9 as city, page@10 as page, CAST(date_bin(IntervalMonthDayNano { months: 0, days: 0, nanoseconds: 60000000000 }, time@6) AS Timestamp(Second, None)) as arrow_cast(date_bin(Utf8("60 seconds"),base_table.time),Utf8("Timestamp(s)"))], aggr=[__uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(base_table.shard_key)] REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[env@7 as env, service_name@8 as service_name, city@9 as city, page@10 as page, CAST(date_bin(IntervalMonthDayNano { months: 0, days: 0, nanoseconds: 60000000000 }, time@6) AS Timestamp(s)) as arrow_cast(date_bin(Utf8("60 seconds"),base_table.time),Utf8("Timestamp(s)"))], aggr=[__uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(base_table.shard_key)] REDACTED
|_|_|_ProjectionExec: expr=[CASE WHEN lcp@5 > 0 AND lcp@5 < 3000000 THEN lcp@5 END as __common_expr_1, CASE WHEN fmp@6 > 0 AND fmp@6 < 3000000 THEN fmp@6 END as __common_expr_2, CASE WHEN fcp@7 > 0 AND fcp@7 < 3000000 THEN fcp@7 END as __common_expr_3, CASE WHEN fp@8 > 0 AND fp@8 < 3000000 THEN fp@8 END as __common_expr_4, CASE WHEN tti@9 > 0 AND tti@9 < 3000000 THEN tti@9 END as __common_expr_5, CASE WHEN fid@10 > 0 AND fid@10 < 3000000 THEN fid@10 END as __common_expr_6, time@0 as time, env@1 as env, service_name@2 as service_name, city@3 as city, page@4 as page, shard_key@11 as shard_key] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_FilterExec: lcp@5 > 0 AND lcp@5 < 3000000 OR fmp@6 > 0 AND fmp@6 < 3000000 OR fcp@7 > 0 AND fcp@7 < 3000000 OR fp@8 > 0 AND fp@8 < 3000000 OR tti@9 > 0 AND tti@9 < 3000000 OR fid@10 > 0 AND fid@10 < 3000000 REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_UnorderedScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
| 1_| 3_|_AggregateExec: mode=FinalPartitioned, gby=[env@0 as env, service_name@1 as service_name, city@2 as city, page@3 as page, arrow_cast(date_bin(Utf8("60 seconds"),base_table.time),Utf8("Timestamp(s)"))@4 as arrow_cast(date_bin(Utf8("60 seconds"),base_table.time),Utf8("Timestamp(s)"))], aggr=[__uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(base_table.shard_key)] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: partitioning=REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[env@7 as env, service_name@8 as service_name, city@9 as city, page@10 as page, CAST(date_bin(IntervalMonthDayNano { months: 0, days: 0, nanoseconds: 60000000000 }, time@6) AS Timestamp(Second, None)) as arrow_cast(date_bin(Utf8("60 seconds"),base_table.time),Utf8("Timestamp(s)"))], aggr=[__uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(base_table.shard_key)] REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[env@7 as env, service_name@8 as service_name, city@9 as city, page@10 as page, CAST(date_bin(IntervalMonthDayNano { months: 0, days: 0, nanoseconds: 60000000000 }, time@6) AS Timestamp(s)) as arrow_cast(date_bin(Utf8("60 seconds"),base_table.time),Utf8("Timestamp(s)"))], aggr=[__uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(base_table.shard_key)] REDACTED
|_|_|_ProjectionExec: expr=[CASE WHEN lcp@5 > 0 AND lcp@5 < 3000000 THEN lcp@5 END as __common_expr_1, CASE WHEN fmp@6 > 0 AND fmp@6 < 3000000 THEN fmp@6 END as __common_expr_2, CASE WHEN fcp@7 > 0 AND fcp@7 < 3000000 THEN fcp@7 END as __common_expr_3, CASE WHEN fp@8 > 0 AND fp@8 < 3000000 THEN fp@8 END as __common_expr_4, CASE WHEN tti@9 > 0 AND tti@9 < 3000000 THEN tti@9 END as __common_expr_5, CASE WHEN fid@10 > 0 AND fid@10 < 3000000 THEN fid@10 END as __common_expr_6, time@0 as time, env@1 as env, service_name@2 as service_name, city@3 as city, page@4 as page, shard_key@11 as shard_key] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_FilterExec: lcp@5 > 0 AND lcp@5 < 3000000 OR fmp@6 > 0 AND fmp@6 < 3000000 OR fcp@7 > 0 AND fcp@7 < 3000000 OR fp@8 > 0 AND fp@8 < 3000000 OR tti@9 > 0 AND tti@9 < 3000000 OR fid@10 > 0 AND fid@10 < 3000000 REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_UnorderedScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
| 1_| 4_|_AggregateExec: mode=FinalPartitioned, gby=[env@0 as env, service_name@1 as service_name, city@2 as city, page@3 as page, arrow_cast(date_bin(Utf8("60 seconds"),base_table.time),Utf8("Timestamp(s)"))@4 as arrow_cast(date_bin(Utf8("60 seconds"),base_table.time),Utf8("Timestamp(s)"))], aggr=[__uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(base_table.shard_key)] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: partitioning=REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[env@7 as env, service_name@8 as service_name, city@9 as city, page@10 as page, CAST(date_bin(IntervalMonthDayNano { months: 0, days: 0, nanoseconds: 60000000000 }, time@6) AS Timestamp(Second, None)) as arrow_cast(date_bin(Utf8("60 seconds"),base_table.time),Utf8("Timestamp(s)"))], aggr=[__uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(base_table.shard_key)] REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[env@7 as env, service_name@8 as service_name, city@9 as city, page@10 as page, CAST(date_bin(IntervalMonthDayNano { months: 0, days: 0, nanoseconds: 60000000000 }, time@6) AS Timestamp(s)) as arrow_cast(date_bin(Utf8("60 seconds"),base_table.time),Utf8("Timestamp(s)"))], aggr=[__uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(base_table.shard_key)] REDACTED
|_|_|_ProjectionExec: expr=[CASE WHEN lcp@5 > 0 AND lcp@5 < 3000000 THEN lcp@5 END as __common_expr_1, CASE WHEN fmp@6 > 0 AND fmp@6 < 3000000 THEN fmp@6 END as __common_expr_2, CASE WHEN fcp@7 > 0 AND fcp@7 < 3000000 THEN fcp@7 END as __common_expr_3, CASE WHEN fp@8 > 0 AND fp@8 < 3000000 THEN fp@8 END as __common_expr_4, CASE WHEN tti@9 > 0 AND tti@9 < 3000000 THEN tti@9 END as __common_expr_5, CASE WHEN fid@10 > 0 AND fid@10 < 3000000 THEN fid@10 END as __common_expr_6, time@0 as time, env@1 as env, service_name@2 as service_name, city@3 as city, page@4 as page, shard_key@11 as shard_key] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_FilterExec: lcp@5 > 0 AND lcp@5 < 3000000 OR fmp@6 > 0 AND fmp@6 < 3000000 OR fcp@7 > 0 AND fcp@7 < 3000000 OR fp@8 > 0 AND fp@8 < 3000000 OR tti@9 > 0 AND tti@9 < 3000000 OR fid@10 > 0 AND fid@10 < 3000000 REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_UnorderedScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
| 1_| 5_|_AggregateExec: mode=FinalPartitioned, gby=[env@0 as env, service_name@1 as service_name, city@2 as city, page@3 as page, arrow_cast(date_bin(Utf8("60 seconds"),base_table.time),Utf8("Timestamp(s)"))@4 as arrow_cast(date_bin(Utf8("60 seconds"),base_table.time),Utf8("Timestamp(s)"))], aggr=[__uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(base_table.shard_key)] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: partitioning=REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[env@7 as env, service_name@8 as service_name, city@9 as city, page@10 as page, CAST(date_bin(IntervalMonthDayNano { months: 0, days: 0, nanoseconds: 60000000000 }, time@6) AS Timestamp(Second, None)) as arrow_cast(date_bin(Utf8("60 seconds"),base_table.time),Utf8("Timestamp(s)"))], aggr=[__uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(base_table.shard_key)] REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[env@7 as env, service_name@8 as service_name, city@9 as city, page@10 as page, CAST(date_bin(IntervalMonthDayNano { months: 0, days: 0, nanoseconds: 60000000000 }, time@6) AS Timestamp(s)) as arrow_cast(date_bin(Utf8("60 seconds"),base_table.time),Utf8("Timestamp(s)"))], aggr=[__uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(base_table.shard_key)] REDACTED
|_|_|_ProjectionExec: expr=[CASE WHEN lcp@5 > 0 AND lcp@5 < 3000000 THEN lcp@5 END as __common_expr_1, CASE WHEN fmp@6 > 0 AND fmp@6 < 3000000 THEN fmp@6 END as __common_expr_2, CASE WHEN fcp@7 > 0 AND fcp@7 < 3000000 THEN fcp@7 END as __common_expr_3, CASE WHEN fp@8 > 0 AND fp@8 < 3000000 THEN fp@8 END as __common_expr_4, CASE WHEN tti@9 > 0 AND tti@9 < 3000000 THEN tti@9 END as __common_expr_5, CASE WHEN fid@10 > 0 AND fid@10 < 3000000 THEN fid@10 END as __common_expr_6, time@0 as time, env@1 as env, service_name@2 as service_name, city@3 as city, page@4 as page, shard_key@11 as shard_key] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_FilterExec: lcp@5 > 0 AND lcp@5 < 3000000 OR fmp@6 > 0 AND fmp@6 < 3000000 OR fcp@7 > 0 AND fcp@7 < 3000000 OR fp@8 > 0 AND fp@8 < 3000000 OR tti@9 > 0 AND tti@9 < 3000000 OR fid@10 > 0 AND fid@10 < 3000000 REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_UnorderedScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
| 1_| 6_|_AggregateExec: mode=FinalPartitioned, gby=[env@0 as env, service_name@1 as service_name, city@2 as city, page@3 as page, arrow_cast(date_bin(Utf8("60 seconds"),base_table.time),Utf8("Timestamp(s)"))@4 as arrow_cast(date_bin(Utf8("60 seconds"),base_table.time),Utf8("Timestamp(s)"))], aggr=[__uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(base_table.shard_key)] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: partitioning=REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[env@7 as env, service_name@8 as service_name, city@9 as city, page@10 as page, CAST(date_bin(IntervalMonthDayNano { months: 0, days: 0, nanoseconds: 60000000000 }, time@6) AS Timestamp(Second, None)) as arrow_cast(date_bin(Utf8("60 seconds"),base_table.time),Utf8("Timestamp(s)"))], aggr=[__uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(base_table.shard_key)] REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[env@7 as env, service_name@8 as service_name, city@9 as city, page@10 as page, CAST(date_bin(IntervalMonthDayNano { months: 0, days: 0, nanoseconds: 60000000000 }, time@6) AS Timestamp(s)) as arrow_cast(date_bin(Utf8("60 seconds"),base_table.time),Utf8("Timestamp(s)"))], aggr=[__uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(base_table.shard_key)] REDACTED
|_|_|_ProjectionExec: expr=[CASE WHEN lcp@5 > 0 AND lcp@5 < 3000000 THEN lcp@5 END as __common_expr_1, CASE WHEN fmp@6 > 0 AND fmp@6 < 3000000 THEN fmp@6 END as __common_expr_2, CASE WHEN fcp@7 > 0 AND fcp@7 < 3000000 THEN fcp@7 END as __common_expr_3, CASE WHEN fp@8 > 0 AND fp@8 < 3000000 THEN fp@8 END as __common_expr_4, CASE WHEN tti@9 > 0 AND tti@9 < 3000000 THEN tti@9 END as __common_expr_5, CASE WHEN fid@10 > 0 AND fid@10 < 3000000 THEN fid@10 END as __common_expr_6, time@0 as time, env@1 as env, service_name@2 as service_name, city@3 as city, page@4 as page, shard_key@11 as shard_key] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_FilterExec: lcp@5 > 0 AND lcp@5 < 3000000 OR fmp@6 > 0 AND fmp@6 < 3000000 OR fcp@7 > 0 AND fcp@7 < 3000000 OR fp@8 > 0 AND fp@8 < 3000000 OR tti@9 > 0 AND tti@9 < 3000000 OR fid@10 > 0 AND fid@10 < 3000000 REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_UnorderedScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
| 1_| 7_|_AggregateExec: mode=FinalPartitioned, gby=[env@0 as env, service_name@1 as service_name, city@2 as city, page@3 as page, arrow_cast(date_bin(Utf8("60 seconds"),base_table.time),Utf8("Timestamp(s)"))@4 as arrow_cast(date_bin(Utf8("60 seconds"),base_table.time),Utf8("Timestamp(s)"))], aggr=[__uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(base_table.shard_key)] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: partitioning=REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[env@7 as env, service_name@8 as service_name, city@9 as city, page@10 as page, CAST(date_bin(IntervalMonthDayNano { months: 0, days: 0, nanoseconds: 60000000000 }, time@6) AS Timestamp(Second, None)) as arrow_cast(date_bin(Utf8("60 seconds"),base_table.time),Utf8("Timestamp(s)"))], aggr=[__uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(base_table.shard_key)] REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[env@7 as env, service_name@8 as service_name, city@9 as city, page@10 as page, CAST(date_bin(IntervalMonthDayNano { months: 0, days: 0, nanoseconds: 60000000000 }, time@6) AS Timestamp(s)) as arrow_cast(date_bin(Utf8("60 seconds"),base_table.time),Utf8("Timestamp(s)"))], aggr=[__uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(base_table.shard_key)] REDACTED
|_|_|_ProjectionExec: expr=[CASE WHEN lcp@5 > 0 AND lcp@5 < 3000000 THEN lcp@5 END as __common_expr_1, CASE WHEN fmp@6 > 0 AND fmp@6 < 3000000 THEN fmp@6 END as __common_expr_2, CASE WHEN fcp@7 > 0 AND fcp@7 < 3000000 THEN fcp@7 END as __common_expr_3, CASE WHEN fp@8 > 0 AND fp@8 < 3000000 THEN fp@8 END as __common_expr_4, CASE WHEN tti@9 > 0 AND tti@9 < 3000000 THEN tti@9 END as __common_expr_5, CASE WHEN fid@10 > 0 AND fid@10 < 3000000 THEN fid@10 END as __common_expr_6, time@0 as time, env@1 as env, service_name@2 as service_name, city@3 as city, page@4 as page, shard_key@11 as shard_key] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_FilterExec: lcp@5 > 0 AND lcp@5 < 3000000 OR fmp@6 > 0 AND fmp@6 < 3000000 OR fcp@7 > 0 AND fcp@7 < 3000000 OR fp@8 > 0 AND fp@8 < 3000000 OR tti@9 > 0 AND tti@9 < 3000000 OR fid@10 > 0 AND fid@10 < 3000000 REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_UnorderedScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
| 1_| 8_|_AggregateExec: mode=FinalPartitioned, gby=[env@0 as env, service_name@1 as service_name, city@2 as city, page@3 as page, arrow_cast(date_bin(Utf8("60 seconds"),base_table.time),Utf8("Timestamp(s)"))@4 as arrow_cast(date_bin(Utf8("60 seconds"),base_table.time),Utf8("Timestamp(s)"))], aggr=[__uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(base_table.shard_key)] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: partitioning=REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[env@7 as env, service_name@8 as service_name, city@9 as city, page@10 as page, CAST(date_bin(IntervalMonthDayNano { months: 0, days: 0, nanoseconds: 60000000000 }, time@6) AS Timestamp(Second, None)) as arrow_cast(date_bin(Utf8("60 seconds"),base_table.time),Utf8("Timestamp(s)"))], aggr=[__uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(base_table.shard_key)] REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[env@7 as env, service_name@8 as service_name, city@9 as city, page@10 as page, CAST(date_bin(IntervalMonthDayNano { months: 0, days: 0, nanoseconds: 60000000000 }, time@6) AS Timestamp(s)) as arrow_cast(date_bin(Utf8("60 seconds"),base_table.time),Utf8("Timestamp(s)"))], aggr=[__uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(base_table.shard_key)] REDACTED
|_|_|_ProjectionExec: expr=[CASE WHEN lcp@5 > 0 AND lcp@5 < 3000000 THEN lcp@5 END as __common_expr_1, CASE WHEN fmp@6 > 0 AND fmp@6 < 3000000 THEN fmp@6 END as __common_expr_2, CASE WHEN fcp@7 > 0 AND fcp@7 < 3000000 THEN fcp@7 END as __common_expr_3, CASE WHEN fp@8 > 0 AND fp@8 < 3000000 THEN fp@8 END as __common_expr_4, CASE WHEN tti@9 > 0 AND tti@9 < 3000000 THEN tti@9 END as __common_expr_5, CASE WHEN fid@10 > 0 AND fid@10 < 3000000 THEN fid@10 END as __common_expr_6, time@0 as time, env@1 as env, service_name@2 as service_name, city@3 as city, page@4 as page, shard_key@11 as shard_key] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_FilterExec: lcp@5 > 0 AND lcp@5 < 3000000 OR fmp@6 > 0 AND fmp@6 < 3000000 OR fcp@7 > 0 AND fcp@7 < 3000000 OR fp@8 > 0 AND fp@8 < 3000000 OR tti@9 > 0 AND tti@9 < 3000000 OR fid@10 > 0 AND fid@10 < 3000000 REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_UnorderedScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
| 1_| 9_|_AggregateExec: mode=FinalPartitioned, gby=[env@0 as env, service_name@1 as service_name, city@2 as city, page@3 as page, arrow_cast(date_bin(Utf8("60 seconds"),base_table.time),Utf8("Timestamp(s)"))@4 as arrow_cast(date_bin(Utf8("60 seconds"),base_table.time),Utf8("Timestamp(s)"))], aggr=[__uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(base_table.shard_key)] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: partitioning=REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[env@7 as env, service_name@8 as service_name, city@9 as city, page@10 as page, CAST(date_bin(IntervalMonthDayNano { months: 0, days: 0, nanoseconds: 60000000000 }, time@6) AS Timestamp(Second, None)) as arrow_cast(date_bin(Utf8("60 seconds"),base_table.time),Utf8("Timestamp(s)"))], aggr=[__uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(base_table.shard_key)] REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[env@7 as env, service_name@8 as service_name, city@9 as city, page@10 as page, CAST(date_bin(IntervalMonthDayNano { months: 0, days: 0, nanoseconds: 60000000000 }, time@6) AS Timestamp(s)) as arrow_cast(date_bin(Utf8("60 seconds"),base_table.time),Utf8("Timestamp(s)"))], aggr=[__uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(base_table.shard_key)] REDACTED
|_|_|_ProjectionExec: expr=[CASE WHEN lcp@5 > 0 AND lcp@5 < 3000000 THEN lcp@5 END as __common_expr_1, CASE WHEN fmp@6 > 0 AND fmp@6 < 3000000 THEN fmp@6 END as __common_expr_2, CASE WHEN fcp@7 > 0 AND fcp@7 < 3000000 THEN fcp@7 END as __common_expr_3, CASE WHEN fp@8 > 0 AND fp@8 < 3000000 THEN fp@8 END as __common_expr_4, CASE WHEN tti@9 > 0 AND tti@9 < 3000000 THEN tti@9 END as __common_expr_5, CASE WHEN fid@10 > 0 AND fid@10 < 3000000 THEN fid@10 END as __common_expr_6, time@0 as time, env@1 as env, service_name@2 as service_name, city@3 as city, page@4 as page, shard_key@11 as shard_key] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_FilterExec: lcp@5 > 0 AND lcp@5 < 3000000 OR fmp@6 > 0 AND fmp@6 < 3000000 OR fcp@7 > 0 AND fcp@7 < 3000000 OR fp@8 > 0 AND fp@8 < 3000000 OR tti@9 > 0 AND tti@9 < 3000000 OR fid@10 > 0 AND fid@10 < 3000000 REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_UnorderedScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
| 1_| 10_|_AggregateExec: mode=FinalPartitioned, gby=[env@0 as env, service_name@1 as service_name, city@2 as city, page@3 as page, arrow_cast(date_bin(Utf8("60 seconds"),base_table.time),Utf8("Timestamp(s)"))@4 as arrow_cast(date_bin(Utf8("60 seconds"),base_table.time),Utf8("Timestamp(s)"))], aggr=[__uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(base_table.shard_key)] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: partitioning=REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[env@7 as env, service_name@8 as service_name, city@9 as city, page@10 as page, CAST(date_bin(IntervalMonthDayNano { months: 0, days: 0, nanoseconds: 60000000000 }, time@6) AS Timestamp(Second, None)) as arrow_cast(date_bin(Utf8("60 seconds"),base_table.time),Utf8("Timestamp(s)"))], aggr=[__uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(base_table.shard_key)] REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[env@7 as env, service_name@8 as service_name, city@9 as city, page@10 as page, CAST(date_bin(IntervalMonthDayNano { months: 0, days: 0, nanoseconds: 60000000000 }, time@6) AS Timestamp(s)) as arrow_cast(date_bin(Utf8("60 seconds"),base_table.time),Utf8("Timestamp(s)"))], aggr=[__uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(base_table.shard_key)] REDACTED
