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Author SHA1 Message Date
Paul Masurel
ebb82dc549 clippy 2025-10-08 17:07:07 +02:00
54 changed files with 1566 additions and 5219 deletions

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@@ -69,7 +69,6 @@ hyperloglogplus = { version = "0.4.1", features = ["const-loop"] }
futures-util = { version = "0.3.28", optional = true }
futures-channel = { version = "0.3.28", optional = true }
fnv = "1.0.7"
typetag = "0.2.21"
[target.'cfg(windows)'.dependencies]
winapi = "0.3.9"
@@ -88,7 +87,7 @@ more-asserts = "0.3.1"
rand_distr = "0.4.3"
time = { version = "0.3.10", features = ["serde-well-known", "macros"] }
postcard = { version = "1.0.4", features = [
"use-std",
"use-std",
], default-features = false }
[target.'cfg(not(windows))'.dev-dependencies]
@@ -176,3 +175,4 @@ harness = false
[[bench]]
name = "and_or_queries"
harness = false

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@@ -23,6 +23,8 @@ performance for different types of queries/collections.
Your mileage WILL vary depending on the nature of queries and their load.
<img src="doc/assets/images/searchbenchmark.png">
Details about the benchmark can be found at this [repository](https://github.com/quickwit-oss/search-benchmark-game).
## Features

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@@ -71,15 +71,8 @@ fn bench_agg(mut group: InputGroup<Index>) {
register!(group, histogram);
register!(group, histogram_hard_bounds);
register!(group, histogram_with_avg_sub_agg);
register!(group, histogram_with_term_agg_few);
register!(group, avg_and_range_with_avg_sub_agg);
// Filter aggregation benchmarks
register!(group, filter_agg_all_query_count_agg);
register!(group, filter_agg_term_query_count_agg);
register!(group, filter_agg_all_query_with_sub_aggs);
register!(group, filter_agg_term_query_with_sub_aggs);
group.run();
}
@@ -346,17 +339,6 @@ fn histogram_with_avg_sub_agg(index: &Index) {
});
execute_agg(index, agg_req);
}
fn histogram_with_term_agg_few(index: &Index) {
let agg_req = json!({
"rangef64": {
"histogram": { "field": "score_f64", "interval": 10 },
"aggs": {
"my_texts": { "terms": { "field": "text_few_terms" } }
}
}
});
execute_agg(index, agg_req);
}
fn avg_and_range_with_avg_sub_agg(index: &Index) {
let agg_req = json!({
"rangef64": {
@@ -478,61 +460,3 @@ fn get_test_index_bench(cardinality: Cardinality) -> tantivy::Result<Index> {
Ok(index)
}
// Filter aggregation benchmarks
fn filter_agg_all_query_count_agg(index: &Index) {
let agg_req = json!({
"filtered": {
"filter": "*",
"aggs": {
"count": { "value_count": { "field": "score" } }
}
}
});
execute_agg(index, agg_req);
}
fn filter_agg_term_query_count_agg(index: &Index) {
let agg_req = json!({
"filtered": {
"filter": "text:cool",
"aggs": {
"count": { "value_count": { "field": "score" } }
}
}
});
execute_agg(index, agg_req);
}
fn filter_agg_all_query_with_sub_aggs(index: &Index) {
let agg_req = json!({
"filtered": {
"filter": "*",
"aggs": {
"avg_score": { "avg": { "field": "score" } },
"stats_score": { "stats": { "field": "score_f64" } },
"terms_text": {
"terms": { "field": "text_few_terms" }
}
}
}
});
execute_agg(index, agg_req);
}
fn filter_agg_term_query_with_sub_aggs(index: &Index) {
let agg_req = json!({
"filtered": {
"filter": "text:cool",
"aggs": {
"avg_score": { "avg": { "field": "score" } },
"stats_score": { "stats": { "field": "score_f64" } },
"terms_text": {
"terms": { "field": "text_few_terms" }
}
}
}
});
execute_agg(index, agg_req);
}

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@@ -29,6 +29,7 @@ impl BinarySerializable for VIntU128 {
}
fn deserialize<R: Read>(reader: &mut R) -> io::Result<Self> {
#[allow(clippy::unbuffered_bytes)]
let mut bytes = reader.bytes();
let mut result = 0u128;
let mut shift = 0u64;
@@ -52,7 +53,7 @@ impl BinarySerializable for VIntU128 {
}
}
/// Wrapper over a `u64` that serializes as a variable int.
/// Wrapper over a `u64` that serializes as a variable int.
#[derive(Clone, Copy, Debug, Eq, PartialEq)]
pub struct VInt(pub u64);
@@ -196,6 +197,7 @@ impl BinarySerializable for VInt {
}
fn deserialize<R: Read>(reader: &mut R) -> io::Result<Self> {
#[allow(clippy::unbuffered_bytes)]
let mut bytes = reader.bytes();
let mut result = 0u64;
let mut shift = 0u64;

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After

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@@ -1,212 +0,0 @@
// # Filter Aggregation Example
//
// This example demonstrates filter aggregations - creating buckets of documents
// matching specific queries, with nested aggregations computed on each bucket.
//
// Filter aggregations are useful for computing metrics on different subsets of
// your data in a single query, like "average price overall + average price for
// electronics + count of in-stock items".
use serde_json::json;
use tantivy::aggregation::agg_req::Aggregations;
use tantivy::aggregation::AggregationCollector;
use tantivy::query::AllQuery;
use tantivy::schema::{Schema, FAST, INDEXED, TEXT};
use tantivy::{doc, Index};
fn main() -> tantivy::Result<()> {
// Create a simple product schema
let mut schema_builder = Schema::builder();
schema_builder.add_text_field("category", TEXT | FAST);
schema_builder.add_text_field("brand", TEXT | FAST);
schema_builder.add_u64_field("price", FAST);
schema_builder.add_f64_field("rating", FAST);
schema_builder.add_bool_field("in_stock", FAST | INDEXED);
let schema = schema_builder.build();
// Create index and add sample products
let index = Index::create_in_ram(schema.clone());
let mut writer = index.writer(50_000_000)?;
writer.add_document(doc!(
schema.get_field("category")? => "electronics",
schema.get_field("brand")? => "apple",
schema.get_field("price")? => 999u64,
schema.get_field("rating")? => 4.5f64,
schema.get_field("in_stock")? => true
))?;
writer.add_document(doc!(
schema.get_field("category")? => "electronics",
schema.get_field("brand")? => "samsung",
schema.get_field("price")? => 799u64,
schema.get_field("rating")? => 4.2f64,
schema.get_field("in_stock")? => true
))?;
writer.add_document(doc!(
schema.get_field("category")? => "clothing",
schema.get_field("brand")? => "nike",
schema.get_field("price")? => 120u64,
schema.get_field("rating")? => 4.1f64,
schema.get_field("in_stock")? => false
))?;
writer.add_document(doc!(
schema.get_field("category")? => "books",
schema.get_field("brand")? => "penguin",
schema.get_field("price")? => 25u64,
schema.get_field("rating")? => 4.8f64,
schema.get_field("in_stock")? => true
))?;
writer.commit()?;
let reader = index.reader()?;
let searcher = reader.searcher();
// Example 1: Basic filter with metric aggregation
println!("=== Example 1: Electronics average price ===");
let agg_req = json!({
"electronics": {
"filter": "category:electronics",
"aggs": {
"avg_price": { "avg": { "field": "price" } }
}
}
});
let agg: Aggregations = serde_json::from_value(agg_req)?;
let collector = AggregationCollector::from_aggs(agg, Default::default());
let result = searcher.search(&AllQuery, &collector)?;
let expected = json!({
"electronics": {
"doc_count": 2,
"avg_price": { "value": 899.0 }
}
});
assert_eq!(serde_json::to_value(&result)?, expected);
println!("{}\n", serde_json::to_string_pretty(&result)?);
// Example 2: Multiple independent filters
println!("=== Example 2: Multiple filters in one query ===");
let agg_req = json!({
"electronics": {
"filter": "category:electronics",
"aggs": { "avg_price": { "avg": { "field": "price" } } }
},
"in_stock": {
"filter": "in_stock:true",
"aggs": { "count": { "value_count": { "field": "brand" } } }
},
"high_rated": {
"filter": "rating:[4.5 TO *]",
"aggs": { "count": { "value_count": { "field": "brand" } } }
}
});
let agg: Aggregations = serde_json::from_value(agg_req)?;
let collector = AggregationCollector::from_aggs(agg, Default::default());
let result = searcher.search(&AllQuery, &collector)?;
let expected = json!({
"electronics": {
"doc_count": 2,
"avg_price": { "value": 899.0 }
},
"in_stock": {
"doc_count": 3,
"count": { "value": 3.0 }
},
"high_rated": {
"doc_count": 2,
"count": { "value": 2.0 }
}
});
assert_eq!(serde_json::to_value(&result)?, expected);
println!("{}\n", serde_json::to_string_pretty(&result)?);
// Example 3: Nested filters - progressive refinement
println!("=== Example 3: Nested filters ===");
let agg_req = json!({
"in_stock": {
"filter": "in_stock:true",
"aggs": {
"electronics": {
"filter": "category:electronics",
"aggs": {
"expensive": {
"filter": "price:[800 TO *]",
"aggs": {
"avg_rating": { "avg": { "field": "rating" } }
}
}
}
}
}
}
});
let agg: Aggregations = serde_json::from_value(agg_req)?;
let collector = AggregationCollector::from_aggs(agg, Default::default());
let result = searcher.search(&AllQuery, &collector)?;
let expected = json!({
"in_stock": {
"doc_count": 3, // apple, samsung, penguin
"electronics": {
"doc_count": 2, // apple, samsung
"expensive": {
"doc_count": 1, // only apple (999)
"avg_rating": { "value": 4.5 }
}
}
}
});
assert_eq!(serde_json::to_value(&result)?, expected);
println!("{}\n", serde_json::to_string_pretty(&result)?);
// Example 4: Filter with sub-aggregation (terms)
println!("=== Example 4: Filter with terms sub-aggregation ===");
let agg_req = json!({
"electronics": {
"filter": "category:electronics",
"aggs": {
"by_brand": {
"terms": { "field": "brand" },
"aggs": {
"avg_price": { "avg": { "field": "price" } }
}
}
}
}
});
let agg: Aggregations = serde_json::from_value(agg_req)?;
let collector = AggregationCollector::from_aggs(agg, Default::default());
let result = searcher.search(&AllQuery, &collector)?;
let expected = json!({
"electronics": {
"doc_count": 2,
"by_brand": {
"buckets": [
{
"key": "samsung",
"doc_count": 1,
"avg_price": { "value": 799.0 }
},
{
"key": "apple",
"doc_count": 1,
"avg_price": { "value": 999.0 }
}
],
"sum_other_doc_count": 0,
"doc_count_error_upper_bound": 0
}
}
});
assert_eq!(serde_json::to_value(&result)?, expected);
println!("{}", serde_json::to_string_pretty(&result)?);
Ok(())
}