|_|_|_ProjectionExec: expr=[CASE WHEN lcp@5 > 0 AND lcp@5 < 3000000 THEN lcp@5 END as __common_expr_1, CASE WHEN fmp@6 > 0 AND fmp@6 < 3000000 THEN fmp@6 END as __common_expr_2, CASE WHEN fcp@7 > 0 AND fcp@7 < 3000000 THEN fcp@7 END as __common_expr_3, CASE WHEN fp@8 > 0 AND fp@8 < 3000000 THEN fp@8 END as __common_expr_4, CASE WHEN tti@9 > 0 AND tti@9 < 3000000 THEN tti@9 END as __common_expr_5, CASE WHEN fid@10 > 0 AND fid@10 < 3000000 THEN fid@10 END as __common_expr_6, time@0 as time, env@1 as env, service_name@2 as service_name, city@3 as city, page@4 as page, shard_key@11 as shard_key] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_FilterExec: lcp@5 > 0 AND lcp@5 < 3000000 OR fmp@6 > 0 AND fmp@6 < 3000000 OR fcp@7 > 0 AND fcp@7 < 3000000 OR fp@8 > 0 AND fp@8 < 3000000 OR tti@9 > 0 AND tti@9 < 3000000 OR fid@10 > 0 AND fid@10 < 3000000 REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_UnorderedScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
| 1_| 11_|_AggregateExec: mode=FinalPartitioned, gby=[env@0 as env, service_name@1 as service_name, city@2 as city, page@3 as page, arrow_cast(date_bin(Utf8("60 seconds"),base_table.time),Utf8("Timestamp(s)"))@4 as arrow_cast(date_bin(Utf8("60 seconds"),base_table.time),Utf8("Timestamp(s)"))], aggr=[__uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(base_table.shard_key)] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: partitioning=REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[env@7 as env, service_name@8 as service_name, city@9 as city, page@10 as page, CAST(date_bin(IntervalMonthDayNano { months: 0, days: 0, nanoseconds: 60000000000 }, time@6) AS Timestamp(Second, None)) as arrow_cast(date_bin(Utf8("60 seconds"),base_table.time),Utf8("Timestamp(s)"))], aggr=[__uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(base_table.shard_key)] REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[env@7 as env, service_name@8 as service_name, city@9 as city, page@10 as page, CAST(date_bin(IntervalMonthDayNano { months: 0, days: 0, nanoseconds: 60000000000 }, time@6) AS Timestamp(s)) as arrow_cast(date_bin(Utf8("60 seconds"),base_table.time),Utf8("Timestamp(s)"))], aggr=[__uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(base_table.shard_key)] REDACTED
|_|_|_ProjectionExec: expr=[CASE WHEN lcp@5 > 0 AND lcp@5 < 3000000 THEN lcp@5 END as __common_expr_1, CASE WHEN fmp@6 > 0 AND fmp@6 < 3000000 THEN fmp@6 END as __common_expr_2, CASE WHEN fcp@7 > 0 AND fcp@7 < 3000000 THEN fcp@7 END as __common_expr_3, CASE WHEN fp@8 > 0 AND fp@8 < 3000000 THEN fp@8 END as __common_expr_4, CASE WHEN tti@9 > 0 AND tti@9 < 3000000 THEN tti@9 END as __common_expr_5, CASE WHEN fid@10 > 0 AND fid@10 < 3000000 THEN fid@10 END as __common_expr_6, time@0 as time, env@1 as env, service_name@2 as service_name, city@3 as city, page@4 as page, shard_key@11 as shard_key] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_FilterExec: lcp@5 > 0 AND lcp@5 < 3000000 OR fmp@6 > 0 AND fmp@6 < 3000000 OR fcp@7 > 0 AND fcp@7 < 3000000 OR fp@8 > 0 AND fp@8 < 3000000 OR tti@9 > 0 AND tti@9 < 3000000 OR fid@10 > 0 AND fid@10 < 3000000 REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_UnorderedScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
| 1_| 12_|_AggregateExec: mode=FinalPartitioned, gby=[env@0 as env, service_name@1 as service_name, city@2 as city, page@3 as page, arrow_cast(date_bin(Utf8("60 seconds"),base_table.time),Utf8("Timestamp(s)"))@4 as arrow_cast(date_bin(Utf8("60 seconds"),base_table.time),Utf8("Timestamp(s)"))], aggr=[__uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(base_table.shard_key)] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: partitioning=REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[env@7 as env, service_name@8 as service_name, city@9 as city, page@10 as page, CAST(date_bin(IntervalMonthDayNano { months: 0, days: 0, nanoseconds: 60000000000 }, time@6) AS Timestamp(Second, None)) as arrow_cast(date_bin(Utf8("60 seconds"),base_table.time),Utf8("Timestamp(s)"))], aggr=[__uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(base_table.shard_key)] REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[env@7 as env, service_name@8 as service_name, city@9 as city, page@10 as page, CAST(date_bin(IntervalMonthDayNano { months: 0, days: 0, nanoseconds: 60000000000 }, time@6) AS Timestamp(s)) as arrow_cast(date_bin(Utf8("60 seconds"),base_table.time),Utf8("Timestamp(s)"))], aggr=[__uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(base_table.shard_key)] REDACTED
|_|_|_ProjectionExec: expr=[CASE WHEN lcp@5 > 0 AND lcp@5 < 3000000 THEN lcp@5 END as __common_expr_1, CASE WHEN fmp@6 > 0 AND fmp@6 < 3000000 THEN fmp@6 END as __common_expr_2, CASE WHEN fcp@7 > 0 AND fcp@7 < 3000000 THEN fcp@7 END as __common_expr_3, CASE WHEN fp@8 > 0 AND fp@8 < 3000000 THEN fp@8 END as __common_expr_4, CASE WHEN tti@9 > 0 AND tti@9 < 3000000 THEN tti@9 END as __common_expr_5, CASE WHEN fid@10 > 0 AND fid@10 < 3000000 THEN fid@10 END as __common_expr_6, time@0 as time, env@1 as env, service_name@2 as service_name, city@3 as city, page@4 as page, shard_key@11 as shard_key] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_FilterExec: lcp@5 > 0 AND lcp@5 < 3000000 OR fmp@6 > 0 AND fmp@6 < 3000000 OR fcp@7 > 0 AND fcp@7 < 3000000 OR fp@8 > 0 AND fp@8 < 3000000 OR tti@9 > 0 AND tti@9 < 3000000 OR fid@10 > 0 AND fid@10 < 3000000 REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_UnorderedScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
| 1_| 13_|_AggregateExec: mode=FinalPartitioned, gby=[env@0 as env, service_name@1 as service_name, city@2 as city, page@3 as page, arrow_cast(date_bin(Utf8("60 seconds"),base_table.time),Utf8("Timestamp(s)"))@4 as arrow_cast(date_bin(Utf8("60 seconds"),base_table.time),Utf8("Timestamp(s)"))], aggr=[__uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(base_table.shard_key)] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: partitioning=REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[env@7 as env, service_name@8 as service_name, city@9 as city, page@10 as page, CAST(date_bin(IntervalMonthDayNano { months: 0, days: 0, nanoseconds: 60000000000 }, time@6) AS Timestamp(Second, None)) as arrow_cast(date_bin(Utf8("60 seconds"),base_table.time),Utf8("Timestamp(s)"))], aggr=[__uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(base_table.shard_key)] REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[env@7 as env, service_name@8 as service_name, city@9 as city, page@10 as page, CAST(date_bin(IntervalMonthDayNano { months: 0, days: 0, nanoseconds: 60000000000 }, time@6) AS Timestamp(s)) as arrow_cast(date_bin(Utf8("60 seconds"),base_table.time),Utf8("Timestamp(s)"))], aggr=[__uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(base_table.shard_key)] REDACTED
|_|_|_ProjectionExec: expr=[CASE WHEN lcp@5 > 0 AND lcp@5 < 3000000 THEN lcp@5 END as __common_expr_1, CASE WHEN fmp@6 > 0 AND fmp@6 < 3000000 THEN fmp@6 END as __common_expr_2, CASE WHEN fcp@7 > 0 AND fcp@7 < 3000000 THEN fcp@7 END as __common_expr_3, CASE WHEN fp@8 > 0 AND fp@8 < 3000000 THEN fp@8 END as __common_expr_4, CASE WHEN tti@9 > 0 AND tti@9 < 3000000 THEN tti@9 END as __common_expr_5, CASE WHEN fid@10 > 0 AND fid@10 < 3000000 THEN fid@10 END as __common_expr_6, time@0 as time, env@1 as env, service_name@2 as service_name, city@3 as city, page@4 as page, shard_key@11 as shard_key] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_FilterExec: lcp@5 > 0 AND lcp@5 < 3000000 OR fmp@6 > 0 AND fmp@6 < 3000000 OR fcp@7 > 0 AND fcp@7 < 3000000 OR fp@8 > 0 AND fp@8 < 3000000 OR tti@9 > 0 AND tti@9 < 3000000 OR fid@10 > 0 AND fid@10 < 3000000 REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_UnorderedScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
| 1_| 14_|_AggregateExec: mode=FinalPartitioned, gby=[env@0 as env, service_name@1 as service_name, city@2 as city, page@3 as page, arrow_cast(date_bin(Utf8("60 seconds"),base_table.time),Utf8("Timestamp(s)"))@4 as arrow_cast(date_bin(Utf8("60 seconds"),base_table.time),Utf8("Timestamp(s)"))], aggr=[__uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(base_table.shard_key)] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: partitioning=REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[env@7 as env, service_name@8 as service_name, city@9 as city, page@10 as page, CAST(date_bin(IntervalMonthDayNano { months: 0, days: 0, nanoseconds: 60000000000 }, time@6) AS Timestamp(Second, None)) as arrow_cast(date_bin(Utf8("60 seconds"),base_table.time),Utf8("Timestamp(s)"))], aggr=[__uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(base_table.shard_key)] REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[env@7 as env, service_name@8 as service_name, city@9 as city, page@10 as page, CAST(date_bin(IntervalMonthDayNano { months: 0, days: 0, nanoseconds: 60000000000 }, time@6) AS Timestamp(s)) as arrow_cast(date_bin(Utf8("60 seconds"),base_table.time),Utf8("Timestamp(s)"))], aggr=[__uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(base_table.shard_key)] REDACTED
|_|_|_ProjectionExec: expr=[CASE WHEN lcp@5 > 0 AND lcp@5 < 3000000 THEN lcp@5 END as __common_expr_1, CASE WHEN fmp@6 > 0 AND fmp@6 < 3000000 THEN fmp@6 END as __common_expr_2, CASE WHEN fcp@7 > 0 AND fcp@7 < 3000000 THEN fcp@7 END as __common_expr_3, CASE WHEN fp@8 > 0 AND fp@8 < 3000000 THEN fp@8 END as __common_expr_4, CASE WHEN tti@9 > 0 AND tti@9 < 3000000 THEN tti@9 END as __common_expr_5, CASE WHEN fid@10 > 0 AND fid@10 < 3000000 THEN fid@10 END as __common_expr_6, time@0 as time, env@1 as env, service_name@2 as service_name, city@3 as city, page@4 as page, shard_key@11 as shard_key] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_FilterExec: lcp@5 > 0 AND lcp@5 < 3000000 OR fmp@6 > 0 AND fmp@6 < 3000000 OR fcp@7 > 0 AND fcp@7 < 3000000 OR fp@8 > 0 AND fp@8 < 3000000 OR tti@9 > 0 AND tti@9 < 3000000 OR fid@10 > 0 AND fid@10 < 3000000 REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_UnorderedScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
| 1_| 15_|_AggregateExec: mode=FinalPartitioned, gby=[env@0 as env, service_name@1 as service_name, city@2 as city, page@3 as page, arrow_cast(date_bin(Utf8("60 seconds"),base_table.time),Utf8("Timestamp(s)"))@4 as arrow_cast(date_bin(Utf8("60 seconds"),base_table.time),Utf8("Timestamp(s)"))], aggr=[__uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(base_table.shard_key)] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: partitioning=REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[env@7 as env, service_name@8 as service_name, city@9 as city, page@10 as page, CAST(date_bin(IntervalMonthDayNano { months: 0, days: 0, nanoseconds: 60000000000 }, time@6) AS Timestamp(Second, None)) as arrow_cast(date_bin(Utf8("60 seconds"),base_table.time),Utf8("Timestamp(s)"))], aggr=[__uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(base_table.shard_key)] REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[env@7 as env, service_name@8 as service_name, city@9 as city, page@10 as page, CAST(date_bin(IntervalMonthDayNano { months: 0, days: 0, nanoseconds: 60000000000 }, time@6) AS Timestamp(s)) as arrow_cast(date_bin(Utf8("60 seconds"),base_table.time),Utf8("Timestamp(s)"))], aggr=[__uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.lcp > Int64(0) AND base_table.lcp < Int64(3000000) THEN base_table.lcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fmp > Int64(0) AND base_table.fmp < Int64(3000000) THEN base_table.fmp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fcp > Int64(0) AND base_table.fcp < Int64(3000000) THEN base_table.fcp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fp > Int64(0) AND base_table.fp < Int64(3000000) THEN base_table.fp ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.tti > Int64(0) AND base_table.tti < Int64(3000000) THEN base_table.tti ELSE Int64(NULL) END), __uddsketch_state_state(Int64(128),Float64(0.01),CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __min_state(CASE WHEN base_table.fid > Int64(0) AND base_table.fid < Int64(3000000) THEN base_table.fid ELSE Int64(NULL) END), __max_state(base_table.shard_key)] REDACTED
|_|_|_ProjectionExec: expr=[CASE WHEN lcp@5 > 0 AND lcp@5 < 3000000 THEN lcp@5 END as __common_expr_1, CASE WHEN fmp@6 > 0 AND fmp@6 < 3000000 THEN fmp@6 END as __common_expr_2, CASE WHEN fcp@7 > 0 AND fcp@7 < 3000000 THEN fcp@7 END as __common_expr_3, CASE WHEN fp@8 > 0 AND fp@8 < 3000000 THEN fp@8 END as __common_expr_4, CASE WHEN tti@9 > 0 AND tti@9 < 3000000 THEN tti@9 END as __common_expr_5, CASE WHEN fid@10 > 0 AND fid@10 < 3000000 THEN fid@10 END as __common_expr_6, time@0 as time, env@1 as env, service_name@2 as service_name, city@3 as city, page@4 as page, shard_key@11 as shard_key] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_FilterExec: lcp@5 > 0 AND lcp@5 < 3000000 OR fmp@6 > 0 AND fmp@6 < 3000000 OR fcp@7 > 0 AND fcp@7 < 3000000 OR fp@8 > 0 AND fp@8 < 3000000 OR tti@9 > 0 AND tti@9 < 3000000 OR fid@10 > 0 AND fid@10 < 3000000 REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_UnorderedScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
|_|_| Total rows: 0_|
@@ -655,7 +603,6 @@ where
|_|_AggregateExec: mode=Final, gby=[], aggr=[count(Int64(1))]_|
|_|_CoalescePartitionsExec_|
|_|_AggregateExec: mode=Partial, gby=[], aggr=[count(Int64(1))]_|
|_|_CooperativeExec_|
|_|_MergeScanExec: REDACTED
|_|_|
+-+-+
@@ -684,103 +631,86 @@ where
|_|_|_AggregateExec: mode=Final, gby=[], aggr=[count(Int64(1))] REDACTED
|_|_|_CoalescePartitionsExec REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[], aggr=[count(Int64(1))] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_MergeScanExec: REDACTED
|_|_|_|
| 1_| 0_|_AggregateExec: mode=Final, gby=[], aggr=[__count_state(base_table.time)] REDACTED
|_|_|_CoalescePartitionsExec REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[], aggr=[__count_state(base_table.time)] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_UnorderedScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
| 1_| 1_|_AggregateExec: mode=Final, gby=[], aggr=[__count_state(base_table.time)] REDACTED
|_|_|_CoalescePartitionsExec REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[], aggr=[__count_state(base_table.time)] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_UnorderedScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
| 1_| 2_|_AggregateExec: mode=Final, gby=[], aggr=[__count_state(base_table.time)] REDACTED
|_|_|_CoalescePartitionsExec REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[], aggr=[__count_state(base_table.time)] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_UnorderedScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
| 1_| 3_|_AggregateExec: mode=Final, gby=[], aggr=[__count_state(base_table.time)] REDACTED
|_|_|_CoalescePartitionsExec REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[], aggr=[__count_state(base_table.time)] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_UnorderedScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
| 1_| 4_|_AggregateExec: mode=Final, gby=[], aggr=[__count_state(base_table.time)] REDACTED
|_|_|_CoalescePartitionsExec REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[], aggr=[__count_state(base_table.time)] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_UnorderedScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
| 1_| 5_|_AggregateExec: mode=Final, gby=[], aggr=[__count_state(base_table.time)] REDACTED
|_|_|_CoalescePartitionsExec REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[], aggr=[__count_state(base_table.time)] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_UnorderedScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
| 1_| 6_|_AggregateExec: mode=Final, gby=[], aggr=[__count_state(base_table.time)] REDACTED
|_|_|_CoalescePartitionsExec REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[], aggr=[__count_state(base_table.time)] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_UnorderedScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
| 1_| 7_|_AggregateExec: mode=Final, gby=[], aggr=[__count_state(base_table.time)] REDACTED
|_|_|_CoalescePartitionsExec REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[], aggr=[__count_state(base_table.time)] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_UnorderedScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
| 1_| 8_|_AggregateExec: mode=Final, gby=[], aggr=[__count_state(base_table.time)] REDACTED
|_|_|_CoalescePartitionsExec REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[], aggr=[__count_state(base_table.time)] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_UnorderedScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
| 1_| 9_|_AggregateExec: mode=Final, gby=[], aggr=[__count_state(base_table.time)] REDACTED
|_|_|_CoalescePartitionsExec REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[], aggr=[__count_state(base_table.time)] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_UnorderedScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
| 1_| 10_|_AggregateExec: mode=Final, gby=[], aggr=[__count_state(base_table.time)] REDACTED
|_|_|_CoalescePartitionsExec REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[], aggr=[__count_state(base_table.time)] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_UnorderedScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
| 1_| 11_|_AggregateExec: mode=Final, gby=[], aggr=[__count_state(base_table.time)] REDACTED
|_|_|_CoalescePartitionsExec REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[], aggr=[__count_state(base_table.time)] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_UnorderedScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
| 1_| 12_|_AggregateExec: mode=Final, gby=[], aggr=[__count_state(base_table.time)] REDACTED
|_|_|_CoalescePartitionsExec REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[], aggr=[__count_state(base_table.time)] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_UnorderedScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
| 1_| 13_|_AggregateExec: mode=Final, gby=[], aggr=[__count_state(base_table.time)] REDACTED
|_|_|_CoalescePartitionsExec REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[], aggr=[__count_state(base_table.time)] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_UnorderedScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
| 1_| 14_|_AggregateExec: mode=Final, gby=[], aggr=[__count_state(base_table.time)] REDACTED
|_|_|_CoalescePartitionsExec REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[], aggr=[__count_state(base_table.time)] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_UnorderedScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
| 1_| 15_|_AggregateExec: mode=Final, gby=[], aggr=[__count_state(base_table.time)] REDACTED
|_|_|_CoalescePartitionsExec REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[], aggr=[__count_state(base_table.time)] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_UnorderedScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
|_|_| Total rows: 1_|