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@@ -85,6 +85,7 @@ fn main() -> tantivy::Result<()> {
index_writer.add_document(doc!(
title => "The Diary of a Young Girl",
))?;
index_writer.commit()?;
// ### Committing
//

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@@ -20,16 +20,17 @@ Contains all metric aggregations, like average aggregation. Metric aggregations
#### agg_req
agg_req contains the users aggregation request. Deserialization from json is compatible with elasticsearch aggregation requests.
#### agg_data
agg_data contains the users aggregation request enriched with fast field accessors etc, which are
#### agg_req_with_accessor
agg_req_with_accessor contains the users aggregation request enriched with fast field accessors etc, which are
used during collection.
#### segment_agg_result
segment_agg_result contains the aggregation result tree, which is used for collection of a segment.
agg_data is passed during collection.
The tree from agg_req_with_accessor is passed during collection.
#### intermediate_agg_result
intermediate_agg_result contains the aggregation tree for merging with other trees.
#### agg_result
agg_result contains the final aggregation tree.

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@@ -1,104 +0,0 @@
//! This will enhance the request tree with access to the fastfield and metadata.
use std::io;
use columnar::{Column, ColumnType};
use crate::aggregation::{f64_to_fastfield_u64, Key};
use crate::index::SegmentReader;
/// Get the missing value as internal u64 representation
///
/// For terms we use u64::MAX as sentinel value
/// For numerical data we convert the value into the representation
/// we would get from the fast field, when we open it as u64_lenient_for_type.
///
/// That way we can use it the same way as if it would come from the fastfield.
pub(crate) fn get_missing_val_as_u64_lenient(
column_type: ColumnType,
missing: &Key,
field_name: &str,
) -> crate::Result<Option<u64>> {
let missing_val = match missing {
Key::Str(_) if column_type == ColumnType::Str => Some(u64::MAX),
// Allow fallback to number on text fields
Key::F64(_) if column_type == ColumnType::Str => Some(u64::MAX),
Key::U64(_) if column_type == ColumnType::Str => Some(u64::MAX),
Key::I64(_) if column_type == ColumnType::Str => Some(u64::MAX),
Key::F64(val) if column_type.numerical_type().is_some() => {
f64_to_fastfield_u64(*val, &column_type)
}
// NOTE: We may loose precision of the passed missing value by casting i64 and u64 to f64.
Key::I64(val) if column_type.numerical_type().is_some() => {
f64_to_fastfield_u64(*val as f64, &column_type)
}
Key::U64(val) if column_type.numerical_type().is_some() => {
f64_to_fastfield_u64(*val as f64, &column_type)
}
_ => {
return Err(crate::TantivyError::InvalidArgument(format!(
"Missing value {missing:?} for field {field_name} is not supported for column \
type {column_type:?}"
)));
}
};
Ok(missing_val)
}
pub(crate) fn get_numeric_or_date_column_types() -> &'static [ColumnType] {
&[
ColumnType::F64,
ColumnType::U64,
ColumnType::I64,
ColumnType::DateTime,
]
}
/// Get fast field reader or empty as default.
pub(crate) fn get_ff_reader(
reader: &SegmentReader,
field_name: &str,
allowed_column_types: Option<&[ColumnType]>,
) -> crate::Result<(columnar::Column<u64>, ColumnType)> {
let ff_fields = reader.fast_fields();
let ff_field_with_type = ff_fields
.u64_lenient_for_type(allowed_column_types, field_name)?
.unwrap_or_else(|| {
(
Column::build_empty_column(reader.num_docs()),
ColumnType::U64,
)
});
Ok(ff_field_with_type)
}
pub(crate) fn get_dynamic_columns(
reader: &SegmentReader,
field_name: &str,
) -> crate::Result<Vec<columnar::DynamicColumn>> {
let ff_fields = reader.fast_fields().dynamic_column_handles(field_name)?;
let cols = ff_fields
.iter()
.map(|h| h.open())
.collect::<io::Result<_>>()?;
assert!(!ff_fields.is_empty(), "field {field_name} not found");
Ok(cols)
}
/// Get all fast field reader or empty as default.
///
/// Is guaranteed to return at least one column.
pub(crate) fn get_all_ff_reader_or_empty(
reader: &SegmentReader,
field_name: &str,
allowed_column_types: Option<&[ColumnType]>,
fallback_type: ColumnType,
) -> crate::Result<Vec<(columnar::Column<u64>, ColumnType)>> {
let ff_fields = reader.fast_fields();
let mut ff_field_with_type =
ff_fields.u64_lenient_for_type_all(allowed_column_types, field_name)?;
if ff_field_with_type.is_empty() {
ff_field_with_type.push((Column::build_empty_column(reader.num_docs()), fallback_type));
}
Ok(ff_field_with_type)
}

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@@ -70,7 +70,7 @@ impl AggregationLimitsGuard {
/// *memory_limit*
/// memory_limit is defined in bytes.
/// Aggregation fails when the estimated memory consumption of the aggregation is higher than
/// memory_limit.
/// memory_limit.
/// memory_limit will default to `DEFAULT_MEMORY_LIMIT` (500MB)
///
/// *bucket_limit*

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@@ -26,14 +26,12 @@
//! let _agg_req: Aggregations = serde_json::from_str(elasticsearch_compatible_json_req).unwrap();
//! ```
use std::collections::HashSet;
use std::collections::{HashMap, HashSet};
use rustc_hash::FxHashMap;
use serde::{Deserialize, Serialize};
use super::bucket::{
DateHistogramAggregationReq, FilterAggregation, HistogramAggregation, RangeAggregation,
TermsAggregation,
DateHistogramAggregationReq, HistogramAggregation, RangeAggregation, TermsAggregation,
};
use super::metric::{
AverageAggregation, CardinalityAggregationReq, CountAggregation, ExtendedStatsAggregation,
@@ -45,7 +43,7 @@ use super::metric::{
/// defined names. It is also used in buckets aggregations to define sub-aggregations.
///
/// The key is the user defined name of the aggregation.
pub type Aggregations = FxHashMap<String, Aggregation>;
pub type Aggregations = HashMap<String, Aggregation>;
/// Aggregation request.
///
@@ -131,9 +129,6 @@ pub enum AggregationVariants {
/// Put data into buckets of terms.
#[serde(rename = "terms")]
Terms(TermsAggregation),
/// Filter documents into a single bucket.
#[serde(rename = "filter")]
Filter(FilterAggregation),
// Metric aggregation types
/// Computes the average of the extracted values.
@@ -179,7 +174,6 @@ impl AggregationVariants {
AggregationVariants::Range(range) => vec![range.field.as_str()],
AggregationVariants::Histogram(histogram) => vec![histogram.field.as_str()],
AggregationVariants::DateHistogram(histogram) => vec![histogram.field.as_str()],
AggregationVariants::Filter(filter) => filter.get_fast_field_names(),
AggregationVariants::Average(avg) => vec![avg.field_name()],
AggregationVariants::Count(count) => vec![count.field_name()],
AggregationVariants::Max(max) => vec![max.field_name()],
@@ -214,6 +208,13 @@ impl AggregationVariants {
_ => None,
}
}
pub(crate) fn as_top_hits(&self) -> Option<&TopHitsAggregationReq> {
match &self {
AggregationVariants::TopHits(top_hits) => Some(top_hits),
_ => None,
}
}
pub(crate) fn as_percentile(&self) -> Option<&PercentilesAggregationReq> {
match &self {
AggregationVariants::Percentiles(percentile_req) => Some(percentile_req),

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@@ -0,0 +1,471 @@
//! This will enhance the request tree with access to the fastfield and metadata.
use std::collections::HashMap;
use std::io;
use columnar::{Column, ColumnBlockAccessor, ColumnType, DynamicColumn, StrColumn};
use super::agg_req::{Aggregation, AggregationVariants, Aggregations};
use super::bucket::{
DateHistogramAggregationReq, HistogramAggregation, RangeAggregation, TermsAggregation,
};
use super::metric::{
AverageAggregation, CardinalityAggregationReq, CountAggregation, ExtendedStatsAggregation,
MaxAggregation, MinAggregation, StatsAggregation, SumAggregation,
};
use super::segment_agg_result::AggregationLimitsGuard;
use super::VecWithNames;
use crate::aggregation::{f64_to_fastfield_u64, Key};
use crate::index::SegmentReader;
use crate::SegmentOrdinal;
#[derive(Default)]
pub(crate) struct AggregationsWithAccessor {
pub aggs: VecWithNames<AggregationWithAccessor>,
}
impl AggregationsWithAccessor {
fn from_data(aggs: VecWithNames<AggregationWithAccessor>) -> Self {
Self { aggs }
}
pub fn is_empty(&self) -> bool {
self.aggs.is_empty()
}
}
pub struct AggregationWithAccessor {
pub(crate) segment_ordinal: SegmentOrdinal,
/// In general there can be buckets without fast field access, e.g. buckets that are created
/// based on search terms. That is not that case currently, but eventually this needs to be
/// Option or moved.
pub(crate) accessor: Column<u64>,
/// Load insert u64 for missing use case
pub(crate) missing_value_for_accessor: Option<u64>,
pub(crate) str_dict_column: Option<StrColumn>,
pub(crate) field_type: ColumnType,
pub(crate) sub_aggregation: AggregationsWithAccessor,
pub(crate) limits: AggregationLimitsGuard,
pub(crate) column_block_accessor: ColumnBlockAccessor<u64>,
/// Used for missing term aggregation, which checks all columns for existence.
/// And also for `top_hits` aggregation, which may sort on multiple fields.
/// By convention the missing aggregation is chosen, when this property is set
/// (instead bein set in `agg`).
/// If this needs to used by other aggregations, we need to refactor this.
// NOTE: we can make all other aggregations use this instead of the `accessor` and `field_type`
// (making them obsolete) But will it have a performance impact?
pub(crate) accessors: Vec<(Column<u64>, ColumnType)>,
/// Map field names to all associated column accessors.
/// This field is used for `docvalue_fields`, which is currently only supported for `top_hits`.
pub(crate) value_accessors: HashMap<String, Vec<DynamicColumn>>,
pub(crate) agg: Aggregation,
}
impl AggregationWithAccessor {
/// May return multiple accessors if the aggregation is e.g. on mixed field types.
fn try_from_agg(
agg: &Aggregation,
sub_aggregation: &Aggregations,
reader: &SegmentReader,
segment_ordinal: SegmentOrdinal,
limits: AggregationLimitsGuard,
) -> crate::Result<Vec<AggregationWithAccessor>> {
let mut agg = agg.clone();
let add_agg_with_accessor = |agg: &Aggregation,
accessor: Column<u64>,
column_type: ColumnType,
aggs: &mut Vec<AggregationWithAccessor>|
-> crate::Result<()> {
let res = AggregationWithAccessor {
segment_ordinal,
accessor,
accessors: Default::default(),
value_accessors: Default::default(),
field_type: column_type,
sub_aggregation: get_aggs_with_segment_accessor_and_validate(
sub_aggregation,
reader,
segment_ordinal,
&limits,
)?,
agg: agg.clone(),
limits: limits.clone(),
missing_value_for_accessor: None,
str_dict_column: None,
column_block_accessor: Default::default(),
};
aggs.push(res);
Ok(())
};
let add_agg_with_accessors = |agg: &Aggregation,
accessors: Vec<(Column<u64>, ColumnType)>,
aggs: &mut Vec<AggregationWithAccessor>,
value_accessors: HashMap<String, Vec<DynamicColumn>>|
-> crate::Result<()> {
let (accessor, field_type) = accessors.first().expect("at least one accessor");
let limits = limits.clone();
let res = AggregationWithAccessor {
segment_ordinal,
// TODO: We should do away with the `accessor` field altogether
accessor: accessor.clone(),
value_accessors,
field_type: *field_type,
accessors,
sub_aggregation: get_aggs_with_segment_accessor_and_validate(
sub_aggregation,
reader,
segment_ordinal,
&limits,
)?,
agg: agg.clone(),
limits,
missing_value_for_accessor: None,
str_dict_column: None,
column_block_accessor: Default::default(),
};
aggs.push(res);
Ok(())
};
let mut res: Vec<AggregationWithAccessor> = Vec::new();
use AggregationVariants::*;
match agg.agg {
Range(RangeAggregation {
field: ref field_name,
..
}) => {
let (accessor, column_type) =
get_ff_reader(reader, field_name, Some(get_numeric_or_date_column_types()))?;
add_agg_with_accessor(&agg, accessor, column_type, &mut res)?;
}
Histogram(HistogramAggregation {
field: ref field_name,
..
}) => {
let (accessor, column_type) =
get_ff_reader(reader, field_name, Some(get_numeric_or_date_column_types()))?;
add_agg_with_accessor(&agg, accessor, column_type, &mut res)?;
}
DateHistogram(DateHistogramAggregationReq {
field: ref field_name,
..
}) => {
let (accessor, column_type) =
// Only DateTime is supported for DateHistogram
get_ff_reader(reader, field_name, Some(&[ColumnType::DateTime]))?;
add_agg_with_accessor(&agg, accessor, column_type, &mut res)?;
}
Terms(TermsAggregation {
field: ref field_name,
ref missing,
..
})
| Cardinality(CardinalityAggregationReq {
field: ref field_name,
ref missing,
..
}) => {
let str_dict_column = reader.fast_fields().str(field_name)?;
let allowed_column_types = [
ColumnType::I64,
ColumnType::U64,
ColumnType::F64,
ColumnType::Str,
ColumnType::DateTime,
ColumnType::Bool,
ColumnType::IpAddr,
// ColumnType::Bytes Unsupported
];
// In case the column is empty we want the shim column to match the missing type
let fallback_type = missing
.as_ref()
.map(|missing| match missing {
Key::Str(_) => ColumnType::Str,
Key::F64(_) => ColumnType::F64,
Key::I64(_) => ColumnType::I64,
Key::U64(_) => ColumnType::U64,
})
.unwrap_or(ColumnType::U64);
let column_and_types = get_all_ff_reader_or_empty(
reader,
field_name,
Some(&allowed_column_types),
fallback_type,
)?;
let missing_and_more_than_one_col = column_and_types.len() > 1 && missing.is_some();
let text_on_non_text_col = column_and_types.len() == 1
&& column_and_types[0].1.numerical_type().is_some()
&& missing
.as_ref()
.map(|m| matches!(m, Key::Str(_)))
.unwrap_or(false);
// Actually we could convert the text to a number and have the fast path, if it is
// provided in Rfc3339 format. But this use case is probably common
// enough to justify the effort.
let text_on_date_col = column_and_types.len() == 1
&& column_and_types[0].1 == ColumnType::DateTime
&& missing
.as_ref()
.map(|m| matches!(m, Key::Str(_)))
.unwrap_or(false);
let use_special_missing_agg =
missing_and_more_than_one_col || text_on_non_text_col || text_on_date_col;
if use_special_missing_agg {
let column_and_types =
get_all_ff_reader_or_empty(reader, field_name, None, fallback_type)?;
let accessors = column_and_types
.iter()
.map(|c_t| (c_t.0.clone(), c_t.1))
.collect();
add_agg_with_accessors(&agg, accessors, &mut res, Default::default())?;
}
for (accessor, column_type) in column_and_types {
let missing_value_term_agg = if use_special_missing_agg {
None
} else {
missing.clone()
};
let missing_value_for_accessor =
if let Some(missing) = missing_value_term_agg.as_ref() {
get_missing_val_as_u64_lenient(
column_type,
missing,
agg.agg.get_fast_field_names()[0],
)?
} else {
None
};
let limits = limits.clone();
let agg = AggregationWithAccessor {
segment_ordinal,
missing_value_for_accessor,
accessor,
accessors: Default::default(),
value_accessors: Default::default(),
field_type: column_type,
sub_aggregation: get_aggs_with_segment_accessor_and_validate(
sub_aggregation,
reader,
segment_ordinal,
&limits,
)?,
agg: agg.clone(),
str_dict_column: str_dict_column.clone(),
limits,
column_block_accessor: Default::default(),
};
res.push(agg);
}
}
Average(AverageAggregation {
field: ref field_name,
..
})
| Max(MaxAggregation {
field: ref field_name,
..
})
| Min(MinAggregation {
field: ref field_name,
..
})
| Stats(StatsAggregation {
field: ref field_name,
..
})
| ExtendedStats(ExtendedStatsAggregation {
field: ref field_name,
..
})
| Sum(SumAggregation {
field: ref field_name,
..
}) => {
let (accessor, column_type) =
get_ff_reader(reader, field_name, Some(get_numeric_or_date_column_types()))?;
add_agg_with_accessor(&agg, accessor, column_type, &mut res)?;
}
Count(CountAggregation {
field: ref field_name,
..
}) => {
let allowed_column_types = [
ColumnType::I64,
ColumnType::U64,
ColumnType::F64,
ColumnType::Str,
ColumnType::DateTime,
ColumnType::Bool,
ColumnType::IpAddr,
// ColumnType::Bytes Unsupported
];
let (accessor, column_type) =
get_ff_reader(reader, field_name, Some(&allowed_column_types))?;
add_agg_with_accessor(&agg, accessor, column_type, &mut res)?;
}
Percentiles(ref percentiles) => {
let (accessor, column_type) = get_ff_reader(
reader,
percentiles.field_name(),
Some(get_numeric_or_date_column_types()),
)?;
add_agg_with_accessor(&agg, accessor, column_type, &mut res)?;
}
TopHits(ref mut top_hits) => {
top_hits.validate_and_resolve_field_names(reader.fast_fields().columnar())?;
let accessors: Vec<(Column<u64>, ColumnType)> = top_hits
.field_names()
.iter()
.map(|field| {
get_ff_reader(reader, field, Some(get_numeric_or_date_column_types()))
})
.collect::<crate::Result<_>>()?;
let value_accessors = top_hits
.value_field_names()
.iter()
.map(|field_name| {
Ok((
field_name.to_string(),
get_dynamic_columns(reader, field_name)?,
))
})
.collect::<crate::Result<_>>()?;
add_agg_with_accessors(&agg, accessors, &mut res, value_accessors)?;
}
};
Ok(res)
}
}
/// Get the missing value as internal u64 representation
///
/// For terms we use u64::MAX as sentinel value
/// For numerical data we convert the value into the representation
/// we would get from the fast field, when we open it as u64_lenient_for_type.
///
/// That way we can use it the same way as if it would come from the fastfield.
fn get_missing_val_as_u64_lenient(
column_type: ColumnType,
missing: &Key,
field_name: &str,
) -> crate::Result<Option<u64>> {
let missing_val = match missing {
Key::Str(_) if column_type == ColumnType::Str => Some(u64::MAX),
// Allow fallback to number on text fields
Key::F64(_) if column_type == ColumnType::Str => Some(u64::MAX),
Key::U64(_) if column_type == ColumnType::Str => Some(u64::MAX),
Key::I64(_) if column_type == ColumnType::Str => Some(u64::MAX),
Key::F64(val) if column_type.numerical_type().is_some() => {
f64_to_fastfield_u64(*val, &column_type)
}
// NOTE: We may loose precision of the passed missing value by casting i64 and u64 to f64.
Key::I64(val) if column_type.numerical_type().is_some() => {
f64_to_fastfield_u64(*val as f64, &column_type)
}
Key::U64(val) if column_type.numerical_type().is_some() => {
f64_to_fastfield_u64(*val as f64, &column_type)
}
_ => {
return Err(crate::TantivyError::InvalidArgument(format!(
"Missing value {missing:?} for field {field_name} is not supported for column \
type {column_type:?}"
)));
}
};
Ok(missing_val)
}
fn get_numeric_or_date_column_types() -> &'static [ColumnType] {
&[
ColumnType::F64,
ColumnType::U64,
ColumnType::I64,
ColumnType::DateTime,
]
}
pub(crate) fn get_aggs_with_segment_accessor_and_validate(
aggs: &Aggregations,
reader: &SegmentReader,
segment_ordinal: SegmentOrdinal,
limits: &AggregationLimitsGuard,
) -> crate::Result<AggregationsWithAccessor> {
let mut aggss = Vec::new();
for (key, agg) in aggs.iter() {
let aggs = AggregationWithAccessor::try_from_agg(
agg,
agg.sub_aggregation(),
reader,
segment_ordinal,
limits.clone(),
)?;
for agg in aggs {
aggss.push((key.to_string(), agg));
}
}
Ok(AggregationsWithAccessor::from_data(
VecWithNames::from_entries(aggss),
))
}
/// Get fast field reader or empty as default.
fn get_ff_reader(
reader: &SegmentReader,
field_name: &str,
allowed_column_types: Option<&[ColumnType]>,
) -> crate::Result<(columnar::Column<u64>, ColumnType)> {
let ff_fields = reader.fast_fields();
let ff_field_with_type = ff_fields
.u64_lenient_for_type(allowed_column_types, field_name)?
.unwrap_or_else(|| {
(
Column::build_empty_column(reader.num_docs()),
ColumnType::U64,
)
});
Ok(ff_field_with_type)
}
fn get_dynamic_columns(
reader: &SegmentReader,
field_name: &str,
) -> crate::Result<Vec<columnar::DynamicColumn>> {
let ff_fields = reader.fast_fields().dynamic_column_handles(field_name)?;
let cols = ff_fields
.iter()
.map(|h| h.open())
.collect::<io::Result<_>>()?;
assert!(!ff_fields.is_empty(), "field {field_name} not found");
Ok(cols)
}
/// Get all fast field reader or empty as default.
///
/// Is guaranteed to return at least one column.
fn get_all_ff_reader_or_empty(
reader: &SegmentReader,
field_name: &str,
allowed_column_types: Option<&[ColumnType]>,
fallback_type: ColumnType,
) -> crate::Result<Vec<(columnar::Column<u64>, ColumnType)>> {
let ff_fields = reader.fast_fields();
let mut ff_field_with_type =
ff_fields.u64_lenient_for_type_all(allowed_column_types, field_name)?;
if ff_field_with_type.is_empty() {
ff_field_with_type.push((Column::build_empty_column(reader.num_docs()), fallback_type));
}
Ok(ff_field_with_type)
}