37
tests/cases/distributed/explain/subqueries.result
View File

@@ -24,15 +24,10 @@ EXPLAIN SELECT * FROM integers WHERE i IN ((SELECT i FROM integers)) ORDER BY i;
|_| ]]_|
| physical_plan | SortPreservingMergeExec: [i@0 ASC NULLS LAST]_|
|_|_SortExec: expr=[i@0 ASC NULLS LAST], preserve_partitioning=[true]_|
|_|_CoalesceBatchesExec: target_batch_size=8192_|
|_|_REDACTED
|_|_CoalesceBatchesExec: target_batch_size=8192_|
|_|_RepartitionExec: partitioning=REDACTED
|_|_CooperativeExec_|
|_|_MergeScanExec: REDACTED
|_|_CoalesceBatchesExec: target_batch_size=8192_|
|_|_RepartitionExec: partitioning=REDACTED
|_|_CooperativeExec_|
|_|_MergeScanExec: REDACTED
|_|_|
+-+-+
@@ -60,16 +55,11 @@ EXPLAIN SELECT * FROM integers i1 WHERE EXISTS(SELECT i FROM integers WHERE i=i1
|_| ]]_|
| physical_plan | SortPreservingMergeExec: [i@0 ASC NULLS LAST]_|
|_|_SortExec: expr=[i@0 ASC NULLS LAST], preserve_partitioning=[true]_|
|_|_CoalesceBatchesExec: target_batch_size=8192_|
|_|_REDACTED
|_|_CoalesceBatchesExec: target_batch_size=8192_|
|_|_RepartitionExec: partitioning=REDACTED
|_|_CooperativeExec_|
|_|_MergeScanExec: REDACTED
|_|_CoalesceBatchesExec: target_batch_size=8192_|
|_|_RepartitionExec: partitioning=REDACTED
|_|_ProjectionExec: expr=[i@0 as i]_|
|_|_CooperativeExec_|
|_|_MergeScanExec: REDACTED
|_|_|
+-+-+
@@ -109,13 +99,10 @@ order by t.i desc;
|_|_SortExec: expr=[i@0 DESC], preserve_partitioning=[true]_|
|_|_CrossJoinExec_|
|_|_CoalescePartitionsExec_|
|_|_CoalesceBatchesExec: target_batch_size=8192_|
|_|_FilterExec: i@0 IS NOT NULL_|
|_|_ProjectionExec: expr=[i@0 as i]_|
|_|_CooperativeExec_|
|_|_MergeScanExec: REDACTED
|_|_ProjectionExec: expr=[]_|
|_|_CooperativeExec_|
|_|_MergeScanExec: REDACTED
|_|_|
+-+-+
@@ -187,12 +174,9 @@ EXPLAIN SELECT * FROM integers i1 WHERE EXISTS(SELECT i FROM integers WHERE i=i1
|_| ]]_|
| physical_plan | SortPreservingMergeExec: [i@0 ASC NULLS LAST]_|
|_|_SortExec: expr=[i@0 ASC NULLS LAST], preserve_partitioning=[true]_|
|_|_CoalesceBatchesExec: target_batch_size=8192_|
|_|_REDACTED
|_|_CooperativeExec_|
|_|_MergeScanExec: REDACTED
|_|_ProjectionExec: expr=[i@0 as i]_|
|_|_CooperativeExec_|
|_|_MergeScanExec: REDACTED
|_|_|
+-+-+
@@ -221,13 +205,10 @@ EXPLAIN SELECT * FROM integers i1 WHERE EXISTS(SELECT count(i) FROM integers WHE
|_| ]]_|
| physical_plan | SortPreservingMergeExec: [i@0 ASC NULLS LAST]_|
|_|_SortExec: expr=[i@0 ASC NULLS LAST], preserve_partitioning=[true]_|
|_|_CoalesceBatchesExec: target_batch_size=8192_|
|_|_REDACTED
|_|_CooperativeExec_|
|_|_MergeScanExec: REDACTED
|_|_AggregateExec: mode=SinglePartitioned, gby=[i@0 as i], aggr=[]_|
|_|_ProjectionExec: expr=[i@0 as i]_|
|_|_CooperativeExec_|
|_|_MergeScanExec: REDACTED
|_|_|
+-+-+
@@ -302,8 +283,6 @@ EXPLAIN SELECT x FROM (SELECT a AS x FROM t) sq ORDER BY x;
|_|_TableScan: t_|
|_| ]]_|
| physical_plan | SortPreservingMergeExec: [x@0 ASC NULLS LAST]_|
|_|_CooperativeExec_|
|_|_CooperativeExec_|
|_|_MergeScanExec: REDACTED
|_|_|
+-+-+
@@ -343,8 +322,6 @@ EXPLAIN SELECT x, COUNT(*) AS c FROM (SELECT a AS x FROM t) sq GROUP BY x ORDER
|_|_TableScan: t_|
|_| ]]_|
| physical_plan | SortPreservingMergeExec: [x@0 ASC NULLS LAST]_|
|_|_CooperativeExec_|
|_|_CooperativeExec_|
|_|_MergeScanExec: REDACTED
|_|_|
+-+-+
@@ -382,7 +359,6 @@ EXPLAIN SELECT DISTINCT x FROM (SELECT a AS x FROM t) sq ORDER BY x;
| physical_plan | SortPreservingMergeExec: [x@0 ASC NULLS LAST]_|
|_|_SortExec: expr=[x@0 ASC NULLS LAST], preserve_partitioning=[true]_|
|_|_AggregateExec: mode=SinglePartitioned, gby=[x@0 as x], aggr=[]_|
|_|_CooperativeExec_|
|_|_MergeScanExec: REDACTED
|_|_|
+-+-+
@@ -417,8 +393,6 @@ EXPLAIN SELECT sq.x FROM (SELECT a AS x FROM t) sq ORDER BY sq.x;
|_|_TableScan: t_|
|_| ]]_|
| physical_plan | SortPreservingMergeExec: [x@0 ASC NULLS LAST]_|
|_|_CooperativeExec_|
|_|_CooperativeExec_|
|_|_MergeScanExec: REDACTED
|_|_|
+-+-+
@@ -455,8 +429,6 @@ EXPLAIN SELECT y FROM (SELECT x AS y FROM (SELECT a AS x FROM t) sq1) sq2 ORDER
|_|_TableScan: t_|
|_| ]]_|
| physical_plan | SortPreservingMergeExec: [y@0 ASC NULLS LAST]_|
|_|_CooperativeExec_|
|_|_CooperativeExec_|
|_|_MergeScanExec: REDACTED
|_|_|
+-+-+
@@ -495,8 +467,6 @@ EXPLAIN SELECT x, x + 1 AS y FROM (SELECT a AS x FROM t) sq ORDER BY x;
|_|_TableScan: t_|
|_| ]]_|
| physical_plan | SortPreservingMergeExec: [x@0 ASC NULLS LAST]_|
|_|_CooperativeExec_|
|_|_CooperativeExec_|
|_|_MergeScanExec: REDACTED
|_|_|
+-+-+
@@ -537,9 +507,7 @@ EXPLAIN SELECT a FROM ((SELECT a FROM t1) UNION ALL (SELECT a FROM t2)) u ORDER
| physical_plan | SortPreservingMergeExec: [a@0 ASC NULLS LAST]_|
|_|_SortExec: expr=[a@0 ASC NULLS LAST], preserve_partitioning=[true]_|
|_|_InterleaveExec_|
|_|_CooperativeExec_|
|_|_MergeScanExec: REDACTED
|_|_CooperativeExec_|
|_|_MergeScanExec: REDACTED
|_|_|
+-+-+
@@ -584,11 +552,8 @@ ORDER BY u1.a;
|_| ]]_|
| physical_plan | SortPreservingMergeExec: [a@0 ASC NULLS LAST]_|
|_|_SortExec: expr=[a@0 ASC NULLS LAST], preserve_partitioning=[true]_|
|_|_CoalesceBatchesExec: target_batch_size=8192_|
|_|_REDACTED
|_|_CooperativeExec_|
|_|_MergeScanExec: REDACTED
|_|_CooperativeExec_|
|_|_MergeScanExec: REDACTED
|_|_|
+-+-+
@@ -654,9 +619,7 @@ EXPLAIN SELECT x FROM (SELECT a AS x FROM t) sq ORDER BY x LIMIT 2;
|_|_TableScan: t_|
|_| ]]_|
| physical_plan | SortPreservingMergeExec: [x@0 ASC NULLS LAST], fetch=2_|
|_|_CooperativeExec_|
|_|_SortExec: TopK(fetch=2), expr=[x@0 ASC NULLS LAST], preserve_partitioning=[true]_|
|_|_CooperativeExec_|
|_|_MergeScanExec: REDACTED
|_|_|
+-+-+

6
tests/cases/distributed/flow-tql/tsid_on_phy.result
View File

@@ -121,10 +121,8 @@ TQL EXPLAIN (
| | ]] |
| physical_plan | HistogramFoldExec: le=@0, field=@4, quantile=0.5 |
| | SortExec: expr=[tag4@1 ASC NULLS LAST, tag5@2 ASC NULLS LAST, ts@3 ASC NULLS LAST, CAST(le@0 AS Float64) ASC NULLS LAST], preserve_partitioning=[true] |
| | CoalesceBatchesExec: target_batch_size=8192 |
| | RepartitionExec: REDACTED
| | CooperativeExec |
| | MergeScanExec: REDACTED
| | RepartitionExec: REDACTED
| | MergeScanExec: REDACTED
| | |
+---------------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+

17
tests/cases/distributed/optimizer/count.result
View File

@@ -139,7 +139,6 @@ select count(1) from count_where_bug where `tag` = 'b';
|_|_|_AggregateExec: mode=Final, gby=[], aggr=[count(count_where_bug.ts)] REDACTED
|_|_|_CoalescePartitionsExec REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[], aggr=[count(count_where_bug.ts)] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_UnorderedScan: region=REDACTED, "partition_count":{"count":1, "mem_ranges":1, "files":0, "file_ranges":0} REDACTED
|_|_|_|
|_|_| Total rows: 1_|
@@ -182,7 +181,6 @@ select count(1) from count_where_bug where ts > '2024-09-06T06:00:04Z';
|_|_|_AggregateExec: mode=Final, gby=[], aggr=[count(count_where_bug.ts)] REDACTED
|_|_|_CoalescePartitionsExec REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[], aggr=[count(count_where_bug.ts)] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_UnorderedScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
|_|_| Total rows: 1_|
@@ -223,9 +221,7 @@ select count(1) from count_where_bug where num != 3;
|_|_|_AggregateExec: mode=Final, gby=[], aggr=[count(count_where_bug.ts)] REDACTED
|_|_|_CoalescePartitionsExec REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[], aggr=[count(count_where_bug.ts)] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_FilterExec: num@1 != 3, projection=[ts@0] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_UnorderedScan: region=REDACTED, "partition_count":{"count":1, "mem_ranges":1, "files":0, "file_ranges":0} REDACTED
|_|_|_|
|_|_| Total rows: 1_|
@@ -285,7 +281,6 @@ select count(1) from count_where_bug;
| 0_| 0_|_AggregateExec: mode=Final, gby=[], aggr=[count(Int64(1))] REDACTED
|_|_|_CoalescePartitionsExec REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[], aggr=[count(Int64(1))] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_MergeScanExec: REDACTED
|_|_|_|
| 1_| 0_|_ProjectionExec: expr=[{count[count]:REDACTED} as __count_state(count_where_bug.ts)] REDACTED
@@ -321,13 +316,11 @@ select count(1) from count_where_bug where `tag` = 'b';
| 0_| 0_|_AggregateExec: mode=Final, gby=[], aggr=[count(Int64(1))] REDACTED
|_|_|_CoalescePartitionsExec REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[], aggr=[count(Int64(1))] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_MergeScanExec: REDACTED
|_|_|_|
| 1_| 0_|_AggregateExec: mode=Final, gby=[], aggr=[__count_state(count_where_bug.ts)] REDACTED
|_|_|_CoalescePartitionsExec REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[], aggr=[__count_state(count_where_bug.ts)] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_UnorderedScan: region=REDACTED, "partition_count":{"count":1, "mem_ranges":1, "files":0, "file_ranges":0} REDACTED
|_|_|_|
|_|_| Total rows: 1_|
@@ -349,13 +342,11 @@ select count(1) from count_where_bug where `tag` = 'b';
| 0_| 0_|_AggregateExec: mode=Final, gby=[], aggr=[count(Int64(1))] REDACTED
|_|_|_CoalescePartitionsExec REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[], aggr=[count(Int64(1))] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_MergeScanExec: REDACTED
|_|_|_|
| 1_| 0_|_AggregateExec: mode=Final, gby=[], aggr=[__count_state(count_where_bug.ts)] REDACTED
|_|_|_CoalescePartitionsExec REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[], aggr=[__count_state(count_where_bug.ts)] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_UnorderedScan: region=REDACTED, "partition_count":{"count":1, "mem_ranges":1, "files":0, "file_ranges":0} REDACTED
|_|_|_|
|_|_| Total rows: 1_|
@@ -387,19 +378,16 @@ select count(1) from count_where_bug where ts > '2024-09-06T06:00:04Z';
| 0_| 0_|_AggregateExec: mode=Final, gby=[], aggr=[count(Int64(1))] REDACTED
|_|_|_CoalescePartitionsExec REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[], aggr=[count(Int64(1))] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_MergeScanExec: REDACTED
|_|_|_|
| 1_| 0_|_AggregateExec: mode=Final, gby=[], aggr=[__count_state(count_where_bug.ts)] REDACTED
|_|_|_CoalescePartitionsExec REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[], aggr=[__count_state(count_where_bug.ts)] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_UnorderedScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
| 1_| 1_|_AggregateExec: mode=Final, gby=[], aggr=[__count_state(count_where_bug.ts)] REDACTED
|_|_|_CoalescePartitionsExec REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[], aggr=[__count_state(count_where_bug.ts)] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_UnorderedScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
|_|_| Total rows: 1_|
@@ -429,23 +417,18 @@ select count(1) from count_where_bug where num != 3;
| 0_| 0_|_AggregateExec: mode=Final, gby=[], aggr=[count(Int64(1))] REDACTED
|_|_|_CoalescePartitionsExec REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[], aggr=[count(Int64(1))] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_MergeScanExec: REDACTED
|_|_|_|
| 1_| 0_|_AggregateExec: mode=Final, gby=[], aggr=[__count_state(count_where_bug.ts)] REDACTED
|_|_|_CoalescePartitionsExec REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[], aggr=[__count_state(count_where_bug.ts)] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_FilterExec: num@1 != 3, projection=[ts@0] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_UnorderedScan: region=REDACTED, "partition_count":{"count":1, "mem_ranges":1, "files":0, "file_ranges":0} REDACTED
|_|_|_|
| 1_| 1_|_AggregateExec: mode=Final, gby=[], aggr=[__count_state(count_where_bug.ts)] REDACTED
|_|_|_CoalescePartitionsExec REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[], aggr=[__count_state(count_where_bug.ts)] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_FilterExec: num@1 != 3, projection=[ts@0] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_UnorderedScan: region=REDACTED, "partition_count":{"count":1, "mem_ranges":1, "files":0, "file_ranges":0} REDACTED
|_|_|_|
|_|_| Total rows: 1_|

1
tests/cases/distributed/optimizer/filter_push_down.result
View File

@@ -110,7 +110,6 @@ SELECT * FROM integers WHERE i NOT IN ((SELECT i FROM integers WHERE i=1)) ORDER
+---+-------------------------+
| 2 | 1970-01-01T00:00:00.002 |
| 3 | 1970-01-01T00:00:00.003 |
| | 1970-01-01T00:00:00.004 |
+---+-------------------------+
SELECT * FROM integers WHERE i IN ((SELECT i FROM integers)) AND i<3 ORDER BY i;

53
tests/cases/distributed/optimizer/first_value_advance.result
View File

@@ -111,10 +111,8 @@ explain analyze
|_|_|_|
| 1_| 0_|_ProjectionExec: expr=[first_value(t.host) ORDER BY [t.ts ASC NULLS LAST]@1 as first_value(t.host) ORDER BY [t.ts ASC NULLS LAST], first_value(t.not_pk) ORDER BY [t.ts ASC NULLS LAST]@2 as first_value(t.not_pk) ORDER BY [t.ts ASC NULLS LAST], first_value(t.val) ORDER BY [t.ts ASC NULLS LAST]@3 as first_value(t.val) ORDER BY [t.ts ASC NULLS LAST]] REDACTED
|_|_|_AggregateExec: mode=FinalPartitioned, gby=[host@0 as host], aggr=[first_value(t.host) ORDER BY [t.ts ASC NULLS LAST], first_value(t.not_pk) ORDER BY [t.ts ASC NULLS LAST], first_value(t.val) ORDER BY [t.ts ASC NULLS LAST]] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[host@1 as host], aggr=[first_value(t.host) ORDER BY [t.ts ASC NULLS LAST], first_value(t.not_pk) ORDER BY [t.ts ASC NULLS LAST], first_value(t.val) ORDER BY [t.ts ASC NULLS LAST]] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_UnorderedScan: region=REDACTED, "partition_count":{"count":1, "mem_ranges":0, "files":1, "file_ranges":1} REDACTED
|_|_|_|
|_|_| Total rows: 4_|
@@ -167,7 +165,6 @@ explain analyze
| 1_| 0_|_AggregateExec: mode=Final, gby=[], aggr=[first_value(t.ts) ORDER BY [t.ts ASC NULLS LAST]] REDACTED
|_|_|_CoalescePartitionsExec REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[], aggr=[first_value(t.ts) ORDER BY [t.ts ASC NULLS LAST]] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_UnorderedScan: region=REDACTED, "partition_count":{"count":1, "mem_ranges":0, "files":1, "file_ranges":1} REDACTED
|_|_|_|
|_|_| Total rows: 1_|
@@ -244,8 +241,6 @@ order by ordered_host;
|_|_TableScan: t_|
|_| ]]_|
| physical_plan | SortPreservingMergeExec: [ordered_host@0 ASC NULLS LAST]_|
|_|_CooperativeExec_|
|_|_CooperativeExec_|
|_|_MergeScanExec: REDACTED
|_|_|
+-+-+
@@ -273,8 +268,6 @@ order by ordered_host;
| stage | node | plan_|
+-+-+-+
| 0_| 0_|_SortPreservingMergeExec: [ordered_host@0 ASC NULLS LAST] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_MergeScanExec: REDACTED
|_|_|_|
| 1_| 0_|_ProjectionExec: expr=[first_value(t.host) ORDER BY [t.ts ASC NULLS LAST]@0 as ordered_host, first_value(t.not_pk) ORDER BY [t.ts ASC NULLS LAST]@1 as first_value(t.not_pk) ORDER BY [t.ts ASC NULLS LAST], first_value(t.val) ORDER BY [t.ts ASC NULLS LAST]@2 as first_value(t.val) ORDER BY [t.ts ASC NULLS LAST]] REDACTED
@@ -282,10 +275,8 @@ order by ordered_host;
|_|_|_SortExec: expr=[first_value(t.host) ORDER BY [t.ts ASC NULLS LAST]@0 ASC NULLS LAST], preserve_REDACTED
|_|_|_ProjectionExec: expr=[first_value(t.host) ORDER BY [t.ts ASC NULLS LAST]@1 as first_value(t.host) ORDER BY [t.ts ASC NULLS LAST], first_value(t.not_pk) ORDER BY [t.ts ASC NULLS LAST]@2 as first_value(t.not_pk) ORDER BY [t.ts ASC NULLS LAST], first_value(t.val) ORDER BY [t.ts ASC NULLS LAST]@3 as first_value(t.val) ORDER BY [t.ts ASC NULLS LAST]] REDACTED
|_|_|_AggregateExec: mode=FinalPartitioned, gby=[host@0 as host], aggr=[first_value(t.host) ORDER BY [t.ts ASC NULLS LAST], first_value(t.not_pk) ORDER BY [t.ts ASC NULLS LAST], first_value(t.val) ORDER BY [t.ts ASC NULLS LAST]] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[host@1 as host], aggr=[first_value(t.host) ORDER BY [t.ts ASC NULLS LAST], first_value(t.not_pk) ORDER BY [t.ts ASC NULLS LAST], first_value(t.val) ORDER BY [t.ts ASC NULLS LAST]] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
| 1_| 1_|_ProjectionExec: expr=[first_value(t.host) ORDER BY [t.ts ASC NULLS LAST]@0 as ordered_host, first_value(t.not_pk) ORDER BY [t.ts ASC NULLS LAST]@1 as first_value(t.not_pk) ORDER BY [t.ts ASC NULLS LAST], first_value(t.val) ORDER BY [t.ts ASC NULLS LAST]@2 as first_value(t.val) ORDER BY [t.ts ASC NULLS LAST]] REDACTED
@@ -293,10 +284,8 @@ order by ordered_host;
|_|_|_SortExec: expr=[first_value(t.host) ORDER BY [t.ts ASC NULLS LAST]@0 ASC NULLS LAST], preserve_REDACTED
|_|_|_ProjectionExec: expr=[first_value(t.host) ORDER BY [t.ts ASC NULLS LAST]@1 as first_value(t.host) ORDER BY [t.ts ASC NULLS LAST], first_value(t.not_pk) ORDER BY [t.ts ASC NULLS LAST]@2 as first_value(t.not_pk) ORDER BY [t.ts ASC NULLS LAST], first_value(t.val) ORDER BY [t.ts ASC NULLS LAST]@3 as first_value(t.val) ORDER BY [t.ts ASC NULLS LAST]] REDACTED
|_|_|_AggregateExec: mode=FinalPartitioned, gby=[host@0 as host], aggr=[first_value(t.host) ORDER BY [t.ts ASC NULLS LAST], first_value(t.not_pk) ORDER BY [t.ts ASC NULLS LAST], first_value(t.val) ORDER BY [t.ts ASC NULLS LAST]] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[host@1 as host], aggr=[first_value(t.host) ORDER BY [t.ts ASC NULLS LAST], first_value(t.not_pk) ORDER BY [t.ts ASC NULLS LAST], first_value(t.val) ORDER BY [t.ts ASC NULLS LAST]] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
| 1_| 2_|_ProjectionExec: expr=[first_value(t.host) ORDER BY [t.ts ASC NULLS LAST]@0 as ordered_host, first_value(t.not_pk) ORDER BY [t.ts ASC NULLS LAST]@1 as first_value(t.not_pk) ORDER BY [t.ts ASC NULLS LAST], first_value(t.val) ORDER BY [t.ts ASC NULLS LAST]@2 as first_value(t.val) ORDER BY [t.ts ASC NULLS LAST]] REDACTED
@@ -304,10 +293,8 @@ order by ordered_host;
|_|_|_SortExec: expr=[first_value(t.host) ORDER BY [t.ts ASC NULLS LAST]@0 ASC NULLS LAST], preserve_REDACTED
|_|_|_ProjectionExec: expr=[first_value(t.host) ORDER BY [t.ts ASC NULLS LAST]@1 as first_value(t.host) ORDER BY [t.ts ASC NULLS LAST], first_value(t.not_pk) ORDER BY [t.ts ASC NULLS LAST]@2 as first_value(t.not_pk) ORDER BY [t.ts ASC NULLS LAST], first_value(t.val) ORDER BY [t.ts ASC NULLS LAST]@3 as first_value(t.val) ORDER BY [t.ts ASC NULLS LAST]] REDACTED
|_|_|_AggregateExec: mode=FinalPartitioned, gby=[host@0 as host], aggr=[first_value(t.host) ORDER BY [t.ts ASC NULLS LAST], first_value(t.not_pk) ORDER BY [t.ts ASC NULLS LAST], first_value(t.val) ORDER BY [t.ts ASC NULLS LAST]] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[host@1 as host], aggr=[first_value(t.host) ORDER BY [t.ts ASC NULLS LAST], first_value(t.not_pk) ORDER BY [t.ts ASC NULLS LAST], first_value(t.val) ORDER BY [t.ts ASC NULLS LAST]] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
|_|_| Total rows: 4_|
@@ -338,7 +325,6 @@ explain select first_value(ts order by ts) from t;
| physical_plan | AggregateExec: mode=Final, gby=[], aggr=[first_value(t.ts) ORDER BY [t.ts ASC NULLS LAST]]_|
|_|_CoalescePartitionsExec_|
|_|_AggregateExec: mode=Partial, gby=[], aggr=[first_value(t.ts) ORDER BY [t.ts ASC NULLS LAST]]_|
|_|_CooperativeExec_|
|_|_MergeScanExec: REDACTED
|_|_|
+-+-+
@@ -362,25 +348,21 @@ explain analyze
| 0_| 0_|_AggregateExec: mode=Final, gby=[], aggr=[first_value(t.ts) ORDER BY [t.ts ASC NULLS LAST]] REDACTED
|_|_|_CoalescePartitionsExec REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[], aggr=[first_value(t.ts) ORDER BY [t.ts ASC NULLS LAST]] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_MergeScanExec: REDACTED
|_|_|_|
| 1_| 0_|_AggregateExec: mode=Final, gby=[], aggr=[__first_value_state(t.ts) ORDER BY [t.ts ASC NULLS LAST]] REDACTED
|_|_|_CoalescePartitionsExec REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[], aggr=[__first_value_state(t.ts) ORDER BY [t.ts ASC NULLS LAST]] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
| 1_| 1_|_AggregateExec: mode=Final, gby=[], aggr=[__first_value_state(t.ts) ORDER BY [t.ts ASC NULLS LAST]] REDACTED
|_|_|_CoalescePartitionsExec REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[], aggr=[__first_value_state(t.ts) ORDER BY [t.ts ASC NULLS LAST]] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
| 1_| 2_|_AggregateExec: mode=Final, gby=[], aggr=[__first_value_state(t.ts) ORDER BY [t.ts ASC NULLS LAST]] REDACTED
|_|_|_CoalescePartitionsExec REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[], aggr=[__first_value_state(t.ts) ORDER BY [t.ts ASC NULLS LAST]] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
|_|_| Total rows: 1_|
@@ -430,10 +412,8 @@ order by time_window, ordered_host;
|_|_SortExec: expr=[time_window@3 ASC NULLS LAST, ordered_host@0 ASC NULLS LAST], preserve_REDACTED
|_|_ProjectionExec: expr=[first_value(t.host) ORDER BY [t.ts ASC NULLS LAST]@1 as ordered_host, first_value(t.val) ORDER BY [t.ts ASC NULLS LAST]@2 as first_value(t.val) ORDER BY [t.ts ASC NULLS LAST], first_value(t.ts) ORDER BY [t.ts ASC NULLS LAST]@3 as first_value(t.ts) ORDER BY [t.ts ASC NULLS LAST], date_bin(Utf8("5 milliseconds"),t.ts)@0 as time_window]_|
|_|_AggregateExec: mode=FinalPartitioned, gby=[date_bin(Utf8("5 milliseconds"),t.ts)@0 as date_bin(Utf8("5 milliseconds"),t.ts)], aggr=[first_value(t.host) ORDER BY [t.ts ASC NULLS LAST], first_value(t.val) ORDER BY [t.ts ASC NULLS LAST], first_value(t.ts) ORDER BY [t.ts ASC NULLS LAST]]_|
|_|_CoalesceBatchesExec: target_batch_size=8192_|
|_|_RepartitionExec: REDACTED
|_|_AggregateExec: mode=Partial, gby=[date_bin(Utf8("5 milliseconds"),t.ts)@0 as date_bin(Utf8("5 milliseconds"),t.ts)], aggr=[first_value(t.host) ORDER BY [t.ts ASC NULLS LAST], first_value(t.val) ORDER BY [t.ts ASC NULLS LAST], first_value(t.ts) ORDER BY [t.ts ASC NULLS LAST]]_|
|_|_CooperativeExec_|
|_|_MergeScanExec: REDACTED
|_|_|
+-+-+
@@ -465,31 +445,23 @@ order by time_window, ordered_host;
|_|_|_SortExec: expr=[time_window@3 ASC NULLS LAST, ordered_host@0 ASC NULLS LAST], preserve_REDACTED
|_|_|_ProjectionExec: expr=[first_value(t.host) ORDER BY [t.ts ASC NULLS LAST]@1 as ordered_host, first_value(t.val) ORDER BY [t.ts ASC NULLS LAST]@2 as first_value(t.val) ORDER BY [t.ts ASC NULLS LAST], first_value(t.ts) ORDER BY [t.ts ASC NULLS LAST]@3 as first_value(t.ts) ORDER BY [t.ts ASC NULLS LAST], date_bin(Utf8("5 milliseconds"),t.ts)@0 as time_window] REDACTED
|_|_|_AggregateExec: mode=FinalPartitioned, gby=[date_bin(Utf8("5 milliseconds"),t.ts)@0 as date_bin(Utf8("5 milliseconds"),t.ts)], aggr=[first_value(t.host) ORDER BY [t.ts ASC NULLS LAST], first_value(t.val) ORDER BY [t.ts ASC NULLS LAST], first_value(t.ts) ORDER BY [t.ts ASC NULLS LAST]] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[date_bin(Utf8("5 milliseconds"),t.ts)@0 as date_bin(Utf8("5 milliseconds"),t.ts)], aggr=[first_value(t.host) ORDER BY [t.ts ASC NULLS LAST], first_value(t.val) ORDER BY [t.ts ASC NULLS LAST], first_value(t.ts) ORDER BY [t.ts ASC NULLS LAST]] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_MergeScanExec: REDACTED
|_|_|_|
| 1_| 0_|_AggregateExec: mode=FinalPartitioned, gby=[date_bin(Utf8("5 milliseconds"),t.ts)@0 as date_bin(Utf8("5 milliseconds"),t.ts)], aggr=[__first_value_state(t.host) ORDER BY [t.ts ASC NULLS LAST], __first_value_state(t.val) ORDER BY [t.ts ASC NULLS LAST], __first_value_state(t.ts) ORDER BY [t.ts ASC NULLS LAST]] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[date_bin(IntervalMonthDayNano { months: 0, days: 0, nanoseconds: 5000000 }, ts@0) as date_bin(Utf8("5 milliseconds"),t.ts)], aggr=[__first_value_state(t.host) ORDER BY [t.ts ASC NULLS LAST], __first_value_state(t.val) ORDER BY [t.ts ASC NULLS LAST], __first_value_state(t.ts) ORDER BY [t.ts ASC NULLS LAST]] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
| 1_| 1_|_AggregateExec: mode=FinalPartitioned, gby=[date_bin(Utf8("5 milliseconds"),t.ts)@0 as date_bin(Utf8("5 milliseconds"),t.ts)], aggr=[__first_value_state(t.host) ORDER BY [t.ts ASC NULLS LAST], __first_value_state(t.val) ORDER BY [t.ts ASC NULLS LAST], __first_value_state(t.ts) ORDER BY [t.ts ASC NULLS LAST]] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[date_bin(IntervalMonthDayNano { months: 0, days: 0, nanoseconds: 5000000 }, ts@0) as date_bin(Utf8("5 milliseconds"),t.ts)], aggr=[__first_value_state(t.host) ORDER BY [t.ts ASC NULLS LAST], __first_value_state(t.val) ORDER BY [t.ts ASC NULLS LAST], __first_value_state(t.ts) ORDER BY [t.ts ASC NULLS LAST]] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
| 1_| 2_|_AggregateExec: mode=FinalPartitioned, gby=[date_bin(Utf8("5 milliseconds"),t.ts)@0 as date_bin(Utf8("5 milliseconds"),t.ts)], aggr=[__first_value_state(t.host) ORDER BY [t.ts ASC NULLS LAST], __first_value_state(t.val) ORDER BY [t.ts ASC NULLS LAST], __first_value_state(t.ts) ORDER BY [t.ts ASC NULLS LAST]] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[date_bin(IntervalMonthDayNano { months: 0, days: 0, nanoseconds: 5000000 }, ts@0) as date_bin(Utf8("5 milliseconds"),t.ts)], aggr=[__first_value_state(t.host) ORDER BY [t.ts ASC NULLS LAST], __first_value_state(t.val) ORDER BY [t.ts ASC NULLS LAST], __first_value_state(t.ts) ORDER BY [t.ts ASC NULLS LAST]] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
|_|_| Total rows: 2_|
@@ -553,7 +525,6 @@ explain
| physical_plan | AggregateExec: mode=Final, gby=[], aggr=[first_value(t1.ts) ORDER BY [t1.ts ASC NULLS LAST]]_|
|_|_CoalescePartitionsExec_|
|_|_AggregateExec: mode=Partial, gby=[], aggr=[first_value(t1.ts) ORDER BY [t1.ts ASC NULLS LAST]]_|
|_|_CooperativeExec_|
|_|_MergeScanExec: REDACTED
|_|_|
+-+-+
@@ -577,25 +548,21 @@ explain analyze
| 0_| 0_|_AggregateExec: mode=Final, gby=[], aggr=[first_value(t1.ts) ORDER BY [t1.ts ASC NULLS LAST]] REDACTED
|_|_|_CoalescePartitionsExec REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[], aggr=[first_value(t1.ts) ORDER BY [t1.ts ASC NULLS LAST]] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_MergeScanExec: REDACTED
|_|_|_|
| 1_| 0_|_AggregateExec: mode=Final, gby=[], aggr=[__first_value_state(t1.ts) ORDER BY [t1.ts ASC NULLS LAST]] REDACTED
|_|_|_CoalescePartitionsExec REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[], aggr=[__first_value_state(t1.ts) ORDER BY [t1.ts ASC NULLS LAST]] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
| 1_| 1_|_AggregateExec: mode=Final, gby=[], aggr=[__first_value_state(t1.ts) ORDER BY [t1.ts ASC NULLS LAST]] REDACTED
|_|_|_CoalescePartitionsExec REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[], aggr=[__first_value_state(t1.ts) ORDER BY [t1.ts ASC NULLS LAST]] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
| 1_| 2_|_AggregateExec: mode=Final, gby=[], aggr=[__first_value_state(t1.ts) ORDER BY [t1.ts ASC NULLS LAST]] REDACTED
|_|_|_CoalescePartitionsExec REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[], aggr=[__first_value_state(t1.ts) ORDER BY [t1.ts ASC NULLS LAST]] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
|_|_| Total rows: 1_|
@@ -640,8 +607,6 @@ order by ordered_host;
|_|_TableScan: t1_|
|_| ]]_|
| physical_plan | SortPreservingMergeExec: [ordered_host@0 ASC NULLS LAST]_|
|_|_CooperativeExec_|
|_|_CooperativeExec_|
|_|_MergeScanExec: REDACTED
|_|_|
+-+-+
@@ -668,8 +633,6 @@ order by ordered_host;
| stage | node | plan_|
+-+-+-+
| 0_| 0_|_SortPreservingMergeExec: [ordered_host@0 ASC NULLS LAST] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_MergeScanExec: REDACTED
|_|_|_|
| 1_| 0_|_ProjectionExec: expr=[first_value(t1.host) ORDER BY [t1.ts ASC NULLS LAST]@0 as ordered_host, first_value(t1.val) ORDER BY [t1.ts ASC NULLS LAST]@1 as first_value(t1.val) ORDER BY [t1.ts ASC NULLS LAST]] REDACTED
@@ -677,10 +640,8 @@ order by ordered_host;
|_|_|_SortExec: expr=[first_value(t1.host) ORDER BY [t1.ts ASC NULLS LAST]@0 ASC NULLS LAST], preserve_REDACTED
|_|_|_ProjectionExec: expr=[first_value(t1.host) ORDER BY [t1.ts ASC NULLS LAST]@1 as first_value(t1.host) ORDER BY [t1.ts ASC NULLS LAST], first_value(t1.val) ORDER BY [t1.ts ASC NULLS LAST]@2 as first_value(t1.val) ORDER BY [t1.ts ASC NULLS LAST]] REDACTED
|_|_|_AggregateExec: mode=FinalPartitioned, gby=[host@0 as host], aggr=[first_value(t1.host) ORDER BY [t1.ts ASC NULLS LAST], first_value(t1.val) ORDER BY [t1.ts ASC NULLS LAST]] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[host@0 as host], aggr=[first_value(t1.host) ORDER BY [t1.ts ASC NULLS LAST], first_value(t1.val) ORDER BY [t1.ts ASC NULLS LAST]] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
| 1_| 1_|_ProjectionExec: expr=[first_value(t1.host) ORDER BY [t1.ts ASC NULLS LAST]@0 as ordered_host, first_value(t1.val) ORDER BY [t1.ts ASC NULLS LAST]@1 as first_value(t1.val) ORDER BY [t1.ts ASC NULLS LAST]] REDACTED
@@ -688,10 +649,8 @@ order by ordered_host;
|_|_|_SortExec: expr=[first_value(t1.host) ORDER BY [t1.ts ASC NULLS LAST]@0 ASC NULLS LAST], preserve_REDACTED
|_|_|_ProjectionExec: expr=[first_value(t1.host) ORDER BY [t1.ts ASC NULLS LAST]@1 as first_value(t1.host) ORDER BY [t1.ts ASC NULLS LAST], first_value(t1.val) ORDER BY [t1.ts ASC NULLS LAST]@2 as first_value(t1.val) ORDER BY [t1.ts ASC NULLS LAST]] REDACTED
|_|_|_AggregateExec: mode=FinalPartitioned, gby=[host@0 as host], aggr=[first_value(t1.host) ORDER BY [t1.ts ASC NULLS LAST], first_value(t1.val) ORDER BY [t1.ts ASC NULLS LAST]] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[host@0 as host], aggr=[first_value(t1.host) ORDER BY [t1.ts ASC NULLS LAST], first_value(t1.val) ORDER BY [t1.ts ASC NULLS LAST]] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
| 1_| 2_|_ProjectionExec: expr=[first_value(t1.host) ORDER BY [t1.ts ASC NULLS LAST]@0 as ordered_host, first_value(t1.val) ORDER BY [t1.ts ASC NULLS LAST]@1 as first_value(t1.val) ORDER BY [t1.ts ASC NULLS LAST]] REDACTED
@@ -699,10 +658,8 @@ order by ordered_host;
|_|_|_SortExec: expr=[first_value(t1.host) ORDER BY [t1.ts ASC NULLS LAST]@0 ASC NULLS LAST], preserve_REDACTED
|_|_|_ProjectionExec: expr=[first_value(t1.host) ORDER BY [t1.ts ASC NULLS LAST]@1 as first_value(t1.host) ORDER BY [t1.ts ASC NULLS LAST], first_value(t1.val) ORDER BY [t1.ts ASC NULLS LAST]@2 as first_value(t1.val) ORDER BY [t1.ts ASC NULLS LAST]] REDACTED
|_|_|_AggregateExec: mode=FinalPartitioned, gby=[host@0 as host], aggr=[first_value(t1.host) ORDER BY [t1.ts ASC NULLS LAST], first_value(t1.val) ORDER BY [t1.ts ASC NULLS LAST]] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[host@0 as host], aggr=[first_value(t1.host) ORDER BY [t1.ts ASC NULLS LAST], first_value(t1.val) ORDER BY [t1.ts ASC NULLS LAST]] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
|_|_| Total rows: 4_|
@@ -752,10 +709,8 @@ order by time_window, ordered_host;
|_|_SortExec: expr=[time_window@3 ASC NULLS LAST, ordered_host@0 ASC NULLS LAST], preserve_REDACTED
|_|_ProjectionExec: expr=[first_value(t1.host) ORDER BY [t1.ts ASC NULLS LAST]@1 as ordered_host, first_value(t1.val) ORDER BY [t1.ts ASC NULLS LAST]@2 as first_value(t1.val) ORDER BY [t1.ts ASC NULLS LAST], first_value(t1.ts) ORDER BY [t1.ts ASC NULLS LAST]@3 as first_value(t1.ts) ORDER BY [t1.ts ASC NULLS LAST], date_bin(Utf8("5 milliseconds"),t1.ts)@0 as time_window]_|
|_|_AggregateExec: mode=FinalPartitioned, gby=[date_bin(Utf8("5 milliseconds"),t1.ts)@0 as date_bin(Utf8("5 milliseconds"),t1.ts)], aggr=[first_value(t1.host) ORDER BY [t1.ts ASC NULLS LAST], first_value(t1.val) ORDER BY [t1.ts ASC NULLS LAST], first_value(t1.ts) ORDER BY [t1.ts ASC NULLS LAST]]_|
|_|_CoalesceBatchesExec: target_batch_size=8192_|
|_|_RepartitionExec: REDACTED
|_|_AggregateExec: mode=Partial, gby=[date_bin(Utf8("5 milliseconds"),t1.ts)@0 as date_bin(Utf8("5 milliseconds"),t1.ts)], aggr=[first_value(t1.host) ORDER BY [t1.ts ASC NULLS LAST], first_value(t1.val) ORDER BY [t1.ts ASC NULLS LAST], first_value(t1.ts) ORDER BY [t1.ts ASC NULLS LAST]]_|
|_|_CooperativeExec_|
|_|_MergeScanExec: REDACTED
|_|_|
+-+-+
@@ -787,31 +742,23 @@ order by time_window, ordered_host;
|_|_|_SortExec: expr=[time_window@3 ASC NULLS LAST, ordered_host@0 ASC NULLS LAST], preserve_REDACTED
|_|_|_ProjectionExec: expr=[first_value(t1.host) ORDER BY [t1.ts ASC NULLS LAST]@1 as ordered_host, first_value(t1.val) ORDER BY [t1.ts ASC NULLS LAST]@2 as first_value(t1.val) ORDER BY [t1.ts ASC NULLS LAST], first_value(t1.ts) ORDER BY [t1.ts ASC NULLS LAST]@3 as first_value(t1.ts) ORDER BY [t1.ts ASC NULLS LAST], date_bin(Utf8("5 milliseconds"),t1.ts)@0 as time_window] REDACTED
|_|_|_AggregateExec: mode=FinalPartitioned, gby=[date_bin(Utf8("5 milliseconds"),t1.ts)@0 as date_bin(Utf8("5 milliseconds"),t1.ts)], aggr=[first_value(t1.host) ORDER BY [t1.ts ASC NULLS LAST], first_value(t1.val) ORDER BY [t1.ts ASC NULLS LAST], first_value(t1.ts) ORDER BY [t1.ts ASC NULLS LAST]] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[date_bin(Utf8("5 milliseconds"),t1.ts)@0 as date_bin(Utf8("5 milliseconds"),t1.ts)], aggr=[first_value(t1.host) ORDER BY [t1.ts ASC NULLS LAST], first_value(t1.val) ORDER BY [t1.ts ASC NULLS LAST], first_value(t1.ts) ORDER BY [t1.ts ASC NULLS LAST]] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_MergeScanExec: REDACTED
|_|_|_|
| 1_| 0_|_AggregateExec: mode=FinalPartitioned, gby=[date_bin(Utf8("5 milliseconds"),t1.ts)@0 as date_bin(Utf8("5 milliseconds"),t1.ts)], aggr=[__first_value_state(t1.host) ORDER BY [t1.ts ASC NULLS LAST], __first_value_state(t1.val) ORDER BY [t1.ts ASC NULLS LAST], __first_value_state(t1.ts) ORDER BY [t1.ts ASC NULLS LAST]] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[date_bin(IntervalMonthDayNano { months: 0, days: 0, nanoseconds: 5000000 }, ts@1) as date_bin(Utf8("5 milliseconds"),t1.ts)], aggr=[__first_value_state(t1.host) ORDER BY [t1.ts ASC NULLS LAST], __first_value_state(t1.val) ORDER BY [t1.ts ASC NULLS LAST], __first_value_state(t1.ts) ORDER BY [t1.ts ASC NULLS LAST]] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
| 1_| 1_|_AggregateExec: mode=FinalPartitioned, gby=[date_bin(Utf8("5 milliseconds"),t1.ts)@0 as date_bin(Utf8("5 milliseconds"),t1.ts)], aggr=[__first_value_state(t1.host) ORDER BY [t1.ts ASC NULLS LAST], __first_value_state(t1.val) ORDER BY [t1.ts ASC NULLS LAST], __first_value_state(t1.ts) ORDER BY [t1.ts ASC NULLS LAST]] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[date_bin(IntervalMonthDayNano { months: 0, days: 0, nanoseconds: 5000000 }, ts@1) as date_bin(Utf8("5 milliseconds"),t1.ts)], aggr=[__first_value_state(t1.host) ORDER BY [t1.ts ASC NULLS LAST], __first_value_state(t1.val) ORDER BY [t1.ts ASC NULLS LAST], __first_value_state(t1.ts) ORDER BY [t1.ts ASC NULLS LAST]] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
| 1_| 2_|_AggregateExec: mode=FinalPartitioned, gby=[date_bin(Utf8("5 milliseconds"),t1.ts)@0 as date_bin(Utf8("5 milliseconds"),t1.ts)], aggr=[__first_value_state(t1.host) ORDER BY [t1.ts ASC NULLS LAST], __first_value_state(t1.val) ORDER BY [t1.ts ASC NULLS LAST], __first_value_state(t1.ts) ORDER BY [t1.ts ASC NULLS LAST]] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[date_bin(IntervalMonthDayNano { months: 0, days: 0, nanoseconds: 5000000 }, ts@1) as date_bin(Utf8("5 milliseconds"),t1.ts)], aggr=[__first_value_state(t1.host) ORDER BY [t1.ts ASC NULLS LAST], __first_value_state(t1.val) ORDER BY [t1.ts ASC NULLS LAST], __first_value_state(t1.ts) ORDER BY [t1.ts ASC NULLS LAST]] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
|_|_| Total rows: 2_|