View File

@@ -156,8 +156,6 @@ pub enum BucketResult {
/// The upper bound error for the doc count of each term.
doc_count_error_upper_bound: Option<u64>,
},
/// This is the filter result - a single bucket with sub-aggregations
Filter(FilterBucketResult),
}
impl BucketResult {
@@ -174,11 +172,6 @@ impl BucketResult {
sum_other_doc_count: _,
doc_count_error_upper_bound: _,
} => buckets.iter().map(|bucket| bucket.get_bucket_count()).sum(),
BucketResult::Filter(filter_result) => {
// Filter doesn't add to bucket count - it's not a user-facing bucket
// Only count sub-aggregation buckets
filter_result.sub_aggregations.get_bucket_count()
}
}
}
}
@@ -315,25 +308,3 @@ impl RangeBucketEntry {
1 + self.sub_aggregation.get_bucket_count()
}
}
/// This is the filter bucket result, which contains the document count and sub-aggregations.
///
/// # JSON Format
/// ```json
/// {
/// "electronics_only": {
/// "doc_count": 2,
/// "avg_price": {
/// "value": 150.0
/// }
/// }
/// }
/// ```
#[derive(Clone, Debug, PartialEq, Serialize, Deserialize)]
pub struct FilterBucketResult {
/// Number of documents in the filter bucket
pub doc_count: u64,
/// Sub-aggregation results
#[serde(flatten)]
pub sub_aggregations: AggregationResults,
}

View File

@@ -5,6 +5,7 @@ use crate::aggregation::agg_result::AggregationResults;
use crate::aggregation::buf_collector::DOC_BLOCK_SIZE;
use crate::aggregation::collector::AggregationCollector;
use crate::aggregation::intermediate_agg_result::IntermediateAggregationResults;
use crate::aggregation::segment_agg_result::AggregationLimitsGuard;
use crate::aggregation::tests::{get_test_index_2_segments, get_test_index_from_values_and_terms};
use crate::aggregation::DistributedAggregationCollector;
use crate::query::{AllQuery, TermQuery};
@@ -127,8 +128,10 @@ fn test_aggregation_flushing(
.unwrap();
let agg_res: AggregationResults = if use_distributed_collector {
let collector =
DistributedAggregationCollector::from_aggs(agg_req.clone(), Default::default());
let collector = DistributedAggregationCollector::from_aggs(
agg_req.clone(),
AggregationLimitsGuard::default(),
);
let searcher = reader.searcher();
let intermediate_agg_result = searcher.search(&AllQuery, &collector).unwrap();