53
tests/cases/distributed/optimizer/last_value_advance.result
View File

@@ -111,10 +111,8 @@ explain analyze
|_|_|_|
| 1_| 0_|_ProjectionExec: expr=[last_value(t.host) ORDER BY [t.ts ASC NULLS LAST]@1 as last_value(t.host) ORDER BY [t.ts ASC NULLS LAST], last_value(t.not_pk) ORDER BY [t.ts ASC NULLS LAST]@2 as last_value(t.not_pk) ORDER BY [t.ts ASC NULLS LAST], last_value(t.val) ORDER BY [t.ts ASC NULLS LAST]@3 as last_value(t.val) ORDER BY [t.ts ASC NULLS LAST]] REDACTED
|_|_|_AggregateExec: mode=FinalPartitioned, gby=[host@0 as host], aggr=[last_value(t.host) ORDER BY [t.ts ASC NULLS LAST], last_value(t.not_pk) ORDER BY [t.ts ASC NULLS LAST], last_value(t.val) ORDER BY [t.ts ASC NULLS LAST]] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[host@1 as host], aggr=[last_value(t.host) ORDER BY [t.ts ASC NULLS LAST], last_value(t.not_pk) ORDER BY [t.ts ASC NULLS LAST], last_value(t.val) ORDER BY [t.ts ASC NULLS LAST]] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":{"count":1, "mem_ranges":0, "files":1, "file_ranges":1}, "selector":"LastRow" REDACTED
|_|_|_|
|_|_| Total rows: 4_|
@@ -167,7 +165,6 @@ explain analyze
| 1_| 0_|_AggregateExec: mode=Final, gby=[], aggr=[last_value(t.ts) ORDER BY [t.ts ASC NULLS LAST]] REDACTED
|_|_|_CoalescePartitionsExec REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[], aggr=[last_value(t.ts) ORDER BY [t.ts ASC NULLS LAST]] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":{"count":1, "mem_ranges":0, "files":1, "file_ranges":1}, "selector":"LastRow" REDACTED
|_|_|_|
|_|_| Total rows: 1_|
@@ -244,8 +241,6 @@ order by ordered_host;
|_|_TableScan: t_|
|_| ]]_|
| physical_plan | SortPreservingMergeExec: [ordered_host@0 ASC NULLS LAST]_|
|_|_CooperativeExec_|
|_|_CooperativeExec_|
|_|_MergeScanExec: REDACTED
|_|_|
+-+-+
@@ -273,8 +268,6 @@ order by ordered_host;
| stage | node | plan_|
+-+-+-+
| 0_| 0_|_SortPreservingMergeExec: [ordered_host@0 ASC NULLS LAST] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_MergeScanExec: REDACTED
|_|_|_|
| 1_| 0_|_ProjectionExec: expr=[last_value(t.host) ORDER BY [t.ts ASC NULLS LAST]@0 as ordered_host, last_value(t.not_pk) ORDER BY [t.ts ASC NULLS LAST]@1 as last_value(t.not_pk) ORDER BY [t.ts ASC NULLS LAST], last_value(t.val) ORDER BY [t.ts ASC NULLS LAST]@2 as last_value(t.val) ORDER BY [t.ts ASC NULLS LAST]] REDACTED
@@ -282,10 +275,8 @@ order by ordered_host;
|_|_|_SortExec: expr=[last_value(t.host) ORDER BY [t.ts ASC NULLS LAST]@0 ASC NULLS LAST], preserve_REDACTED
|_|_|_ProjectionExec: expr=[last_value(t.host) ORDER BY [t.ts ASC NULLS LAST]@1 as last_value(t.host) ORDER BY [t.ts ASC NULLS LAST], last_value(t.not_pk) ORDER BY [t.ts ASC NULLS LAST]@2 as last_value(t.not_pk) ORDER BY [t.ts ASC NULLS LAST], last_value(t.val) ORDER BY [t.ts ASC NULLS LAST]@3 as last_value(t.val) ORDER BY [t.ts ASC NULLS LAST]] REDACTED
|_|_|_AggregateExec: mode=FinalPartitioned, gby=[host@0 as host], aggr=[last_value(t.host) ORDER BY [t.ts ASC NULLS LAST], last_value(t.not_pk) ORDER BY [t.ts ASC NULLS LAST], last_value(t.val) ORDER BY [t.ts ASC NULLS LAST]] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[host@1 as host], aggr=[last_value(t.host) ORDER BY [t.ts ASC NULLS LAST], last_value(t.not_pk) ORDER BY [t.ts ASC NULLS LAST], last_value(t.val) ORDER BY [t.ts ASC NULLS LAST]] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":REDACTED, "selector":"LastRow" REDACTED
|_|_|_|
| 1_| 1_|_ProjectionExec: expr=[last_value(t.host) ORDER BY [t.ts ASC NULLS LAST]@0 as ordered_host, last_value(t.not_pk) ORDER BY [t.ts ASC NULLS LAST]@1 as last_value(t.not_pk) ORDER BY [t.ts ASC NULLS LAST], last_value(t.val) ORDER BY [t.ts ASC NULLS LAST]@2 as last_value(t.val) ORDER BY [t.ts ASC NULLS LAST]] REDACTED
@@ -293,10 +284,8 @@ order by ordered_host;
|_|_|_SortExec: expr=[last_value(t.host) ORDER BY [t.ts ASC NULLS LAST]@0 ASC NULLS LAST], preserve_REDACTED
|_|_|_ProjectionExec: expr=[last_value(t.host) ORDER BY [t.ts ASC NULLS LAST]@1 as last_value(t.host) ORDER BY [t.ts ASC NULLS LAST], last_value(t.not_pk) ORDER BY [t.ts ASC NULLS LAST]@2 as last_value(t.not_pk) ORDER BY [t.ts ASC NULLS LAST], last_value(t.val) ORDER BY [t.ts ASC NULLS LAST]@3 as last_value(t.val) ORDER BY [t.ts ASC NULLS LAST]] REDACTED
|_|_|_AggregateExec: mode=FinalPartitioned, gby=[host@0 as host], aggr=[last_value(t.host) ORDER BY [t.ts ASC NULLS LAST], last_value(t.not_pk) ORDER BY [t.ts ASC NULLS LAST], last_value(t.val) ORDER BY [t.ts ASC NULLS LAST]] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[host@1 as host], aggr=[last_value(t.host) ORDER BY [t.ts ASC NULLS LAST], last_value(t.not_pk) ORDER BY [t.ts ASC NULLS LAST], last_value(t.val) ORDER BY [t.ts ASC NULLS LAST]] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":REDACTED, "selector":"LastRow" REDACTED
|_|_|_|
| 1_| 2_|_ProjectionExec: expr=[last_value(t.host) ORDER BY [t.ts ASC NULLS LAST]@0 as ordered_host, last_value(t.not_pk) ORDER BY [t.ts ASC NULLS LAST]@1 as last_value(t.not_pk) ORDER BY [t.ts ASC NULLS LAST], last_value(t.val) ORDER BY [t.ts ASC NULLS LAST]@2 as last_value(t.val) ORDER BY [t.ts ASC NULLS LAST]] REDACTED
@@ -304,10 +293,8 @@ order by ordered_host;
|_|_|_SortExec: expr=[last_value(t.host) ORDER BY [t.ts ASC NULLS LAST]@0 ASC NULLS LAST], preserve_REDACTED
|_|_|_ProjectionExec: expr=[last_value(t.host) ORDER BY [t.ts ASC NULLS LAST]@1 as last_value(t.host) ORDER BY [t.ts ASC NULLS LAST], last_value(t.not_pk) ORDER BY [t.ts ASC NULLS LAST]@2 as last_value(t.not_pk) ORDER BY [t.ts ASC NULLS LAST], last_value(t.val) ORDER BY [t.ts ASC NULLS LAST]@3 as last_value(t.val) ORDER BY [t.ts ASC NULLS LAST]] REDACTED
|_|_|_AggregateExec: mode=FinalPartitioned, gby=[host@0 as host], aggr=[last_value(t.host) ORDER BY [t.ts ASC NULLS LAST], last_value(t.not_pk) ORDER BY [t.ts ASC NULLS LAST], last_value(t.val) ORDER BY [t.ts ASC NULLS LAST]] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[host@1 as host], aggr=[last_value(t.host) ORDER BY [t.ts ASC NULLS LAST], last_value(t.not_pk) ORDER BY [t.ts ASC NULLS LAST], last_value(t.val) ORDER BY [t.ts ASC NULLS LAST]] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":REDACTED, "selector":"LastRow" REDACTED
|_|_|_|
|_|_| Total rows: 4_|
@@ -338,7 +325,6 @@ explain select last_value(ts order by ts) from t;
| physical_plan | AggregateExec: mode=Final, gby=[], aggr=[last_value(t.ts) ORDER BY [t.ts ASC NULLS LAST]]_|
|_|_CoalescePartitionsExec_|
|_|_AggregateExec: mode=Partial, gby=[], aggr=[last_value(t.ts) ORDER BY [t.ts ASC NULLS LAST]]_|
|_|_CooperativeExec_|
|_|_MergeScanExec: REDACTED
|_|_|
+-+-+
@@ -362,25 +348,21 @@ explain analyze
| 0_| 0_|_AggregateExec: mode=Final, gby=[], aggr=[last_value(t.ts) ORDER BY [t.ts ASC NULLS LAST]] REDACTED
|_|_|_CoalescePartitionsExec REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[], aggr=[last_value(t.ts) ORDER BY [t.ts ASC NULLS LAST]] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_MergeScanExec: REDACTED
|_|_|_|
| 1_| 0_|_AggregateExec: mode=Final, gby=[], aggr=[__last_value_state(t.ts) ORDER BY [t.ts ASC NULLS LAST]] REDACTED
|_|_|_CoalescePartitionsExec REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[], aggr=[__last_value_state(t.ts) ORDER BY [t.ts ASC NULLS LAST]] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":REDACTED, "selector":"LastRow" REDACTED
|_|_|_|
| 1_| 1_|_AggregateExec: mode=Final, gby=[], aggr=[__last_value_state(t.ts) ORDER BY [t.ts ASC NULLS LAST]] REDACTED
|_|_|_CoalescePartitionsExec REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[], aggr=[__last_value_state(t.ts) ORDER BY [t.ts ASC NULLS LAST]] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":REDACTED, "selector":"LastRow" REDACTED
|_|_|_|
| 1_| 2_|_AggregateExec: mode=Final, gby=[], aggr=[__last_value_state(t.ts) ORDER BY [t.ts ASC NULLS LAST]] REDACTED
|_|_|_CoalescePartitionsExec REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[], aggr=[__last_value_state(t.ts) ORDER BY [t.ts ASC NULLS LAST]] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":REDACTED, "selector":"LastRow" REDACTED
|_|_|_|
|_|_| Total rows: 1_|
@@ -430,10 +412,8 @@ order by time_window, ordered_host;
|_|_SortExec: expr=[time_window@3 ASC NULLS LAST, ordered_host@0 ASC NULLS LAST], preserve_REDACTED
|_|_ProjectionExec: expr=[last_value(t.host) ORDER BY [t.ts ASC NULLS LAST]@1 as ordered_host, last_value(t.val) ORDER BY [t.ts ASC NULLS LAST]@2 as last_value(t.val) ORDER BY [t.ts ASC NULLS LAST], last_value(t.ts) ORDER BY [t.ts ASC NULLS LAST]@3 as last_value(t.ts) ORDER BY [t.ts ASC NULLS LAST], date_bin(Utf8("5 milliseconds"),t.ts)@0 as time_window]_|
|_|_AggregateExec: mode=FinalPartitioned, gby=[date_bin(Utf8("5 milliseconds"),t.ts)@0 as date_bin(Utf8("5 milliseconds"),t.ts)], aggr=[last_value(t.host) ORDER BY [t.ts ASC NULLS LAST], last_value(t.val) ORDER BY [t.ts ASC NULLS LAST], last_value(t.ts) ORDER BY [t.ts ASC NULLS LAST]]_|
|_|_CoalesceBatchesExec: target_batch_size=8192_|
|_|_RepartitionExec: REDACTED
|_|_AggregateExec: mode=Partial, gby=[date_bin(Utf8("5 milliseconds"),t.ts)@0 as date_bin(Utf8("5 milliseconds"),t.ts)], aggr=[last_value(t.host) ORDER BY [t.ts ASC NULLS LAST], last_value(t.val) ORDER BY [t.ts ASC NULLS LAST], last_value(t.ts) ORDER BY [t.ts ASC NULLS LAST]]_|
|_|_CooperativeExec_|
|_|_MergeScanExec: REDACTED
|_|_|
+-+-+
@@ -465,31 +445,23 @@ order by time_window, ordered_host;
|_|_|_SortExec: expr=[time_window@3 ASC NULLS LAST, ordered_host@0 ASC NULLS LAST], preserve_REDACTED
|_|_|_ProjectionExec: expr=[last_value(t.host) ORDER BY [t.ts ASC NULLS LAST]@1 as ordered_host, last_value(t.val) ORDER BY [t.ts ASC NULLS LAST]@2 as last_value(t.val) ORDER BY [t.ts ASC NULLS LAST], last_value(t.ts) ORDER BY [t.ts ASC NULLS LAST]@3 as last_value(t.ts) ORDER BY [t.ts ASC NULLS LAST], date_bin(Utf8("5 milliseconds"),t.ts)@0 as time_window] REDACTED
|_|_|_AggregateExec: mode=FinalPartitioned, gby=[date_bin(Utf8("5 milliseconds"),t.ts)@0 as date_bin(Utf8("5 milliseconds"),t.ts)], aggr=[last_value(t.host) ORDER BY [t.ts ASC NULLS LAST], last_value(t.val) ORDER BY [t.ts ASC NULLS LAST], last_value(t.ts) ORDER BY [t.ts ASC NULLS LAST]] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[date_bin(Utf8("5 milliseconds"),t.ts)@0 as date_bin(Utf8("5 milliseconds"),t.ts)], aggr=[last_value(t.host) ORDER BY [t.ts ASC NULLS LAST], last_value(t.val) ORDER BY [t.ts ASC NULLS LAST], last_value(t.ts) ORDER BY [t.ts ASC NULLS LAST]] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_MergeScanExec: REDACTED
|_|_|_|
| 1_| 0_|_AggregateExec: mode=FinalPartitioned, gby=[date_bin(Utf8("5 milliseconds"),t.ts)@0 as date_bin(Utf8("5 milliseconds"),t.ts)], aggr=[__last_value_state(t.host) ORDER BY [t.ts ASC NULLS LAST], __last_value_state(t.val) ORDER BY [t.ts ASC NULLS LAST], __last_value_state(t.ts) ORDER BY [t.ts ASC NULLS LAST]] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[date_bin(IntervalMonthDayNano { months: 0, days: 0, nanoseconds: 5000000 }, ts@0) as date_bin(Utf8("5 milliseconds"),t.ts)], aggr=[__last_value_state(t.host) ORDER BY [t.ts ASC NULLS LAST], __last_value_state(t.val) ORDER BY [t.ts ASC NULLS LAST], __last_value_state(t.ts) ORDER BY [t.ts ASC NULLS LAST]] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
| 1_| 1_|_AggregateExec: mode=FinalPartitioned, gby=[date_bin(Utf8("5 milliseconds"),t.ts)@0 as date_bin(Utf8("5 milliseconds"),t.ts)], aggr=[__last_value_state(t.host) ORDER BY [t.ts ASC NULLS LAST], __last_value_state(t.val) ORDER BY [t.ts ASC NULLS LAST], __last_value_state(t.ts) ORDER BY [t.ts ASC NULLS LAST]] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[date_bin(IntervalMonthDayNano { months: 0, days: 0, nanoseconds: 5000000 }, ts@0) as date_bin(Utf8("5 milliseconds"),t.ts)], aggr=[__last_value_state(t.host) ORDER BY [t.ts ASC NULLS LAST], __last_value_state(t.val) ORDER BY [t.ts ASC NULLS LAST], __last_value_state(t.ts) ORDER BY [t.ts ASC NULLS LAST]] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
| 1_| 2_|_AggregateExec: mode=FinalPartitioned, gby=[date_bin(Utf8("5 milliseconds"),t.ts)@0 as date_bin(Utf8("5 milliseconds"),t.ts)], aggr=[__last_value_state(t.host) ORDER BY [t.ts ASC NULLS LAST], __last_value_state(t.val) ORDER BY [t.ts ASC NULLS LAST], __last_value_state(t.ts) ORDER BY [t.ts ASC NULLS LAST]] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[date_bin(IntervalMonthDayNano { months: 0, days: 0, nanoseconds: 5000000 }, ts@0) as date_bin(Utf8("5 milliseconds"),t.ts)], aggr=[__last_value_state(t.host) ORDER BY [t.ts ASC NULLS LAST], __last_value_state(t.val) ORDER BY [t.ts ASC NULLS LAST], __last_value_state(t.ts) ORDER BY [t.ts ASC NULLS LAST]] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
|_|_| Total rows: 2_|
@@ -553,7 +525,6 @@ explain
| physical_plan | AggregateExec: mode=Final, gby=[], aggr=[last_value(t1.ts) ORDER BY [t1.ts ASC NULLS LAST]]_|
|_|_CoalescePartitionsExec_|
|_|_AggregateExec: mode=Partial, gby=[], aggr=[last_value(t1.ts) ORDER BY [t1.ts ASC NULLS LAST]]_|
|_|_CooperativeExec_|
|_|_MergeScanExec: REDACTED
|_|_|
+-+-+
@@ -577,25 +548,21 @@ explain analyze
| 0_| 0_|_AggregateExec: mode=Final, gby=[], aggr=[last_value(t1.ts) ORDER BY [t1.ts ASC NULLS LAST]] REDACTED
|_|_|_CoalescePartitionsExec REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[], aggr=[last_value(t1.ts) ORDER BY [t1.ts ASC NULLS LAST]] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_MergeScanExec: REDACTED
|_|_|_|
| 1_| 0_|_AggregateExec: mode=Final, gby=[], aggr=[__last_value_state(t1.ts) ORDER BY [t1.ts ASC NULLS LAST]] REDACTED
|_|_|_CoalescePartitionsExec REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[], aggr=[__last_value_state(t1.ts) ORDER BY [t1.ts ASC NULLS LAST]] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":REDACTED, "selector":"LastRow" REDACTED
|_|_|_|
| 1_| 1_|_AggregateExec: mode=Final, gby=[], aggr=[__last_value_state(t1.ts) ORDER BY [t1.ts ASC NULLS LAST]] REDACTED
|_|_|_CoalescePartitionsExec REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[], aggr=[__last_value_state(t1.ts) ORDER BY [t1.ts ASC NULLS LAST]] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":REDACTED, "selector":"LastRow" REDACTED
|_|_|_|
| 1_| 2_|_AggregateExec: mode=Final, gby=[], aggr=[__last_value_state(t1.ts) ORDER BY [t1.ts ASC NULLS LAST]] REDACTED
|_|_|_CoalescePartitionsExec REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[], aggr=[__last_value_state(t1.ts) ORDER BY [t1.ts ASC NULLS LAST]] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":REDACTED, "selector":"LastRow" REDACTED
|_|_|_|
|_|_| Total rows: 1_|
@@ -640,8 +607,6 @@ order by ordered_host;
|_|_TableScan: t1_|
|_| ]]_|
| physical_plan | SortPreservingMergeExec: [ordered_host@0 ASC NULLS LAST]_|
|_|_CooperativeExec_|
|_|_CooperativeExec_|
|_|_MergeScanExec: REDACTED
|_|_|
+-+-+
@@ -668,8 +633,6 @@ order by ordered_host;
| stage | node | plan_|
+-+-+-+
| 0_| 0_|_SortPreservingMergeExec: [ordered_host@0 ASC NULLS LAST] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_MergeScanExec: REDACTED
|_|_|_|
| 1_| 0_|_ProjectionExec: expr=[last_value(t1.host) ORDER BY [t1.ts ASC NULLS LAST]@0 as ordered_host, last_value(t1.val) ORDER BY [t1.ts ASC NULLS LAST]@1 as last_value(t1.val) ORDER BY [t1.ts ASC NULLS LAST]] REDACTED
@@ -677,10 +640,8 @@ order by ordered_host;
|_|_|_SortExec: expr=[last_value(t1.host) ORDER BY [t1.ts ASC NULLS LAST]@0 ASC NULLS LAST], preserve_REDACTED
|_|_|_ProjectionExec: expr=[last_value(t1.host) ORDER BY [t1.ts ASC NULLS LAST]@1 as last_value(t1.host) ORDER BY [t1.ts ASC NULLS LAST], last_value(t1.val) ORDER BY [t1.ts ASC NULLS LAST]@2 as last_value(t1.val) ORDER BY [t1.ts ASC NULLS LAST]] REDACTED
|_|_|_AggregateExec: mode=FinalPartitioned, gby=[host@0 as host], aggr=[last_value(t1.host) ORDER BY [t1.ts ASC NULLS LAST], last_value(t1.val) ORDER BY [t1.ts ASC NULLS LAST]] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[host@0 as host], aggr=[last_value(t1.host) ORDER BY [t1.ts ASC NULLS LAST], last_value(t1.val) ORDER BY [t1.ts ASC NULLS LAST]] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":REDACTED, "selector":"LastRow" REDACTED
|_|_|_|
| 1_| 1_|_ProjectionExec: expr=[last_value(t1.host) ORDER BY [t1.ts ASC NULLS LAST]@0 as ordered_host, last_value(t1.val) ORDER BY [t1.ts ASC NULLS LAST]@1 as last_value(t1.val) ORDER BY [t1.ts ASC NULLS LAST]] REDACTED
@@ -688,10 +649,8 @@ order by ordered_host;
|_|_|_SortExec: expr=[last_value(t1.host) ORDER BY [t1.ts ASC NULLS LAST]@0 ASC NULLS LAST], preserve_REDACTED
|_|_|_ProjectionExec: expr=[last_value(t1.host) ORDER BY [t1.ts ASC NULLS LAST]@1 as last_value(t1.host) ORDER BY [t1.ts ASC NULLS LAST], last_value(t1.val) ORDER BY [t1.ts ASC NULLS LAST]@2 as last_value(t1.val) ORDER BY [t1.ts ASC NULLS LAST]] REDACTED
|_|_|_AggregateExec: mode=FinalPartitioned, gby=[host@0 as host], aggr=[last_value(t1.host) ORDER BY [t1.ts ASC NULLS LAST], last_value(t1.val) ORDER BY [t1.ts ASC NULLS LAST]] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[host@0 as host], aggr=[last_value(t1.host) ORDER BY [t1.ts ASC NULLS LAST], last_value(t1.val) ORDER BY [t1.ts ASC NULLS LAST]] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":REDACTED, "selector":"LastRow" REDACTED
|_|_|_|
| 1_| 2_|_ProjectionExec: expr=[last_value(t1.host) ORDER BY [t1.ts ASC NULLS LAST]@0 as ordered_host, last_value(t1.val) ORDER BY [t1.ts ASC NULLS LAST]@1 as last_value(t1.val) ORDER BY [t1.ts ASC NULLS LAST]] REDACTED
@@ -699,10 +658,8 @@ order by ordered_host;
|_|_|_SortExec: expr=[last_value(t1.host) ORDER BY [t1.ts ASC NULLS LAST]@0 ASC NULLS LAST], preserve_REDACTED
|_|_|_ProjectionExec: expr=[last_value(t1.host) ORDER BY [t1.ts ASC NULLS LAST]@1 as last_value(t1.host) ORDER BY [t1.ts ASC NULLS LAST], last_value(t1.val) ORDER BY [t1.ts ASC NULLS LAST]@2 as last_value(t1.val) ORDER BY [t1.ts ASC NULLS LAST]] REDACTED
|_|_|_AggregateExec: mode=FinalPartitioned, gby=[host@0 as host], aggr=[last_value(t1.host) ORDER BY [t1.ts ASC NULLS LAST], last_value(t1.val) ORDER BY [t1.ts ASC NULLS LAST]] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[host@0 as host], aggr=[last_value(t1.host) ORDER BY [t1.ts ASC NULLS LAST], last_value(t1.val) ORDER BY [t1.ts ASC NULLS LAST]] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":REDACTED, "selector":"LastRow" REDACTED
|_|_|_|
|_|_| Total rows: 4_|
@@ -752,10 +709,8 @@ order by time_window, ordered_host;
|_|_SortExec: expr=[time_window@3 ASC NULLS LAST, ordered_host@0 ASC NULLS LAST], preserve_REDACTED
|_|_ProjectionExec: expr=[last_value(t1.host) ORDER BY [t1.ts ASC NULLS LAST]@1 as ordered_host, last_value(t1.val) ORDER BY [t1.ts ASC NULLS LAST]@2 as last_value(t1.val) ORDER BY [t1.ts ASC NULLS LAST], last_value(t1.ts) ORDER BY [t1.ts ASC NULLS LAST]@3 as last_value(t1.ts) ORDER BY [t1.ts ASC NULLS LAST], date_bin(Utf8("5 milliseconds"),t1.ts)@0 as time_window]_|
|_|_AggregateExec: mode=FinalPartitioned, gby=[date_bin(Utf8("5 milliseconds"),t1.ts)@0 as date_bin(Utf8("5 milliseconds"),t1.ts)], aggr=[last_value(t1.host) ORDER BY [t1.ts ASC NULLS LAST], last_value(t1.val) ORDER BY [t1.ts ASC NULLS LAST], last_value(t1.ts) ORDER BY [t1.ts ASC NULLS LAST]]_|
|_|_CoalesceBatchesExec: target_batch_size=8192_|
|_|_RepartitionExec: REDACTED
|_|_AggregateExec: mode=Partial, gby=[date_bin(Utf8("5 milliseconds"),t1.ts)@0 as date_bin(Utf8("5 milliseconds"),t1.ts)], aggr=[last_value(t1.host) ORDER BY [t1.ts ASC NULLS LAST], last_value(t1.val) ORDER BY [t1.ts ASC NULLS LAST], last_value(t1.ts) ORDER BY [t1.ts ASC NULLS LAST]]_|
|_|_CooperativeExec_|
|_|_MergeScanExec: REDACTED
|_|_|
+-+-+
@@ -787,31 +742,23 @@ order by time_window, ordered_host;
|_|_|_SortExec: expr=[time_window@3 ASC NULLS LAST, ordered_host@0 ASC NULLS LAST], preserve_REDACTED
|_|_|_ProjectionExec: expr=[last_value(t1.host) ORDER BY [t1.ts ASC NULLS LAST]@1 as ordered_host, last_value(t1.val) ORDER BY [t1.ts ASC NULLS LAST]@2 as last_value(t1.val) ORDER BY [t1.ts ASC NULLS LAST], last_value(t1.ts) ORDER BY [t1.ts ASC NULLS LAST]@3 as last_value(t1.ts) ORDER BY [t1.ts ASC NULLS LAST], date_bin(Utf8("5 milliseconds"),t1.ts)@0 as time_window] REDACTED
|_|_|_AggregateExec: mode=FinalPartitioned, gby=[date_bin(Utf8("5 milliseconds"),t1.ts)@0 as date_bin(Utf8("5 milliseconds"),t1.ts)], aggr=[last_value(t1.host) ORDER BY [t1.ts ASC NULLS LAST], last_value(t1.val) ORDER BY [t1.ts ASC NULLS LAST], last_value(t1.ts) ORDER BY [t1.ts ASC NULLS LAST]] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[date_bin(Utf8("5 milliseconds"),t1.ts)@0 as date_bin(Utf8("5 milliseconds"),t1.ts)], aggr=[last_value(t1.host) ORDER BY [t1.ts ASC NULLS LAST], last_value(t1.val) ORDER BY [t1.ts ASC NULLS LAST], last_value(t1.ts) ORDER BY [t1.ts ASC NULLS LAST]] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_MergeScanExec: REDACTED
|_|_|_|
| 1_| 0_|_AggregateExec: mode=FinalPartitioned, gby=[date_bin(Utf8("5 milliseconds"),t1.ts)@0 as date_bin(Utf8("5 milliseconds"),t1.ts)], aggr=[__last_value_state(t1.host) ORDER BY [t1.ts ASC NULLS LAST], __last_value_state(t1.val) ORDER BY [t1.ts ASC NULLS LAST], __last_value_state(t1.ts) ORDER BY [t1.ts ASC NULLS LAST]] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[date_bin(IntervalMonthDayNano { months: 0, days: 0, nanoseconds: 5000000 }, ts@1) as date_bin(Utf8("5 milliseconds"),t1.ts)], aggr=[__last_value_state(t1.host) ORDER BY [t1.ts ASC NULLS LAST], __last_value_state(t1.val) ORDER BY [t1.ts ASC NULLS LAST], __last_value_state(t1.ts) ORDER BY [t1.ts ASC NULLS LAST]] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
| 1_| 1_|_AggregateExec: mode=FinalPartitioned, gby=[date_bin(Utf8("5 milliseconds"),t1.ts)@0 as date_bin(Utf8("5 milliseconds"),t1.ts)], aggr=[__last_value_state(t1.host) ORDER BY [t1.ts ASC NULLS LAST], __last_value_state(t1.val) ORDER BY [t1.ts ASC NULLS LAST], __last_value_state(t1.ts) ORDER BY [t1.ts ASC NULLS LAST]] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[date_bin(IntervalMonthDayNano { months: 0, days: 0, nanoseconds: 5000000 }, ts@1) as date_bin(Utf8("5 milliseconds"),t1.ts)], aggr=[__last_value_state(t1.host) ORDER BY [t1.ts ASC NULLS LAST], __last_value_state(t1.val) ORDER BY [t1.ts ASC NULLS LAST], __last_value_state(t1.ts) ORDER BY [t1.ts ASC NULLS LAST]] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
| 1_| 2_|_AggregateExec: mode=FinalPartitioned, gby=[date_bin(Utf8("5 milliseconds"),t1.ts)@0 as date_bin(Utf8("5 milliseconds"),t1.ts)], aggr=[__last_value_state(t1.host) ORDER BY [t1.ts ASC NULLS LAST], __last_value_state(t1.val) ORDER BY [t1.ts ASC NULLS LAST], __last_value_state(t1.ts) ORDER BY [t1.ts ASC NULLS LAST]] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[date_bin(IntervalMonthDayNano { months: 0, days: 0, nanoseconds: 5000000 }, ts@1) as date_bin(Utf8("5 milliseconds"),t1.ts)], aggr=[__last_value_state(t1.host) ORDER BY [t1.ts ASC NULLS LAST], __last_value_state(t1.val) ORDER BY [t1.ts ASC NULLS LAST], __last_value_state(t1.ts) ORDER BY [t1.ts ASC NULLS LAST]] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
|_|_| Total rows: 2_|