File diff suppressed because it is too large Load Diff

View File

@@ -1,54 +1,25 @@
use std::cmp::Ordering;
use columnar::{Column, ColumnBlockAccessor, ColumnType};
use rustc_hash::FxHashMap;
use serde::{Deserialize, Serialize};
use tantivy_bitpacker::minmax;
use crate::aggregation::agg_data::{
build_segment_agg_collectors, AggRefNode, AggregationsSegmentCtx,
};
use crate::aggregation::agg_limits::MemoryConsumption;
use crate::aggregation::agg_req::Aggregations;
use crate::aggregation::agg_req_with_accessor::{
AggregationWithAccessor, AggregationsWithAccessor,
};
use crate::aggregation::agg_result::BucketEntry;
use crate::aggregation::intermediate_agg_result::{
IntermediateAggregationResult, IntermediateAggregationResults, IntermediateBucketResult,
IntermediateHistogramBucketEntry,
};
use crate::aggregation::segment_agg_result::SegmentAggregationCollector;
use crate::aggregation::segment_agg_result::{
build_segment_agg_collector, SegmentAggregationCollector,
};
use crate::aggregation::*;
use crate::TantivyError;
/// Contains all information required by the SegmentHistogramCollector to perform the
/// histogram or date_histogram aggregation on a segment.
pub struct HistogramAggReqData {
/// The column accessor to access the fast field values.
pub accessor: Column<u64>,
/// The field type of the fast field.
pub field_type: ColumnType,
/// The column block accessor to access the fast field values.
pub column_block_accessor: ColumnBlockAccessor<u64>,
/// The name of the aggregation.
pub name: String,
/// The sub aggregation blueprint, used to create sub aggregations for each bucket.
/// Will be filled during initialization of the collector.
pub sub_aggregation_blueprint: Option<Box<dyn SegmentAggregationCollector>>,
/// The histogram aggregation request.
pub req: HistogramAggregation,
/// True if this is a date_histogram aggregation.
pub is_date_histogram: bool,
/// The bounds to limit the buckets to.
pub bounds: HistogramBounds,
/// The offset used to calculate the bucket position.
pub offset: f64,
}
impl HistogramAggReqData {
/// Estimate the memory consumption of this struct in bytes.
pub fn get_memory_consumption(&self) -> usize {
std::mem::size_of::<Self>()
}
}
/// Histogram is a bucket aggregation, where buckets are created dynamically for given `interval`.
/// Each document value is rounded down to its bucket.
///
@@ -263,12 +234,12 @@ impl SegmentHistogramBucketEntry {
pub(crate) fn into_intermediate_bucket_entry(
self,
sub_aggregation: Option<Box<dyn SegmentAggregationCollector>>,
agg_data: &AggregationsSegmentCtx,
agg_with_accessor: &AggregationsWithAccessor,
) -> crate::Result<IntermediateHistogramBucketEntry> {
let mut sub_aggregation_res = IntermediateAggregationResults::default();
if let Some(sub_aggregation) = sub_aggregation {
sub_aggregation
.add_intermediate_aggregation_result(agg_data, &mut sub_aggregation_res)?;
.add_intermediate_aggregation_result(agg_with_accessor, &mut sub_aggregation_res)?;
}
Ok(IntermediateHistogramBucketEntry {
key: self.key,
@@ -285,20 +256,24 @@ pub struct SegmentHistogramCollector {
/// The buckets containing the aggregation data.
buckets: FxHashMap<i64, SegmentHistogramBucketEntry>,
sub_aggregations: FxHashMap<i64, Box<dyn SegmentAggregationCollector>>,
sub_aggregation_blueprint: Option<Box<dyn SegmentAggregationCollector>>,
column_type: ColumnType,
interval: f64,
offset: f64,
bounds: HistogramBounds,
accessor_idx: usize,
}
impl SegmentAggregationCollector for SegmentHistogramCollector {
fn add_intermediate_aggregation_result(
self: Box<Self>,
agg_data: &AggregationsSegmentCtx,
agg_with_accessor: &AggregationsWithAccessor,
results: &mut IntermediateAggregationResults,
) -> crate::Result<()> {
let name = agg_data
.get_histogram_req_data(self.accessor_idx)
.name
.clone();
let bucket = self.into_intermediate_bucket_result(agg_data)?;
let name = agg_with_accessor.aggs.keys[self.accessor_idx].to_string();
let agg_with_accessor = &agg_with_accessor.aggs.values[self.accessor_idx];
let bucket = self.into_intermediate_bucket_result(agg_with_accessor)?;
results.push(name, IntermediateAggregationResult::Bucket(bucket))?;
Ok(())
@@ -308,52 +283,56 @@ impl SegmentAggregationCollector for SegmentHistogramCollector {
fn collect(
&mut self,
doc: crate::DocId,
agg_data: &mut AggregationsSegmentCtx,
agg_with_accessor: &mut AggregationsWithAccessor,
) -> crate::Result<()> {
self.collect_block(&[doc], agg_data)
self.collect_block(&[doc], agg_with_accessor)
}
#[inline]
fn collect_block(
&mut self,
docs: &[crate::DocId],
agg_data: &mut AggregationsSegmentCtx,
agg_with_accessor: &mut AggregationsWithAccessor,
) -> crate::Result<()> {
let mut req = agg_data.take_histogram_req_data(self.accessor_idx);
let bucket_agg_accessor = &mut agg_with_accessor.aggs.values[self.accessor_idx];
let mem_pre = self.get_memory_consumption();
let bounds = req.bounds;
let interval = req.req.interval;
let offset = req.offset;
let bounds = self.bounds;
let interval = self.interval;
let offset = self.offset;
let get_bucket_pos = |val| get_bucket_pos_f64(val, interval, offset) as i64;
req.column_block_accessor.fetch_block(docs, &req.accessor);
for (doc, val) in req
bucket_agg_accessor
.column_block_accessor
.iter_docid_vals(docs, &req.accessor)
.fetch_block(docs, &bucket_agg_accessor.accessor);
for (doc, val) in bucket_agg_accessor
.column_block_accessor
.iter_docid_vals(docs, &bucket_agg_accessor.accessor)
{
let val = f64_from_fastfield_u64(val, &req.field_type);
let val = self.f64_from_fastfield_u64(val);
let bucket_pos = get_bucket_pos(val);
if bounds.contains(val) {
let bucket = self.buckets.entry(bucket_pos).or_insert_with(|| {
let key = get_bucket_key_from_pos(bucket_pos as f64, interval, offset);
SegmentHistogramBucketEntry { key, doc_count: 0 }
});
bucket.doc_count += 1;
if let Some(sub_aggregation_blueprint) = req.sub_aggregation_blueprint.as_ref() {
if let Some(sub_aggregation_blueprint) = self.sub_aggregation_blueprint.as_mut() {
self.sub_aggregations
.entry(bucket_pos)
.or_insert_with(|| sub_aggregation_blueprint.clone())
.collect(doc, agg_data)?;
.collect(doc, &mut bucket_agg_accessor.sub_aggregation)?;
}
}
}
agg_data.put_back_histogram_req_data(self.accessor_idx, req);
let mem_delta = self.get_memory_consumption() - mem_pre;
if mem_delta > 0 {
agg_data
.context
bucket_agg_accessor
.limits
.add_memory_consumed(mem_delta as u64)?;
}
@@ -361,9 +340,12 @@ impl SegmentAggregationCollector for SegmentHistogramCollector {
Ok(())
}
fn flush(&mut self, agg_data: &mut AggregationsSegmentCtx) -> crate::Result<()> {
fn flush(&mut self, agg_with_accessor: &mut AggregationsWithAccessor) -> crate::Result<()> {
let sub_aggregation_accessor =
&mut agg_with_accessor.aggs.values[self.accessor_idx].sub_aggregation;
for sub_aggregation in self.sub_aggregations.values_mut() {
sub_aggregation.flush(agg_data)?;
sub_aggregation.flush(sub_aggregation_accessor)?;
}
Ok(())
@@ -380,58 +362,65 @@ impl SegmentHistogramCollector {
/// Converts the collector result into a intermediate bucket result.
pub fn into_intermediate_bucket_result(
self,
agg_data: &AggregationsSegmentCtx,
agg_with_accessor: &AggregationWithAccessor,
) -> crate::Result<IntermediateBucketResult> {
let mut buckets = Vec::with_capacity(self.buckets.len());
for (bucket_pos, bucket) in self.buckets {
let bucket_res = bucket.into_intermediate_bucket_entry(
self.sub_aggregations.get(&bucket_pos).cloned(),
agg_data,
&agg_with_accessor.sub_aggregation,
);
buckets.push(bucket_res?);
}
buckets.sort_unstable_by(|b1, b2| b1.key.total_cmp(&b2.key));
let is_date_agg = agg_data
.get_histogram_req_data(self.accessor_idx)
.field_type
== ColumnType::DateTime;
Ok(IntermediateBucketResult::Histogram {
buckets,
is_date_agg,
is_date_agg: self.column_type == ColumnType::DateTime,
})
}
pub(crate) fn from_req_and_validate(
agg_data: &mut AggregationsSegmentCtx,
node: &AggRefNode,
mut req: HistogramAggregation,
sub_aggregation: &mut AggregationsWithAccessor,
field_type: ColumnType,
accessor_idx: usize,
) -> crate::Result<Self> {
let blueprint = if !node.children.is_empty() {
Some(build_segment_agg_collectors(agg_data, &node.children)?)
} else {
None
};
let req_data = agg_data.get_histogram_req_data_mut(node.idx_in_req_data);
req_data.req.validate()?;
if req_data.field_type == ColumnType::DateTime && !req_data.is_date_histogram {
req_data.req.normalize_date_time();
req.validate()?;
if field_type == ColumnType::DateTime {
req.normalize_date_time();
}
req_data.bounds = req_data.req.hard_bounds.unwrap_or(HistogramBounds {
let sub_aggregation_blueprint = if sub_aggregation.is_empty() {
None
} else {
let sub_aggregation = build_segment_agg_collector(sub_aggregation)?;
Some(sub_aggregation)
};
let bounds = req.hard_bounds.unwrap_or(HistogramBounds {
min: f64::MIN,
max: f64::MAX,
});
req_data.offset = req_data.req.offset.unwrap_or(0.0);
req_data.sub_aggregation_blueprint = blueprint;
Ok(Self {
buckets: Default::default(),
column_type: field_type,
interval: req.interval,
offset: req.offset.unwrap_or(0.0),
bounds,
sub_aggregations: Default::default(),
accessor_idx: node.idx_in_req_data,
sub_aggregation_blueprint,
accessor_idx,
})
}
#[inline]
fn f64_from_fastfield_u64(&self, val: u64) -> f64 {
f64_from_fastfield_u64(val, &self.column_type)
}
}
#[inline]