143
tests/cases/distributed/optimizer/order_by.result
View File

@@ -2,103 +2,98 @@
-- SQLNESS REPLACE (RoundRobinBatch.*) REDACTED
explain select * from numbers;
+---------------+-------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| plan_type | plan |
+---------------+-------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| logical_plan | MergeScan [is_placeholder=false, remote_input=[ |
| | Projection: numbers.number |
| | TableScan: numbers |
| | ]] |
| physical_plan | CooperativeExec |
+---------------+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| plan_type | plan |
+---------------+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| logical_plan | MergeScan [is_placeholder=false, remote_input=[ |
| | Projection: numbers.number |
| | TableScan: numbers |
| | ]] |
| physical_plan | CooperativeExec |
| | RepartitionExec: partitioning=REDACTED
| | CooperativeExec |
| | StreamScanAdapter: [<SendableRecordBatchStream>], schema: [Schema { fields: [Field { name: "number", data_type: UInt32 }], metadata: {"greptime:version": "0"} }] |
| | |
+---------------+-------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| | StreamScanAdapter: [<SendableRecordBatchStream>], schema: [Schema { fields: [Field { name: "number", data_type: UInt32 }], metadata: {"greptime:version": "0"} }] |
| | |
+---------------+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------+
-- SQLNESS REPLACE (peers.*) REDACTED
-- SQLNESS REPLACE (RoundRobinBatch.*) REDACTED
explain select * from numbers order by number desc;
+---------------+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| plan_type | plan |
+---------------+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| logical_plan | MergeScan [is_placeholder=false, remote_input=[ |
| | Sort: numbers.number DESC NULLS FIRST |
| | Projection: numbers.number |
| | TableScan: numbers |
| | ]] |
| physical_plan | SortPreservingMergeExec: [number@0 DESC] |
| | CooperativeExec |
| | SortExec: expr=[number@0 DESC], preserve_partitioning=[true] |
+---------------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| plan_type | plan |
+---------------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| logical_plan | MergeScan [is_placeholder=false, remote_input=[ |
| | Sort: numbers.number DESC NULLS FIRST |
| | Projection: numbers.number |
| | TableScan: numbers |
| | ]] |
| physical_plan | SortPreservingMergeExec: [number@0 DESC] |
| | CooperativeExec |
| | SortExec: expr=[number@0 DESC], preserve_partitioning=[true] |
| | RepartitionExec: partitioning=REDACTED
| | CooperativeExec |
| | StreamScanAdapter: [<SendableRecordBatchStream>], schema: [Schema { fields: [Field { name: "number", data_type: UInt32 }], metadata: {"greptime:version": "0"} }] |
| | |
+---------------+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| | StreamScanAdapter: [<SendableRecordBatchStream>], schema: [Schema { fields: [Field { name: "number", data_type: UInt32 }], metadata: {"greptime:version": "0"} }] |
| | |
+---------------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
-- SQLNESS REPLACE (peers.*) REDACTED
-- SQLNESS REPLACE (RoundRobinBatch.*) REDACTED
explain select * from numbers order by number asc;
+---------------+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| plan_type | plan |
+---------------+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| logical_plan | MergeScan [is_placeholder=false, remote_input=[ |
| | Sort: numbers.number ASC NULLS LAST |
| | Projection: numbers.number |
| | TableScan: numbers |
| | ]] |
| physical_plan | SortPreservingMergeExec: [number@0 ASC NULLS LAST] |
| | CooperativeExec |
| | SortExec: expr=[number@0 ASC NULLS LAST], preserve_partitioning=[true] |
+---------------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| plan_type | plan |
+---------------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| logical_plan | MergeScan [is_placeholder=false, remote_input=[ |
| | Sort: numbers.number ASC NULLS LAST |
| | Projection: numbers.number |
| | TableScan: numbers |
| | ]] |
| physical_plan | SortPreservingMergeExec: [number@0 ASC NULLS LAST] |
| | CooperativeExec |
| | SortExec: expr=[number@0 ASC NULLS LAST], preserve_partitioning=[true] |
| | RepartitionExec: partitioning=REDACTED
| | CooperativeExec |
| | StreamScanAdapter: [<SendableRecordBatchStream>], schema: [Schema { fields: [Field { name: "number", data_type: UInt32 }], metadata: {"greptime:version": "0"} }] |
| | |
+---------------+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| | StreamScanAdapter: [<SendableRecordBatchStream>], schema: [Schema { fields: [Field { name: "number", data_type: UInt32 }], metadata: {"greptime:version": "0"} }] |
| | |
+---------------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
-- SQLNESS REPLACE (peers.*) REDACTED
-- SQLNESS REPLACE (RoundRobinBatch.*) REDACTED
explain select * from numbers order by number desc limit 10;
+---------------+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| plan_type | plan |
+---------------+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| logical_plan | MergeScan [is_placeholder=false, remote_input=[ |
| | Limit: skip=0, fetch=10 |
| | Sort: numbers.number DESC NULLS FIRST |
| | Projection: numbers.number |
| | TableScan: numbers |
| | ]] |
| physical_plan | SortPreservingMergeExec: [number@0 DESC], fetch=10 |
| | CooperativeExec |
+---------------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| plan_type | plan |
+---------------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| logical_plan | MergeScan [is_placeholder=false, remote_input=[ |
| | Limit: skip=0, fetch=10 |
| | Sort: numbers.number DESC NULLS FIRST |
| | Projection: numbers.number |
| | TableScan: numbers |
| | ]] |
| physical_plan | SortPreservingMergeExec: [number@0 DESC], fetch=10 |
| | CooperativeExec |
| | RepartitionExec: partitioning=REDACTED
| | SortExec: TopK(fetch=10), expr=[number@0 DESC], preserve_partitioning=[false] |
| | CooperativeExec |
| | StreamScanAdapter: [<SendableRecordBatchStream>], schema: [Schema { fields: [Field { name: "number", data_type: UInt32 }], metadata: {"greptime:version": "0"} }] |
| | |
+---------------+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| | SortExec: TopK(fetch=10), expr=[number@0 DESC], preserve_partitioning=[false] |
| | StreamScanAdapter: [<SendableRecordBatchStream>], schema: [Schema { fields: [Field { name: "number", data_type: UInt32 }], metadata: {"greptime:version": "0"} }] |
| | |
+---------------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
-- SQLNESS REPLACE (peers.*) REDACTED
-- SQLNESS REPLACE (RoundRobinBatch.*) REDACTED
explain select * from numbers order by number asc limit 10;
+---------------+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| plan_type | plan |
+---------------+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| logical_plan | MergeScan [is_placeholder=false, remote_input=[ |
| | Limit: skip=0, fetch=10 |
| | Sort: numbers.number ASC NULLS LAST |
| | Projection: numbers.number |
| | TableScan: numbers |
| | ]] |
| physical_plan | SortPreservingMergeExec: [number@0 ASC NULLS LAST], fetch=10 |
| | CooperativeExec |
+---------------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| plan_type | plan |
+---------------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| logical_plan | MergeScan [is_placeholder=false, remote_input=[ |
| | Limit: skip=0, fetch=10 |
| | Sort: numbers.number ASC NULLS LAST |
| | Projection: numbers.number |
| | TableScan: numbers |
| | ]] |
| physical_plan | SortPreservingMergeExec: [number@0 ASC NULLS LAST], fetch=10 |
| | CooperativeExec |
| | RepartitionExec: partitioning=REDACTED
| | SortExec: TopK(fetch=10), expr=[number@0 ASC NULLS LAST], preserve_partitioning=[false] |
| | CooperativeExec |
| | StreamScanAdapter: [<SendableRecordBatchStream>], schema: [Schema { fields: [Field { name: "number", data_type: UInt32 }], metadata: {"greptime:version": "0"} }] |
| | |
+---------------+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| | SortExec: TopK(fetch=10), expr=[number@0 ASC NULLS LAST], preserve_partitioning=[false] |
| | StreamScanAdapter: [<SendableRecordBatchStream>], schema: [Schema { fields: [Field { name: "number", data_type: UInt32 }], metadata: {"greptime:version": "0"} }] |
| | |
+---------------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------+

4
tests/cases/distributed/optimizer/windowed_sort.result
View File

@@ -73,7 +73,6 @@ ORDER BY
| 1_| 0_|_ProjectionExec: expr=[collect_time_utc@0 as collect_time, peak_current@1 as peak_current] REDACTED
|_|_|_SortPreservingMergeExec: [collect_time_utc@0 ASC NULLS LAST] REDACTED
|_|_|_SortExec: expr=[collect_time_utc@0 ASC NULLS LAST], preserve_partitioning=[true] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":{"count":1, "mem_ranges":1, "files":0, "file_ranges":0} REDACTED
|_|_|_|
|_|_| Total rows: 8_|
@@ -124,7 +123,6 @@ ORDER BY
| 1_| 0_|_ProjectionExec: expr=[collect_time_utc@0 as collect_time_0, peak_current@1 as peak_current] REDACTED
|_|_|_SortPreservingMergeExec: [collect_time_utc@0 ASC NULLS LAST] REDACTED
|_|_|_SortExec: expr=[collect_time_utc@0 ASC NULLS LAST], preserve_partitioning=[true] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":{"count":1, "mem_ranges":1, "files":0, "file_ranges":0} REDACTED
|_|_|_|
|_|_| Total rows: 8_|
@@ -178,7 +176,6 @@ ORDER BY
|_|_|_SortPreservingMergeExec: [collect_time@0 DESC] REDACTED
|_|_|_WindowedSortExec: expr=collect_time@0 DESC num_ranges=REDACTED REDACTED
|_|_|_PartSortExec: expr=collect_time@0 DESC num_ranges=REDACTED REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":{"count":1, "mem_ranges":1, "files":0, "file_ranges":0} REDACTED
|_|_|_|
|_|_| Total rows: 8_|
@@ -233,7 +230,6 @@ ORDER BY
|_|_|_WindowedSortExec: expr=collect_time@1 DESC num_ranges=REDACTED REDACTED
|_|_|_PartSortExec: expr=collect_time@1 DESC num_ranges=REDACTED REDACTED
|_|_|_ProjectionExec: expr=[collect_time_utc@1 as collect_time_utc, collect_time@0 as collect_time, peak_current@2 as peak_current] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":{"count":1, "mem_ranges":1, "files":0, "file_ranges":0} REDACTED
|_|_|_|
|_|_| Total rows: 8_|