View File

@@ -22,7 +22,6 @@
//! - [Range](RangeAggregation)
//! - [Terms](TermsAggregation)
mod filter;
mod histogram;
mod range;
mod term_agg;
@@ -31,7 +30,6 @@ mod term_missing_agg;
use std::collections::HashMap;
use std::fmt;
pub use filter::*;
pub use histogram::*;
pub use range::*;
use serde::{de, Deserialize, Deserializer, Serialize, Serializer};

View File

@@ -1,43 +1,20 @@
use std::fmt::Debug;
use std::ops::Range;
use columnar::{Column, ColumnBlockAccessor, ColumnType};
use rustc_hash::FxHashMap;
use serde::{Deserialize, Serialize};
use crate::aggregation::agg_data::{
build_segment_agg_collectors, AggRefNode, AggregationsSegmentCtx,
};
use crate::aggregation::agg_req_with_accessor::AggregationsWithAccessor;
use crate::aggregation::intermediate_agg_result::{
IntermediateAggregationResult, IntermediateAggregationResults, IntermediateBucketResult,
IntermediateRangeBucketEntry, IntermediateRangeBucketResult,
};
use crate::aggregation::segment_agg_result::SegmentAggregationCollector;
use crate::aggregation::segment_agg_result::{
build_segment_agg_collector, SegmentAggregationCollector,
};
use crate::aggregation::*;
use crate::TantivyError;
/// Contains all information required by the SegmentRangeCollector to perform the
/// range aggregation on a segment.
pub struct RangeAggReqData {
/// The column accessor to access the fast field values.
pub accessor: Column<u64>,
/// The type of the fast field.
pub field_type: ColumnType,
/// The column block accessor to access the fast field values.
pub column_block_accessor: ColumnBlockAccessor<u64>,
/// The range aggregation request.
pub req: RangeAggregation,
/// The name of the aggregation.
pub name: String,
}
impl RangeAggReqData {
/// Estimate the memory consumption of this struct in bytes.
pub fn get_memory_consumption(&self) -> usize {
std::mem::size_of::<Self>()
}
}
/// Provide user-defined buckets to aggregate on.
///
/// Two special buckets will automatically be created to cover the whole range of values.
@@ -184,12 +161,12 @@ impl Debug for SegmentRangeBucketEntry {
impl SegmentRangeBucketEntry {
pub(crate) fn into_intermediate_bucket_entry(
self,
agg_data: &AggregationsSegmentCtx,
agg_with_accessor: &AggregationsWithAccessor,
) -> crate::Result<IntermediateRangeBucketEntry> {
let mut sub_aggregation_res = IntermediateAggregationResults::default();
if let Some(sub_aggregation) = self.sub_aggregation {
sub_aggregation
.add_intermediate_aggregation_result(agg_data, &mut sub_aggregation_res)?
.add_intermediate_aggregation_result(agg_with_accessor, &mut sub_aggregation_res)?
} else {
Default::default()
};
@@ -207,14 +184,12 @@ impl SegmentRangeBucketEntry {
impl SegmentAggregationCollector for SegmentRangeCollector {
fn add_intermediate_aggregation_result(
self: Box<Self>,
agg_data: &AggregationsSegmentCtx,
agg_with_accessor: &AggregationsWithAccessor,
results: &mut IntermediateAggregationResults,
) -> crate::Result<()> {
let field_type = self.column_type;
let name = agg_data
.get_range_req_data(self.accessor_idx)
.name
.to_string();
let name = agg_with_accessor.aggs.keys[self.accessor_idx].to_string();
let sub_agg = &agg_with_accessor.aggs.values[self.accessor_idx].sub_aggregation;
let buckets: FxHashMap<SerializedKey, IntermediateRangeBucketEntry> = self
.buckets
@@ -224,7 +199,7 @@ impl SegmentAggregationCollector for SegmentRangeCollector {
range_to_string(&range_bucket.range, &field_type)?,
range_bucket
.bucket
.into_intermediate_bucket_entry(agg_data)?,
.into_intermediate_bucket_entry(sub_agg)?,
))
})
.collect::<crate::Result<_>>()?;
@@ -243,70 +218,66 @@ impl SegmentAggregationCollector for SegmentRangeCollector {
fn collect(
&mut self,
doc: crate::DocId,
agg_data: &mut AggregationsSegmentCtx,
agg_with_accessor: &mut AggregationsWithAccessor,
) -> crate::Result<()> {
self.collect_block(&[doc], agg_data)
self.collect_block(&[doc], agg_with_accessor)
}
#[inline]
fn collect_block(
&mut self,
docs: &[crate::DocId],
agg_data: &mut AggregationsSegmentCtx,
agg_with_accessor: &mut AggregationsWithAccessor,
) -> crate::Result<()> {
// Take request data to avoid borrow conflicts during sub-aggregation
let mut req = agg_data.take_range_req_data(self.accessor_idx);
let bucket_agg_accessor = &mut agg_with_accessor.aggs.values[self.accessor_idx];
req.column_block_accessor.fetch_block(docs, &req.accessor);
for (doc, val) in req
bucket_agg_accessor
.column_block_accessor
.iter_docid_vals(docs, &req.accessor)
.fetch_block(docs, &bucket_agg_accessor.accessor);
for (doc, val) in bucket_agg_accessor
.column_block_accessor
.iter_docid_vals(docs, &bucket_agg_accessor.accessor)
{
let bucket_pos = self.get_bucket_pos(val);
let bucket = &mut self.buckets[bucket_pos];
bucket.bucket.doc_count += 1;
if let Some(sub_agg) = bucket.bucket.sub_aggregation.as_mut() {
sub_agg.collect(doc, agg_data)?;
if let Some(sub_aggregation) = &mut bucket.bucket.sub_aggregation {
sub_aggregation.collect(doc, &mut bucket_agg_accessor.sub_aggregation)?;
}
}
agg_data.put_back_range_req_data(self.accessor_idx, req);
Ok(())
}
fn flush(&mut self, agg_data: &mut AggregationsSegmentCtx) -> crate::Result<()> {
fn flush(&mut self, agg_with_accessor: &mut AggregationsWithAccessor) -> crate::Result<()> {
let sub_aggregation_accessor =
&mut agg_with_accessor.aggs.values[self.accessor_idx].sub_aggregation;
for bucket in self.buckets.iter_mut() {
if let Some(sub_agg) = bucket.bucket.sub_aggregation.as_mut() {
sub_agg.flush(agg_data)?;
sub_agg.flush(sub_aggregation_accessor)?;
}
}
Ok(())
}
}
impl SegmentRangeCollector {
pub(crate) fn from_req_and_validate(
req_data: &mut AggregationsSegmentCtx,
node: &AggRefNode,
req: &RangeAggregation,
sub_aggregation: &mut AggregationsWithAccessor,
limits: &mut AggregationLimitsGuard,
field_type: ColumnType,
accessor_idx: usize,
) -> crate::Result<Self> {
let accessor_idx = node.idx_in_req_data;
let (field_type, ranges) = {
let req_view = req_data.get_range_req_data(node.idx_in_req_data);
(req_view.field_type, req_view.req.ranges.clone())
};
// The range input on the request is f64.
// We need to convert to u64 ranges, because we read the values as u64.
// The mapping from the conversion is monotonic so ordering is preserved.
let sub_agg_prototype = if !node.children.is_empty() {
Some(build_segment_agg_collectors(req_data, &node.children)?)
} else {
None
};
let buckets: Vec<_> = extend_validate_ranges(&ranges, &field_type)?
let buckets: Vec<_> = extend_validate_ranges(&req.ranges, &field_type)?
.iter()
.map(|range| {
let key = range
@@ -324,7 +295,11 @@ impl SegmentRangeCollector {
} else {
Some(f64_from_fastfield_u64(range.range.start, &field_type))
};
let sub_aggregation = sub_agg_prototype.clone();
let sub_aggregation = if sub_aggregation.is_empty() {
None
} else {
Some(build_segment_agg_collector(sub_aggregation)?)
};
Ok(SegmentRangeAndBucketEntry {
range: range.range.clone(),
@@ -339,7 +314,7 @@ impl SegmentRangeCollector {
})
.collect::<crate::Result<_>>()?;
req_data.context.limits.add_memory_consumed(
limits.add_memory_consumed(
buckets.len() as u64 * std::mem::size_of::<SegmentRangeAndBucketEntry>() as u64,
)?;
@@ -492,45 +467,15 @@ mod tests {
ranges,
..Default::default()
};
// Build buckets directly as in from_req_and_validate without AggregationsData
let buckets: Vec<_> = extend_validate_ranges(&req.ranges, &field_type)
.expect("unexpected error in extend_validate_ranges")
.iter()
.map(|range| {
let key = range
.key
.clone()
.map(|key| Ok(Key::Str(key)))
.unwrap_or_else(|| range_to_key(&range.range, &field_type))
.expect("unexpected error in range_to_key");
let to = if range.range.end == u64::MAX {
None
} else {
Some(f64_from_fastfield_u64(range.range.end, &field_type))
};
let from = if range.range.start == u64::MIN {
None
} else {
Some(f64_from_fastfield_u64(range.range.start, &field_type))
};
SegmentRangeAndBucketEntry {
range: range.range.clone(),
bucket: SegmentRangeBucketEntry {
doc_count: 0,
sub_aggregation: None,
key,
from,
to,
},
}
})
.collect();
SegmentRangeCollector {
buckets,
column_type: field_type,
accessor_idx: 0,
}
SegmentRangeCollector::from_req_and_validate(
&req,
&mut Default::default(),
&mut AggregationLimitsGuard::default(),
field_type,
0,
)
.expect("unexpected error")
}
#[test]