2
tests/cases/distributed/tql-explain-analyze/analyze.result
View File

@@ -160,7 +160,6 @@ TQL ANALYZE (0, 10, '5s') rate(test[10s]);
|_|_|_MergeScanExec: REDACTED
|_|_|_|
| 1_| 0_|_ProjectionExec: expr=[j@0 as j, prom_rate(j_range,i,test.j,Int64(10000))@1 as prom_rate(j_range,i,j,Int64(10000)), k@2 as k, l@3 as l] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_FilterExec: prom_rate(j_range,i,test.j,Int64(10000))@1 IS NOT NULL REDACTED
|_|_|_ProjectionExec: expr=[j@1 as j, prom_rate(j_range@4, i@0, j@1, 10000) as prom_rate(j_range,i,test.j,Int64(10000)), k@2 as k, l@3 as l] REDACTED
|_|_|_PromRangeManipulateExec: req range=[0..10000], interval=[5000], eval range=[10000], time index=[j] REDACTED
@@ -170,7 +169,6 @@ TQL ANALYZE (0, 10, '5s') rate(test[10s]);
|_|_|_SeriesScan: region=REDACTED, "partition_count":{"count":0, "mem_ranges":0, "files":0, "file_ranges":0}, "distribution":"PerSeries" REDACTED
|_|_|_|
| 1_| 1_|_ProjectionExec: expr=[j@0 as j, prom_rate(j_range,i,test.j,Int64(10000))@1 as prom_rate(j_range,i,j,Int64(10000)), k@2 as k, l@3 as l] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_FilterExec: prom_rate(j_range,i,test.j,Int64(10000))@1 IS NOT NULL REDACTED
|_|_|_ProjectionExec: expr=[j@1 as j, prom_rate(j_range@4, i@0, j@1, 10000) as prom_rate(j_range,i,test.j,Int64(10000)), k@2 as k, l@3 as l] REDACTED
|_|_|_PromRangeManipulateExec: req range=[0..10000], interval=[5000], eval range=[10000], time index=[j] REDACTED

14
tests/cases/standalone/common/aggregate/approx_percentile_cont_with_weight.result
View File

@@ -16,7 +16,7 @@ SELECT approx_percentile_cont_with_weight(weight, 0.5) WITHIN GROUP (ORDER BY "v
+---------------------------------------------------------------------------------------------------------------------+
| approx_percentile_cont_with_weight(weight_test.weight,Float64(0.5)) WITHIN GROUP [weight_test.value ASC NULLS LAST] |
+---------------------------------------------------------------------------------------------------------------------+
| 22 |
| 33 |
+---------------------------------------------------------------------------------------------------------------------+
-- Test different percentiles
@@ -25,7 +25,7 @@ SELECT approx_percentile_cont_with_weight(weight, 0.25) WITHIN GROUP (ORDER BY "
+----------------------------------------------------------------------------------------------------------------------+
| approx_percentile_cont_with_weight(weight_test.weight,Float64(0.25)) WITHIN GROUP [weight_test.value ASC NULLS LAST] |
+----------------------------------------------------------------------------------------------------------------------+
| 16 |
| 23 |
+----------------------------------------------------------------------------------------------------------------------+
SELECT approx_percentile_cont_with_weight(weight, 0.75) WITHIN GROUP (ORDER BY "value") FROM weight_test;
@@ -33,7 +33,7 @@ SELECT approx_percentile_cont_with_weight(weight, 0.75) WITHIN GROUP (ORDER BY "
+----------------------------------------------------------------------------------------------------------------------+
| approx_percentile_cont_with_weight(weight_test.weight,Float64(0.75)) WITHIN GROUP [weight_test.value ASC NULLS LAST] |
+----------------------------------------------------------------------------------------------------------------------+
| 44 |
| 40 |
+----------------------------------------------------------------------------------------------------------------------+
-- Test with groups
@@ -53,8 +53,8 @@ FROM weight_groups GROUP BY grp ORDER BY grp;
+-----+-------------------------------------------------------------------------------------------------------------------------+
| grp | approx_percentile_cont_with_weight(weight_groups.weight,Float64(0.5)) WITHIN GROUP [weight_groups.value ASC NULLS LAST] |
+-----+-------------------------------------------------------------------------------------------------------------------------+
| 1 | 12 |
| 2 | 162 |
| 1 | 18 |
| 2 | 212 |
+-----+-------------------------------------------------------------------------------------------------------------------------+
-- Test with double values and weights
@@ -72,7 +72,7 @@ SELECT approx_percentile_cont_with_weight("weight", 0.5) WITHIN GROUP (ORDER BY
+-------------------------------------------------------------------------------------------------------------------------+
| approx_percentile_cont_with_weight(weight_double.weight,Float64(0.5)) WITHIN GROUP [weight_double.value ASC NULLS LAST] |
+-------------------------------------------------------------------------------------------------------------------------+
| 3.3333333333333335 |
| 3.6666666666666665 |
+-------------------------------------------------------------------------------------------------------------------------+
-- Test edge cases
@@ -116,7 +116,7 @@ SELECT approx_percentile_cont_with_weight(weight, 0.5) WITHIN GROUP (ORDER BY "v
+---------------------------------------------------------------------------------------------------------------------+
| approx_percentile_cont_with_weight(weight_test.weight,Float64(0.5)) WITHIN GROUP [weight_test.value ASC NULLS LAST] |
+---------------------------------------------------------------------------------------------------------------------+
| 22 |
| 33 |
+---------------------------------------------------------------------------------------------------------------------+
-- Test empty result

4
tests/cases/standalone/common/aggregate/avg.result
View File

@@ -38,9 +38,7 @@ Affected Rows: 3
SELECT AVG(i), AVG(1), AVG(DISTINCT i), AVG(NULL) FROM integers;
Error: 3000(PlanQuery), Failed to plan SQL: Error during planning: Execution error: Function 'avg' user-defined coercion failed with "Error during planning: Avg does not support inputs of type Null." No function matches the given name and argument types 'avg(Null)'. You might need to add explicit type casts.
Candidate functions:
avg(UserDefined)
Error: 3001(EngineExecuteQuery), Execution error: AvgAccumulator for (Null --> Float64)
SELECT AVG(i) FROM integers WHERE i > 100;

19
tests/cases/standalone/common/aggregate/distinct.result
View File

@@ -96,10 +96,8 @@ EXPLAIN ANALYZE SELECT DISTINCT a FROM test ORDER BY a;
| 1_| 0_|_SortPreservingMergeExec: [a@0 ASC NULLS LAST] REDACTED
|_|_|_SortExec: expr=[a@0 ASC NULLS LAST], preserve_partitioning=[true] REDACTED
|_|_|_AggregateExec: mode=FinalPartitioned, gby=[a@0 as a], aggr=[] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: partitioning=REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[a@0 as a], aggr=[] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":{"count":1, "mem_ranges":1, "files":0, "file_ranges":0} REDACTED
|_|_|_|
|_|_| Total rows: 2_|
@@ -123,10 +121,8 @@ EXPLAIN ANALYZE SELECT DISTINCT a, b FROM test ORDER BY a;
| 1_| 0_|_SortPreservingMergeExec: [a@0 ASC NULLS LAST] REDACTED
|_|_|_SortExec: expr=[a@0 ASC NULLS LAST], preserve_partitioning=[true] REDACTED
|_|_|_AggregateExec: mode=FinalPartitioned, gby=[a@0 as a, b@1 as b], aggr=[] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: partitioning=REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[a@0 as a, b@1 as b], aggr=[] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":{"count":1, "mem_ranges":1, "files":0, "file_ranges":0} REDACTED
|_|_|_|
|_|_| Total rows: 3_|
@@ -174,21 +170,16 @@ EXPLAIN ANALYZE SELECT DISTINCT a FROM test ORDER BY a;
| 0_| 0_|_SortPreservingMergeExec: [a@0 ASC NULLS LAST] REDACTED
|_|_|_SortExec: expr=[a@0 ASC NULLS LAST], preserve_partitioning=[true] REDACTED
|_|_|_AggregateExec: mode=SinglePartitioned, gby=[a@0 as a], aggr=[] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_MergeScanExec: REDACTED
|_|_|_|
| 1_| 0_|_AggregateExec: mode=FinalPartitioned, gby=[a@0 as a], aggr=[] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: partitioning=REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[a@0 as a], aggr=[] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":{"count":1, "mem_ranges":1, "files":0, "file_ranges":0} REDACTED
|_|_|_|
| 1_| 1_|_AggregateExec: mode=FinalPartitioned, gby=[a@0 as a], aggr=[] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: partitioning=REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[a@0 as a], aggr=[] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":{"count":1, "mem_ranges":1, "files":0, "file_ranges":0} REDACTED
|_|_|_|
|_|_| Total rows: 2_|
@@ -208,25 +199,17 @@ EXPLAIN ANALYZE SELECT DISTINCT a, b FROM test ORDER BY a;
+-+-+-+
| 0_| 0_|_SortPreservingMergeExec: [a@0 ASC NULLS LAST] REDACTED
|_|_|_SortExec: expr=[a@0 ASC NULLS LAST], preserve_partitioning=[true] REDACTED
|_|_|_AggregateExec: mode=FinalPartitioned, gby=[a@0 as a, b@1 as b], aggr=[] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: partitioning=REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[a@0 as a, b@1 as b], aggr=[] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_AggregateExec: mode=SinglePartitioned, gby=[a@0 as a, b@1 as b], aggr=[] REDACTED
|_|_|_MergeScanExec: REDACTED
|_|_|_|
| 1_| 0_|_AggregateExec: mode=FinalPartitioned, gby=[a@0 as a, b@1 as b], aggr=[] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: partitioning=REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[a@0 as a, b@1 as b], aggr=[] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":{"count":1, "mem_ranges":1, "files":0, "file_ranges":0} REDACTED
|_|_|_|
| 1_| 1_|_AggregateExec: mode=FinalPartitioned, gby=[a@0 as a, b@1 as b], aggr=[] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: partitioning=REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[a@0 as a, b@1 as b], aggr=[] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":{"count":1, "mem_ranges":1, "files":0, "file_ranges":0} REDACTED
|_|_|_|
|_|_| Total rows: 4_|

13
tests/cases/standalone/common/aggregate/multi_regions.result
View File

@@ -32,18 +32,14 @@ select sum(val) from t group by host;
|_|_|_|
| 1_| 0_|_ProjectionExec: expr=[sum(t.val)@1 as sum(t.val)] REDACTED
|_|_|_AggregateExec: mode=FinalPartitioned, gby=[host@0 as host], aggr=[sum(t.val)] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: partitioning=REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[host@1 as host], aggr=[sum(t.val)] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
| 1_| 1_|_ProjectionExec: expr=[sum(t.val)@1 as sum(t.val)] REDACTED
|_|_|_AggregateExec: mode=FinalPartitioned, gby=[host@0 as host], aggr=[sum(t.val)] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: partitioning=REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[host@1 as host], aggr=[sum(t.val)] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
|_|_| Total rows: 0_|
@@ -66,19 +62,16 @@ select sum(val) from t;
| 0_| 0_|_AggregateExec: mode=Final, gby=[], aggr=[sum(t.val)] REDACTED
|_|_|_CoalescePartitionsExec REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[], aggr=[sum(t.val)] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_MergeScanExec: REDACTED
|_|_|_|
| 1_| 0_|_AggregateExec: mode=Final, gby=[], aggr=[__sum_state(t.val)] REDACTED
|_|_|_CoalescePartitionsExec REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[], aggr=[__sum_state(t.val)] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
| 1_| 1_|_AggregateExec: mode=Final, gby=[], aggr=[__sum_state(t.val)] REDACTED
|_|_|_CoalescePartitionsExec REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[], aggr=[__sum_state(t.val)] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
|_|_| Total rows: 1_|
@@ -101,24 +94,18 @@ select sum(val) from t group by idc;
+-+-+-+
| 0_| 0_|_ProjectionExec: expr=[sum(t.val)@1 as sum(t.val)] REDACTED
|_|_|_AggregateExec: mode=FinalPartitioned, gby=[idc@0 as idc], aggr=[sum(t.val)] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: partitioning=REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[idc@0 as idc], aggr=[sum(t.val)] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_MergeScanExec: REDACTED
|_|_|_|
| 1_| 0_|_AggregateExec: mode=FinalPartitioned, gby=[idc@0 as idc], aggr=[__sum_state(t.val)] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: partitioning=REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[idc@1 as idc], aggr=[__sum_state(t.val)] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
| 1_| 1_|_AggregateExec: mode=FinalPartitioned, gby=[idc@0 as idc], aggr=[__sum_state(t.val)] REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 REDACTED
|_|_|_RepartitionExec: partitioning=REDACTED
|_|_|_AggregateExec: mode=Partial, gby=[idc@1 as idc], aggr=[__sum_state(t.val)] REDACTED
|_|_|_CooperativeExec REDACTED
|_|_|_SeqScan: region=REDACTED, "partition_count":REDACTED REDACTED
|_|_|_|
|_|_| Total rows: 0_|

10
tests/cases/standalone/common/create/metric_engine_partition.result
View File

@@ -149,7 +149,6 @@ select host, count(*) from logical_table_2 GROUP BY host ORDER BY host;
|_|_SortExec: expr=[host@0 ASC NULLS LAST], preserve_partitioning=[true]_|
|_|_ProjectionExec: expr=[host@0 as host, count(Int64(1))@1 as count(*)]_|
|_|_AggregateExec: mode=SinglePartitioned, gby=[host@0 as host], aggr=[count(Int64(1))]_|
|_|_CooperativeExec_|
|_|_MergeScanExec: REDACTED
|_|_|
+-+-+
@@ -187,10 +186,8 @@ select ts, count(*) from logical_table_2 GROUP BY ts ORDER BY ts;
|_|_SortExec: expr=[ts@0 ASC NULLS LAST], preserve_partitioning=[true]_|
|_|_ProjectionExec: expr=[ts@0 as ts, count(Int64(1))@1 as count(*)]_|
|_|_AggregateExec: mode=FinalPartitioned, gby=[ts@0 as ts], aggr=[count(Int64(1))]_|
|_|_CoalesceBatchesExec: target_batch_size=8192_|
|_|_RepartitionExec: REDACTED
|_|_AggregateExec: mode=Partial, gby=[ts@0 as ts], aggr=[count(Int64(1))]_|
|_|_CooperativeExec_|
|_|_MergeScanExec: REDACTED
|_|_|
+-+-+
@@ -284,10 +281,8 @@ select a, count(*) from logical_table_3 GROUP BY a ORDER BY a;
|_|_SortExec: expr=[a@0 ASC NULLS LAST], preserve_partitioning=[true]_|
|_|_ProjectionExec: expr=[a@0 as a, count(Int64(1))@1 as count(*)]_|
|_|_AggregateExec: mode=FinalPartitioned, gby=[a@0 as a], aggr=[count(Int64(1))]_|
|_|_CoalesceBatchesExec: target_batch_size=8192_|
|_|_RepartitionExec: REDACTED
|_|_AggregateExec: mode=Partial, gby=[a@0 as a], aggr=[count(Int64(1))]_|
|_|_CooperativeExec_|
|_|_MergeScanExec: REDACTED
|_|_|
+-+-+
@@ -356,7 +351,7 @@ EXPLAIN select count(*) from logical_table_4;
| plan_type_| plan_|
+-+-+
| logical_plan_| Projection: count(Int64(1)) AS count(*)_|
|_|_Aggregate: groupBy=[[]], aggr=[[__count_merge(__count_state(logical_table_4.ts)) AS count(Int64(1))]]_|
|_|_Aggregate: groupBy=[[]], aggr=[[__count_merge(__count_state(logical_table_4.ts)) AS count(Int64(1))]] |
|_|_MergeScan [is_placeholder=false, remote_input=[_|
|_| Aggregate: groupBy=[[]], aggr=[[__count_state(logical_table_4.ts)]]_|
|_|_TableScan: logical_table_4_|
@@ -365,7 +360,6 @@ EXPLAIN select count(*) from logical_table_4;
|_|_AggregateExec: mode=Final, gby=[], aggr=[count(Int64(1))]_|
|_|_CoalescePartitionsExec_|
|_|_AggregateExec: mode=Partial, gby=[], aggr=[count(Int64(1))]_|
|_|_CooperativeExec_|
|_|_MergeScanExec: REDACTED
|_|_|
+-+-+
@@ -403,10 +397,8 @@ select ts, count(*) from logical_table_4 GROUP BY ts ORDER BY ts;
|_|_SortExec: expr=[ts@0 ASC NULLS LAST], preserve_partitioning=[true]_|
|_|_ProjectionExec: expr=[ts@0 as ts, count(Int64(1))@1 as count(*)]_|
|_|_AggregateExec: mode=FinalPartitioned, gby=[ts@0 as ts], aggr=[count(Int64(1))]_|
|_|_CoalesceBatchesExec: target_batch_size=8192_|
|_|_RepartitionExec: REDACTED
|_|_AggregateExec: mode=Partial, gby=[ts@0 as ts], aggr=[count(Int64(1))]_|
|_|_CooperativeExec_|
|_|_MergeScanExec: REDACTED
|_|_|
+-+-+

8
tests/cases/standalone/common/error/incorrect_sql.result
View File

@@ -18,9 +18,13 @@ Did you mean 'range_fn'?
-- Wrong aggregate parameters
SELECT SUM(42, 84, 11, 'hello');
Error: 3000(PlanQuery), Failed to plan SQL: Error during planning: Execution error: Function 'sum' user-defined coercion failed with "Execution error: sum function requires 1 argument, got 4" No function matches the given name and argument types 'sum(Int64, Int64, Int64, Utf8)'. You might need to add explicit type casts.
Error: 3000(PlanQuery), Failed to plan SQL: Error during planning: Execution error: Function 'sum' failed to match any signature, errors: Error during planning: Function 'sum' expects 1 arguments but received 4,Error during planning: Function 'sum' expects 1 arguments but received 4,Error during planning: Function 'sum' expects 1 arguments but received 4,Error during planning: Function 'sum' expects 1 arguments but received 4,Error during planning: Function 'sum' expects 1 arguments but received 4 No function matches the given name and argument types 'sum(Int64, Int64, Int64, Utf8)'. You might need to add explicit type casts.
Candidate functions:
sum(UserDefined)
sum(Coercion(TypeSignatureClass::Decimal))
sum(Coercion(TypeSignatureClass::Native(LogicalType(Native(UInt64), UInt64)), implicit_coercion=ImplicitCoercion([Native(LogicalType(Native(UInt8), UInt8)), Native(LogicalType(Native(UInt16), UInt16)), Native(LogicalType(Native(UInt32), UInt32))], default_type=UInt64))
sum(Coercion(TypeSignatureClass::Native(LogicalType(Native(Int64), Int64)), implicit_coercion=ImplicitCoercion([Native(LogicalType(Native(Int8), Int8)), Native(LogicalType(Native(Int16), Int16)), Native(LogicalType(Native(Int32), Int32))], default_type=Int64))
sum(Coercion(TypeSignatureClass::Native(LogicalType(Native(Float64), Float64)), implicit_coercion=ImplicitCoercion([Float], default_type=Float64))
sum(Coercion(TypeSignatureClass::Duration))
-- No matching function signature
SELECT cos(0, 1, 2, 3);

4
tests/cases/standalone/common/flow/flow_advance_ttl.result
View File

@@ -1,6 +1,6 @@
-- test ttl = instant
CREATE TABLE distinct_basic (
number INT,
"number" INT,
ts TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
PRIMARY KEY(number),
TIME INDEX(ts)
@@ -159,7 +159,7 @@ Affected Rows: 0
-- test ttl = 5s
CREATE TABLE distinct_basic (
number INT,
"number" INT,
ts TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
PRIMARY KEY(number),
TIME INDEX(ts)

4
tests/cases/standalone/common/flow/flow_advance_ttl.sql
View File

@@ -1,6 +1,6 @@
-- test ttl = instant
CREATE TABLE distinct_basic (
number INT,
"number" INT,
ts TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
PRIMARY KEY(number),
TIME INDEX(ts)
@@ -65,7 +65,7 @@ DROP TABLE out_distinct_basic;
-- test ttl = 5s
CREATE TABLE distinct_basic (
number INT,
"number" INT,
ts TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
PRIMARY KEY(number),
TIME INDEX(ts)

4
tests/cases/standalone/common/flow/flow_auto_sink_table.result
View File

@@ -1,5 +1,5 @@
CREATE TABLE numbers_input_basic (
number INT,
"number" INT,
ts TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
PRIMARY KEY(number),
TIME INDEX(ts)
@@ -96,7 +96,7 @@ DROP TABLE out_num_cnt_basic;
Affected Rows: 0
CREATE TABLE numbers_input_basic (
number INT,
"number" INT,
ts TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
PRIMARY KEY(number),
TIME INDEX(ts)

4
tests/cases/standalone/common/flow/flow_auto_sink_table.sql
View File

@@ -1,5 +1,5 @@
CREATE TABLE numbers_input_basic (
number INT,
"number" INT,
ts TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
PRIMARY KEY(number),
TIME INDEX(ts)
@@ -34,7 +34,7 @@ DROP TABLE numbers_input_basic;
DROP TABLE out_num_cnt_basic;
CREATE TABLE numbers_input_basic (
number INT,
"number" INT,
ts TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
PRIMARY KEY(number),
TIME INDEX(ts)