View File

@@ -1,196 +0,0 @@
use std::fmt::Debug;
use columnar::ColumnType;
use rustc_hash::FxHashMap;
use super::OrderTarget;
use crate::aggregation::agg_data::{
build_segment_agg_collectors, AggRefNode, AggregationsSegmentCtx,
};
use crate::aggregation::agg_limits::MemoryConsumption;
use crate::aggregation::bucket::get_agg_name_and_property;
use crate::aggregation::intermediate_agg_result::{
IntermediateAggregationResult, IntermediateAggregationResults,
};
use crate::aggregation::segment_agg_result::SegmentAggregationCollector;
use crate::TantivyError;
#[derive(Clone, Debug, Default)]
/// Container to store term_ids/or u64 values and their buckets.
struct TermBuckets {
pub(crate) entries: FxHashMap<u64, u32>,
pub(crate) sub_aggs: FxHashMap<u64, Box<dyn SegmentAggregationCollector>>,
}
impl TermBuckets {
fn get_memory_consumption(&self) -> usize {
let sub_aggs_mem = self.sub_aggs.memory_consumption();
let buckets_mem = self.entries.memory_consumption();
sub_aggs_mem + buckets_mem
}
fn force_flush(&mut self, agg_data: &mut AggregationsSegmentCtx) -> crate::Result<()> {
for sub_aggregations in &mut self.sub_aggs.values_mut() {
sub_aggregations.as_mut().flush(agg_data)?;
}
Ok(())
}
}
/// The collector puts values from the fast field into the correct buckets and does a conversion to
/// the correct datatype.
#[derive(Clone, Debug)]
pub struct SegmentTermCollector {
/// The buckets containing the aggregation data.
term_buckets: TermBuckets,
accessor_idx: usize,
}
impl SegmentAggregationCollector for SegmentTermCollector {
fn add_intermediate_aggregation_result(
self: Box<Self>,
agg_data: &AggregationsSegmentCtx,
results: &mut IntermediateAggregationResults,
) -> crate::Result<()> {
let name = agg_data.get_term_req_data(self.accessor_idx).name.clone();
let entries: Vec<(u64, u32)> = self.term_buckets.entries.into_iter().collect();
let bucket = super::into_intermediate_bucket_result(
self.accessor_idx,
entries,
self.term_buckets.sub_aggs,
agg_data,
)?;
results.push(name, IntermediateAggregationResult::Bucket(bucket))?;
Ok(())
}
#[inline]
fn collect(
&mut self,
doc: crate::DocId,
agg_data: &mut AggregationsSegmentCtx,
) -> crate::Result<()> {
self.collect_block(&[doc], agg_data)
}
#[inline]
fn collect_block(
&mut self,
docs: &[crate::DocId],
agg_data: &mut AggregationsSegmentCtx,
) -> crate::Result<()> {
let mut req_data = agg_data.take_term_req_data(self.accessor_idx);
let mem_pre = self.get_memory_consumption();
if let Some(missing) = req_data.missing_value_for_accessor {
req_data.column_block_accessor.fetch_block_with_missing(
docs,
&req_data.accessor,
missing,
);
} else {
req_data
.column_block_accessor
.fetch_block(docs, &req_data.accessor);
}
for term_id in req_data.column_block_accessor.iter_vals() {
if let Some(allowed_bs) = req_data.allowed_term_ids.as_ref() {
if !allowed_bs.contains(term_id as u32) {
continue;
}
}
let entry = self.term_buckets.entries.entry(term_id).or_default();
*entry += 1;
}
// has subagg
if let Some(blueprint) = req_data.sub_aggregation_blueprint.as_ref() {
for (doc, term_id) in req_data
.column_block_accessor
.iter_docid_vals(docs, &req_data.accessor)
{
if let Some(allowed_bs) = req_data.allowed_term_ids.as_ref() {
if !allowed_bs.contains(term_id as u32) {
continue;
}
}
let sub_aggregations = self
.term_buckets
.sub_aggs
.entry(term_id)
.or_insert_with(|| blueprint.clone());
sub_aggregations.collect(doc, agg_data)?;
}
}
let mem_delta = self.get_memory_consumption() - mem_pre;
if mem_delta > 0 {
agg_data
.context
.limits
.add_memory_consumed(mem_delta as u64)?;
}
agg_data.put_back_term_req_data(self.accessor_idx, req_data);
Ok(())
}
fn flush(&mut self, agg_data: &mut AggregationsSegmentCtx) -> crate::Result<()> {
self.term_buckets.force_flush(agg_data)?;
Ok(())
}
}
impl SegmentTermCollector {
pub fn from_req_and_validate(
req_data: &mut AggregationsSegmentCtx,
node: &AggRefNode,
) -> crate::Result<Self> {
let terms_req_data = req_data.get_term_req_data(node.idx_in_req_data);
let column_type = terms_req_data.column_type;
let accessor_idx = node.idx_in_req_data;
if column_type == ColumnType::Bytes {
return Err(TantivyError::InvalidArgument(format!(
"terms aggregation is not supported for column type {column_type:?}"
)));
}
let term_buckets = TermBuckets::default();
// Validate sub aggregation exists
if let OrderTarget::SubAggregation(sub_agg_name) = &terms_req_data.req.order.target {
let (agg_name, _agg_property) = get_agg_name_and_property(sub_agg_name);
node.get_sub_agg(agg_name, &req_data.per_request)
.ok_or_else(|| {
TantivyError::InvalidArgument(format!(
"could not find aggregation with name {agg_name} in metric \
sub_aggregations"
))
})?;
}
let has_sub_aggregations = !node.children.is_empty();
let blueprint = if has_sub_aggregations {
let sub_aggregation = build_segment_agg_collectors(req_data, &node.children)?;
Some(sub_aggregation)
} else {
None
};
let terms_req_data = req_data.get_term_req_data_mut(node.idx_in_req_data);
terms_req_data.sub_aggregation_blueprint = blueprint;
Ok(SegmentTermCollector {
term_buckets,
accessor_idx,
})
}
fn get_memory_consumption(&self) -> usize {
let self_mem = std::mem::size_of::<Self>();
let term_buckets_mem = self.term_buckets.get_memory_consumption();
self_mem + term_buckets_mem
}
}