14
tests/cases/standalone/common/flow/flow_basic.result
View File

@@ -1,5 +1,5 @@
CREATE TABLE numbers_input_basic (
number INT,
"number" INT,
ts TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
PRIMARY KEY(number),
TIME INDEX(ts)
@@ -158,7 +158,7 @@ Affected Rows: 0
-- test count(*) rewrite
CREATE TABLE input_basic (
number INT,
"number" INT,
ts TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
PRIMARY KEY(number),
TIME INDEX(ts)
@@ -289,7 +289,7 @@ Affected Rows: 0
-- test distinct
CREATE TABLE distinct_basic (
number INT,
"number" INT,
ts TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
PRIMARY KEY(number),
TIME INDEX(ts)
@@ -1102,7 +1102,7 @@ Affected Rows: 0
CREATE TABLE ngx_access_log (
client STRING,
stat INT,
size INT,
"size" INT,
access_time TIMESTAMP TIME INDEX
)WITH(
append_mode = 'true'
@@ -1218,8 +1218,8 @@ FROM
| stat | bucket_size | total_logs | time_window |
+------+-------------+------------+---------------------+
| 200 | 100 | 1 | 1970-01-01T00:00:00 |
| 200 | 200 | 1 | 1970-01-01T00:00:00 |
| 200 | 210 | 3 | 1970-01-01T00:00:00 |
| 200 | 200 | 3 | 1970-01-01T00:00:00 |
| 200 | 210 | 1 | 1970-01-01T00:00:00 |
| 200 | 300 | 1 | 1970-01-01T00:00:00 |
+------+-------------+------------+---------------------+
@@ -1677,7 +1677,7 @@ DROP TABLE android_log;
Affected Rows: 0
CREATE TABLE numbers_input_basic (
number INT,
"number" INT,
ts TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
PRIMARY KEY(number),
TIME INDEX(ts)

10
tests/cases/standalone/common/flow/flow_basic.sql
View File

@@ -1,5 +1,5 @@
CREATE TABLE numbers_input_basic (
number INT,
"number" INT,
ts TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
PRIMARY KEY(number),
TIME INDEX(ts)
@@ -69,7 +69,7 @@ DROP TABLE out_num_cnt_basic;
-- test count(*) rewrite
CREATE TABLE input_basic (
number INT,
"number" INT,
ts TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
PRIMARY KEY(number),
TIME INDEX(ts)
@@ -116,7 +116,7 @@ DROP TABLE input_basic;
-- test distinct
CREATE TABLE distinct_basic (
number INT,
"number" INT,
ts TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
PRIMARY KEY(number),
TIME INDEX(ts)
@@ -497,7 +497,7 @@ DROP TABLE temp_alerts;
CREATE TABLE ngx_access_log (
client STRING,
stat INT,
size INT,
"size" INT,
access_time TIMESTAMP TIME INDEX
)WITH(
append_mode = 'true'
@@ -784,7 +784,7 @@ DROP TABLE android_log_abnormal;
DROP TABLE android_log;
CREATE TABLE numbers_input_basic (
number INT,
"number" INT,
ts TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
PRIMARY KEY(number),
TIME INDEX(ts)

8
tests/cases/standalone/common/flow/flow_call_df_func.result
View File

@@ -1,5 +1,5 @@
CREATE TABLE numbers_input_df_func (
number INT,
"number" INT,
ts TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
PRIMARY KEY(number),
TIME INDEX(ts)
@@ -98,7 +98,7 @@ DROP TABLE out_num_cnt_df_func;
Affected Rows: 0
CREATE TABLE numbers_input_df_func (
number INT,
"number" INT,
ts TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
PRIMARY KEY(number),
TIME INDEX(ts)
@@ -196,7 +196,7 @@ Affected Rows: 0
-- test date_bin
CREATE TABLE numbers_input_df_func (
number INT,
"number" INT,
ts TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
PRIMARY KEY(number),
TIME INDEX(ts)
@@ -292,7 +292,7 @@ Affected Rows: 0
-- test date_trunc
CREATE TABLE numbers_input_df_func (
number INT,
"number" INT,
ts TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
PRIMARY KEY(number),
TIME INDEX(ts)

8
tests/cases/standalone/common/flow/flow_call_df_func.sql
View File

@@ -1,5 +1,5 @@
CREATE TABLE numbers_input_df_func (
number INT,
"number" INT,
ts TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
PRIMARY KEY(number),
TIME INDEX(ts)
@@ -45,7 +45,7 @@ DROP TABLE numbers_input_df_func;
DROP TABLE out_num_cnt_df_func;
CREATE TABLE numbers_input_df_func (
number INT,
"number" INT,
ts TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
PRIMARY KEY(number),
TIME INDEX(ts)
@@ -90,7 +90,7 @@ DROP TABLE out_num_cnt_df_func;
-- test date_bin
CREATE TABLE numbers_input_df_func (
number INT,
"number" INT,
ts TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
PRIMARY KEY(number),
TIME INDEX(ts)
@@ -134,7 +134,7 @@ DROP TABLE out_num_cnt_df_func;
-- test date_trunc
CREATE TABLE numbers_input_df_func (
number INT,
"number" INT,
ts TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
PRIMARY KEY(number),
TIME INDEX(ts)

2
tests/cases/standalone/common/flow/flow_flush.result
View File

@@ -1,6 +1,6 @@
-- test if flush_flow works and flush old data to flow for compute
CREATE TABLE numbers_input_basic (
number INT,
"number" INT,
ts TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
PRIMARY KEY(number),
TIME INDEX(ts)

2
tests/cases/standalone/common/flow/flow_flush.sql
View File

@@ -1,6 +1,6 @@
-- test if flush_flow works and flush old data to flow for compute
CREATE TABLE numbers_input_basic (
number INT,
"number" INT,
ts TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
PRIMARY KEY(number),
TIME INDEX(ts)

16
tests/cases/standalone/common/flow/flow_rebuild.result
View File

@@ -1,5 +1,5 @@
CREATE TABLE input_basic (
number INT,
"number" INT,
ts TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
PRIMARY KEY(number),
TIME INDEX(ts)
@@ -56,7 +56,7 @@ Affected Rows: 0
-- combination of different order of rebuild input table/flow
CREATE TABLE input_basic (
number INT,
"number" INT,
ts TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
PRIMARY KEY(number),
TIME INDEX(ts)
@@ -102,7 +102,7 @@ DROP TABLE input_basic;
Affected Rows: 0
CREATE TABLE input_basic (
number INT,
"number" INT,
ts TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
PRIMARY KEY(number),
TIME INDEX(ts)
@@ -198,7 +198,7 @@ DROP TABLE out_basic;
Affected Rows: 0
CREATE TABLE input_basic (
number INT,
"number" INT,
ts TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
PRIMARY KEY(number),
TIME INDEX(ts)
@@ -295,7 +295,7 @@ DROP FLOW test_wildcard_basic;
Affected Rows: 0
CREATE TABLE input_basic (
number INT,
"number" INT,
ts TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
PRIMARY KEY(number),
TIME INDEX(ts)
@@ -362,7 +362,7 @@ Affected Rows: 0
-- combination of different order of rebuild input table/flow
CREATE TABLE input_basic (
number INT,
"number" INT,
ts TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
PRIMARY KEY(number),
TIME INDEX(ts)
@@ -420,7 +420,7 @@ DROP TABLE input_basic;
Affected Rows: 0
CREATE TABLE input_basic (
number INT,
"number" INT,
ts TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
PRIMARY KEY(number),
TIME INDEX(ts)
@@ -540,7 +540,7 @@ DROP TABLE out_basic;
Affected Rows: 0
CREATE TABLE input_basic (
number INT,
"number" INT,
ts TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
PRIMARY KEY(number),
TIME INDEX(ts)

16
tests/cases/standalone/common/flow/flow_rebuild.sql
View File

@@ -1,5 +1,5 @@
CREATE TABLE input_basic (
number INT,
"number" INT,
ts TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
PRIMARY KEY(number),
TIME INDEX(ts)
@@ -33,7 +33,7 @@ DROP FLOW test_wildcard_basic;
-- combination of different order of rebuild input table/flow
CREATE TABLE input_basic (
number INT,
"number" INT,
ts TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
PRIMARY KEY(number),
TIME INDEX(ts)
@@ -59,7 +59,7 @@ SELECT wildcard FROM out_basic;
DROP TABLE input_basic;
CREATE TABLE input_basic (
number INT,
"number" INT,
ts TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
PRIMARY KEY(number),
TIME INDEX(ts)
@@ -107,7 +107,7 @@ DROP FLOW test_wildcard_basic;
DROP TABLE out_basic;
CREATE TABLE input_basic (
number INT,
"number" INT,
ts TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
PRIMARY KEY(number),
TIME INDEX(ts)
@@ -159,7 +159,7 @@ DROP TABLE out_basic;
DROP FLOW test_wildcard_basic;
CREATE TABLE input_basic (
number INT,
"number" INT,
ts TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
PRIMARY KEY(number),
TIME INDEX(ts)
@@ -197,7 +197,7 @@ DROP FLOW test_wildcard_basic;
-- combination of different order of rebuild input table/flow
CREATE TABLE input_basic (
number INT,
"number" INT,
ts TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
PRIMARY KEY(number),
TIME INDEX(ts)
@@ -229,7 +229,7 @@ SELECT wildcard FROM out_basic;
DROP TABLE input_basic;
CREATE TABLE input_basic (
number INT,
"number" INT,
ts TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
PRIMARY KEY(number),
TIME INDEX(ts)
@@ -289,7 +289,7 @@ DROP FLOW test_wildcard_basic;
DROP TABLE out_basic;
CREATE TABLE input_basic (
number INT,
"number" INT,
ts TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
PRIMARY KEY(number),
TIME INDEX(ts)

2
tests/cases/standalone/common/flow/flow_user_guide.result
View File

@@ -497,7 +497,7 @@ Affected Rows: 0
CREATE TABLE ngx_access_log (
client STRING,
stat INT,
size INT,
"size" INT,
access_time TIMESTAMP TIME INDEX
);

2
tests/cases/standalone/common/flow/flow_user_guide.sql
View File

@@ -353,7 +353,7 @@ DROP TABLE temp_alerts;
CREATE TABLE ngx_access_log (
client STRING,
stat INT,
size INT,
"size" INT,
access_time TIMESTAMP TIME INDEX
);

8
tests/cases/standalone/common/flow/show_create_flow.result
View File

@@ -1,5 +1,5 @@
CREATE TABLE numbers_input_show (
number INT,
"number" INT,
ts TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
PRIMARY KEY(number),
TIME INDEX(ts)
@@ -8,7 +8,7 @@ CREATE TABLE numbers_input_show (
Affected Rows: 0
create table out_num_cnt_show (
number INT,
"number" INT,
ts TIMESTAMP DEFAULT CURRENT_TIMESTAMP TIME INDEX,
PRIMARY KEY(number),
);
@@ -350,7 +350,7 @@ drop table numbers_input_show;
Affected Rows: 0
CREATE TABLE numbers_input_show (
number INT,
"number" INT,
ts TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
PRIMARY KEY(number),
TIME INDEX(ts)
@@ -359,7 +359,7 @@ CREATE TABLE numbers_input_show (
Affected Rows: 0
create table out_num_cnt_show (
number INT,
"number" INT,
ts TIMESTAMP DEFAULT CURRENT_TIMESTAMP TIME INDEX,
PRIMARY KEY(number),
);

8
tests/cases/standalone/common/flow/show_create_flow.sql
View File

@@ -1,11 +1,11 @@
CREATE TABLE numbers_input_show (
number INT,
"number" INT,
ts TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
PRIMARY KEY(number),
TIME INDEX(ts)
);
create table out_num_cnt_show (
number INT,
"number" INT,
ts TIMESTAMP DEFAULT CURRENT_TIMESTAMP TIME INDEX,
PRIMARY KEY(number),
);
@@ -130,13 +130,13 @@ drop table out_num_cnt_show;
drop table numbers_input_show;
CREATE TABLE numbers_input_show (
number INT,
"number" INT,
ts TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
PRIMARY KEY(number),
TIME INDEX(ts)
);
create table out_num_cnt_show (
number INT,
"number" INT,
ts TIMESTAMP DEFAULT CURRENT_TIMESTAMP TIME INDEX,
PRIMARY KEY(number),
);

2
tests/cases/standalone/common/function/arithmetic.result
View File

@@ -31,7 +31,7 @@ SELECT POW (2, 5);
+------------------------+
| pow(Int64(2),Int64(5)) |
+------------------------+
| 32 |
| 32.0 |
+------------------------+
SELECT POW (1.01, 365);

2
tests/cases/standalone/common/function/vector/vector_index.result
View File

@@ -332,7 +332,7 @@ Affected Rows: 0
-- ============================================
CREATE TABLE vectors_filter (
vec_id INT,
category STRING,
"category" STRING,
ts TIMESTAMP TIME INDEX,
embedding VECTOR(4) NOT NULL VECTOR INDEX WITH (metric = 'l2sq'),
PRIMARY KEY (vec_id)

2
tests/cases/standalone/common/function/vector/vector_index.sql
View File

@@ -197,7 +197,7 @@ DROP TABLE vectors_mixed;
CREATE TABLE vectors_filter (
vec_id INT,
category STRING,
"category" STRING,
ts TIMESTAMP TIME INDEX,
embedding VECTOR(4) NOT NULL VECTOR INDEX WITH (metric = 'l2sq'),
PRIMARY KEY (vec_id)

8
tests/cases/standalone/common/function/vector/vector_index_explain.result
View File

@@ -56,7 +56,6 @@ LIMIT 2;
| 1_| 0_|_ProjectionExec: expr=[vec_id@0 as vec_id] metrics=REDACTED_|
|_|_|_SortPreservingMergeExec: [vec_l2sq_distance(embedding@1, [1.0, 0.0]) ASC NULLS LAST, vec_id@0 ASC NULLS LAST], fetch=2 metrics=REDACTED_|
|_|_|_SortExec: TopK(fetch=2), expr=[vec_l2sq_distance(embedding@1, [1.0, 0.0]) ASC NULLS LAST, vec_id@0 ASC NULLS LAST], preserve_partitioning=[true] metrics=REDACTED_|
|_|_|_CooperativeExec metrics=REDACTED_|
|_|_|_SeqScan: region=REDACTED, {"partition_count":{"count":1, "mem_ranges":0, "files":1, "file_ranges":1}, "projection": ["vec_id", "embedding"], "vector_index_k": 2, "files": [{"file_id":"REDACTED","time_range_start":"REDACTED","time_range_end":"REDACTED","rows":4,"size":REDACTED,"index_size":893}], "flat_format":REDACTED, "metrics_per_partition": REDACTED metrics=REDACTED |
|_|_|_|
|_|_| Total rows: REDACTED_|
@@ -136,17 +135,12 @@ LIMIT 1;
| 0_| 0_|_ProjectionExec: expr=[vec_id@0 as vec_id] metrics=REDACTED_|
|_|_|_SortPreservingMergeExec: [vec_l2sq_distance(embedding@1, [1.0, 0.0]) ASC NULLS LAST, vec_id@0 ASC NULLS LAST], fetch=1 metrics=REDACTED_|
|_|_|_SortExec: TopK(fetch=1), expr=[vec_l2sq_distance(embedding@1, [1.0, 0.0]) ASC NULLS LAST, vec_id@0 ASC NULLS LAST], preserve_partitioning=[true] metrics=REDACTED_|
|_|_|_CoalesceBatchesExec: target_batch_size=8192 metrics=REDACTED_|
|_|_|_HashJoinExec: mode=Partitioned, join_type=Inner, on=[(vec_id@0, vec_id@0)], projection=[vec_id@0, embedding@1] metrics=REDACTED_|
|_|_|_CoalesceBatchesExec: target_batch_size=8192 metrics=REDACTED_|
|_|_|_RepartitionExec: partitioning=Hash([vec_id@0],REDACTED
|_|_|_ProjectionExec: expr=[vec_id@0 as vec_id, embedding@2 as embedding] metrics=REDACTED_|
|_|_|_CooperativeExec metrics=REDACTED_|
|_|_|_MergeScanExec: REDACTED
|_|_|_CoalesceBatchesExec: target_batch_size=8192 metrics=REDACTED_|
|_|_|_RepartitionExec: partitioning=Hash([vec_id@0],REDACTED
|_|_|_ProjectionExec: expr=[vec_id@0 as vec_id] metrics=REDACTED_|
|_|_|_CooperativeExec metrics=REDACTED_|
|_|_|_MergeScanExec: REDACTED
|_|_|_|
| 1_| 0_|_CooperativeExec metrics=REDACTED_|
@@ -223,7 +217,6 @@ LIMIT 2;
| 1_| 0_|_ProjectionExec: expr=[vec_id@0 as vec_id] metrics=REDACTED_|
|_|_|_SortPreservingMergeExec: [vec_cos_distance(embedding@1, [1.0, 0.0]) ASC NULLS LAST, vec_id@0 ASC NULLS LAST], fetch=2 metrics=REDACTED_|
|_|_|_SortExec: TopK(fetch=2), expr=[vec_cos_distance(embedding@1, [1.0, 0.0]) ASC NULLS LAST, vec_id@0 ASC NULLS LAST], preserve_partitioning=[true] metrics=REDACTED_|
|_|_|_CooperativeExec metrics=REDACTED_|
|_|_|_SeqScan: region=REDACTED, {"partition_count":{"count":1, "mem_ranges":0, "files":1, "file_ranges":1}, "projection": ["vec_id", "embedding"], "vector_index_k": 2, "files": [{"file_id":"REDACTED","time_range_start":"REDACTED","time_range_end":"REDACTED","rows":4,"size":REDACTED,"index_size":895}], "flat_format":REDACTED, "metrics_per_partition": REDACTED metrics=REDACTED |
|_|_|_|
|_|_| Total rows: REDACTED_|
@@ -258,7 +251,6 @@ LIMIT 2;
| 1_| 0_|_ProjectionExec: expr=[vec_id@0 as vec_id] metrics=REDACTED_|
|_|_|_SortPreservingMergeExec: [vec_dot_product(embedding@1, [1.0, 0.0]) DESC, vec_id@0 ASC NULLS LAST], fetch=2 metrics=REDACTED_|
|_|_|_SortExec: TopK(fetch=2), expr=[vec_dot_product(embedding@1, [1.0, 0.0]) DESC, vec_id@0 ASC NULLS LAST], preserve_partitioning=[true] metrics=REDACTED_|
|_|_|_CooperativeExec metrics=REDACTED_|
|_|_|_SeqScan: region=REDACTED, {"partition_count":{"count":1, "mem_ranges":0, "files":1, "file_ranges":1}, "projection": ["vec_id", "embedding"], "vector_index_k": 2, "files": [{"file_id":"REDACTED","time_range_start":"REDACTED","time_range_end":"REDACTED","rows":4,"size":REDACTED,"index_size":895}], "flat_format":REDACTED, "metrics_per_partition": REDACTED metrics=REDACTED |
|_|_|_|
|_|_| Total rows: REDACTED_|

2
tests/cases/standalone/common/join/join_distinct.result
View File

@@ -1,5 +1,5 @@
-- Tests joins with DISTINCT operations
CREATE TABLE products_dist(prod_id INTEGER, prod_name VARCHAR, category VARCHAR, ts TIMESTAMP TIME INDEX);
CREATE TABLE products_dist(prod_id INTEGER, prod_name VARCHAR, "category" VARCHAR, ts TIMESTAMP TIME INDEX);
Affected Rows: 0

2
tests/cases/standalone/common/join/join_distinct.sql
View File

@@ -1,6 +1,6 @@
-- Tests joins with DISTINCT operations
CREATE TABLE products_dist(prod_id INTEGER, prod_name VARCHAR, category VARCHAR, ts TIMESTAMP TIME INDEX);
CREATE TABLE products_dist(prod_id INTEGER, prod_name VARCHAR, "category" VARCHAR, ts TIMESTAMP TIME INDEX);
CREATE TABLE sales_dist(sale_id INTEGER, prod_id INTEGER, customer VARCHAR, ts TIMESTAMP TIME INDEX);

4
tests/cases/standalone/common/join/join_null_handling.result
View File

@@ -1,10 +1,10 @@
-- Migrated from DuckDB test: test/sql/join/ NULL handling tests
-- Tests join behavior with NULL values
CREATE TABLE table_with_nulls("id" INTEGER, "value" VARCHAR, category INTEGER, ts TIMESTAMP TIME INDEX);
CREATE TABLE table_with_nulls("id" INTEGER, "value" VARCHAR, "category" INTEGER, ts TIMESTAMP TIME INDEX);
Affected Rows: 0
CREATE TABLE lookup_table(category INTEGER, cat_name VARCHAR, priority INTEGER, ts TIMESTAMP TIME INDEX);
CREATE TABLE lookup_table("category" INTEGER, cat_name VARCHAR, priority INTEGER, ts TIMESTAMP TIME INDEX);
Affected Rows: 0

4
tests/cases/standalone/common/join/join_null_handling.sql
View File

@@ -1,9 +1,9 @@
-- Migrated from DuckDB test: test/sql/join/ NULL handling tests
-- Tests join behavior with NULL values
CREATE TABLE table_with_nulls("id" INTEGER, "value" VARCHAR, category INTEGER, ts TIMESTAMP TIME INDEX);
CREATE TABLE table_with_nulls("id" INTEGER, "value" VARCHAR, "category" INTEGER, ts TIMESTAMP TIME INDEX);
CREATE TABLE lookup_table(category INTEGER, cat_name VARCHAR, priority INTEGER, ts TIMESTAMP TIME INDEX);
CREATE TABLE lookup_table("category" INTEGER, cat_name VARCHAR, priority INTEGER, ts TIMESTAMP TIME INDEX);
INSERT INTO table_with_nulls VALUES
(1, 'item1', 1, 1000), (2, 'item2', NULL, 2000), (3, 'item3', 2, 3000),

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