View File

@@ -1,228 +0,0 @@
use std::vec;
use rustc_hash::FxHashMap;
use crate::aggregation::agg_data::{
build_segment_agg_collectors, AggRefNode, AggregationsSegmentCtx,
};
use crate::aggregation::bucket::{get_agg_name_and_property, OrderTarget};
use crate::aggregation::intermediate_agg_result::{
IntermediateAggregationResult, IntermediateAggregationResults,
};
use crate::aggregation::segment_agg_result::SegmentAggregationCollector;
use crate::{DocId, TantivyError};
const MAX_BATCH_SIZE: usize = 1_024;
#[derive(Debug, Clone)]
struct LowCardTermBuckets {
entries: Box<[u32]>,
sub_aggs: Vec<Box<dyn SegmentAggregationCollector>>,
doc_buffers: Box<[Vec<DocId>]>,
}
impl LowCardTermBuckets {
pub fn with_num_buckets(
num_buckets: usize,
sub_aggs_blueprint_opt: Option<&Box<dyn SegmentAggregationCollector>>,
) -> Self {
let sub_aggs = sub_aggs_blueprint_opt
.as_ref()
.map(|blueprint| {
std::iter::repeat_with(|| blueprint.clone_box())
.take(num_buckets)
.collect::<Vec<_>>()
})
.unwrap_or_default();
Self {
entries: vec![0; num_buckets].into_boxed_slice(),
sub_aggs,
doc_buffers: std::iter::repeat_with(|| Vec::with_capacity(MAX_BATCH_SIZE))
.take(num_buckets)
.collect::<Vec<_>>()
.into_boxed_slice(),
}
}
fn get_memory_consumption(&self) -> usize {
std::mem::size_of::<Self>()
+ self.entries.len() * std::mem::size_of::<u32>()
+ self.doc_buffers.len()
* (std::mem::size_of::<Vec<DocId>>()
+ std::mem::size_of::<DocId>() * MAX_BATCH_SIZE)
}
}
#[derive(Debug, Clone)]
pub struct LowCardSegmentTermCollector {
term_buckets: LowCardTermBuckets,
accessor_idx: usize,
}
impl LowCardSegmentTermCollector {
pub fn from_req_and_validate(
req_data: &mut AggregationsSegmentCtx,
node: &AggRefNode,
) -> crate::Result<Self> {
let terms_req_data = req_data.get_term_req_data(node.idx_in_req_data);
let accessor_idx = node.idx_in_req_data;
let cardinality = terms_req_data
.accessor
.max_value()
.max(terms_req_data.missing_value_for_accessor.unwrap_or(0))
+ 1;
assert!(cardinality <= super::LOW_CARDINALITY_THRESHOLD);
// Validate sub aggregation exists
if let OrderTarget::SubAggregation(sub_agg_name) = &terms_req_data.req.order.target {
let (agg_name, _agg_property) = get_agg_name_and_property(sub_agg_name);
node.get_sub_agg(agg_name, &req_data.per_request)
.ok_or_else(|| {
TantivyError::InvalidArgument(format!(
"could not find aggregation with name {agg_name} in metric \
sub_aggregations"
))
})?;
}
let has_sub_aggregations = !node.children.is_empty();
let blueprint = if has_sub_aggregations {
let sub_aggregation = build_segment_agg_collectors(req_data, &node.children)?;
Some(sub_aggregation)
} else {
None
};
let terms_req_data = req_data.get_term_req_data_mut(node.idx_in_req_data);
let term_buckets =
LowCardTermBuckets::with_num_buckets(cardinality as usize, blueprint.as_ref());
terms_req_data.sub_aggregation_blueprint = blueprint;
Ok(LowCardSegmentTermCollector {
term_buckets,
accessor_idx,
})
}
fn get_memory_consumption(&self) -> usize {
let self_mem = std::mem::size_of::<Self>();
let term_buckets_mem = self.term_buckets.get_memory_consumption();
self_mem + term_buckets_mem
}
}
impl SegmentAggregationCollector for LowCardSegmentTermCollector {
fn add_intermediate_aggregation_result(
self: Box<Self>,
agg_data: &AggregationsSegmentCtx,
results: &mut IntermediateAggregationResults,
) -> crate::Result<()> {
let name = agg_data.get_term_req_data(self.accessor_idx).name.clone();
let sub_aggs: FxHashMap<u64, Box<dyn SegmentAggregationCollector>> = self
.term_buckets
.sub_aggs
.into_iter()
.enumerate()
.filter(|(bucket_id, _sub_agg)| self.term_buckets.entries[*bucket_id] > 0)
.map(|(bucket_id, sub_agg)| (bucket_id as u64, sub_agg))
.collect();
let entries: Vec<(u64, u32)> = self
.term_buckets
.entries
.iter()
.enumerate()
.filter(|(_, count)| **count > 0)
.map(|(bucket_id, count)| (bucket_id as u64, *count))
.collect();
let bucket =
super::into_intermediate_bucket_result(self.accessor_idx, entries, sub_aggs, agg_data)?;
results.push(name, IntermediateAggregationResult::Bucket(bucket))?;
Ok(())
}
fn collect_block(
&mut self,
docs: &[crate::DocId],
agg_data: &mut AggregationsSegmentCtx,
) -> crate::Result<()> {
if docs.len() > MAX_BATCH_SIZE {
for batch in docs.chunks(MAX_BATCH_SIZE) {
self.collect_block(batch, agg_data)?;
}
}
let mut req_data = agg_data.take_term_req_data(self.accessor_idx);
let mem_pre = self.get_memory_consumption();
if let Some(missing) = req_data.missing_value_for_accessor {
req_data.column_block_accessor.fetch_block_with_missing(
docs,
&req_data.accessor,
missing,
);
} else {
req_data
.column_block_accessor
.fetch_block(docs, &req_data.accessor);
}
// has subagg
if req_data.sub_aggregation_blueprint.is_some() {
for (doc, term_id) in req_data
.column_block_accessor
.iter_docid_vals(docs, &req_data.accessor)
{
if let Some(allowed_bs) = req_data.allowed_term_ids.as_ref() {
if !allowed_bs.contains(term_id as u32) {
continue;
}
}
self.term_buckets.doc_buffers[term_id as usize].push(doc);
}
for (bucket_id, docs) in self.term_buckets.doc_buffers.iter_mut().enumerate() {
self.term_buckets.entries[bucket_id] += docs.len() as u32;
self.term_buckets.sub_aggs[bucket_id].collect_block(&docs[..], agg_data)?;
docs.clear();
}
} else {
for term_id in req_data.column_block_accessor.iter_vals() {
if let Some(allowed_bs) = req_data.allowed_term_ids.as_ref() {
if !allowed_bs.contains(term_id as u32) {
continue;
}
}
self.term_buckets.entries[term_id as usize] += 1;
}
}
let mem_delta = self.get_memory_consumption() - mem_pre;
if mem_delta > 0 {
agg_data
.context
.limits
.add_memory_consumed(mem_delta as u64)?;
}
agg_data.put_back_term_req_data(self.accessor_idx, req_data);
Ok(())
}
fn collect(
&mut self,
doc: crate::DocId,
agg_data: &mut AggregationsSegmentCtx,
) -> crate::Result<()> {
self.collect_block(&[doc], agg_data)
}
fn flush(&mut self, agg_data: &mut AggregationsSegmentCtx) -> crate::Result<()> {
for sub_aggregations in &mut self.term_buckets.sub_aggs.iter_mut() {
sub_aggregations.as_mut().flush(agg_data)?;
}
Ok(())
}
}

View File

@@ -1,39 +1,13 @@
use columnar::{Column, ColumnType};
use rustc_hash::FxHashMap;
use crate::aggregation::agg_data::{
build_segment_agg_collectors, AggRefNode, AggregationsSegmentCtx,
};
use crate::aggregation::bucket::term_agg::TermsAggregation;
use crate::aggregation::agg_req_with_accessor::AggregationsWithAccessor;
use crate::aggregation::intermediate_agg_result::{
IntermediateAggregationResult, IntermediateAggregationResults, IntermediateBucketResult,
IntermediateKey, IntermediateTermBucketEntry, IntermediateTermBucketResult,
};
use crate::aggregation::segment_agg_result::SegmentAggregationCollector;
/// Special aggregation to handle missing values for term aggregations.
/// This missing aggregation will check multiple columns for existence.
///
/// This is needed when:
/// - The field is multi-valued and we therefore have multiple columns
/// - The field is not text and missing is provided as string (we cannot use the numeric missing
/// value optimization)
#[derive(Default)]
pub struct MissingTermAggReqData {
/// The accessors to check for existence of a value.
pub accessors: Vec<(Column<u64>, ColumnType)>,
/// The name of the aggregation.
pub name: String,
/// The original terms aggregation request.
pub req: TermsAggregation,
}
impl MissingTermAggReqData {
/// Estimate the memory consumption of this struct in bytes.
pub fn get_memory_consumption(&self) -> usize {
std::mem::size_of::<Self>()
}
}
use crate::aggregation::segment_agg_result::{
build_segment_agg_collector, SegmentAggregationCollector,
};
/// The specialized missing term aggregation.
#[derive(Default, Debug, Clone)]
@@ -44,13 +18,12 @@ pub struct TermMissingAgg {
}
impl TermMissingAgg {
pub(crate) fn new(
req_data: &mut AggregationsSegmentCtx,
node: &AggRefNode,
accessor_idx: usize,
sub_aggregations: &mut AggregationsWithAccessor,
) -> crate::Result<Self> {
let has_sub_aggregations = !node.children.is_empty();
let accessor_idx = node.idx_in_req_data;
let has_sub_aggregations = !sub_aggregations.is_empty();
let sub_agg = if has_sub_aggregations {
let sub_aggregation = build_segment_agg_collectors(req_data, &node.children)?;
let sub_aggregation = build_segment_agg_collector(sub_aggregations)?;
Some(sub_aggregation)
} else {
None
@@ -67,11 +40,16 @@ impl TermMissingAgg {
impl SegmentAggregationCollector for TermMissingAgg {
fn add_intermediate_aggregation_result(
self: Box<Self>,
agg_data: &AggregationsSegmentCtx,
agg_with_accessor: &AggregationsWithAccessor,
results: &mut IntermediateAggregationResults,
) -> crate::Result<()> {
let req_data = agg_data.get_missing_term_req_data(self.accessor_idx);
let term_agg = &req_data.req;
let name = agg_with_accessor.aggs.keys[self.accessor_idx].to_string();
let agg_with_accessor = &agg_with_accessor.aggs.values[self.accessor_idx];
let term_agg = agg_with_accessor
.agg
.agg
.as_term()
.expect("TermMissingAgg collector must be term agg req");
let missing = term_agg
.missing
.as_ref()
@@ -86,7 +64,10 @@ impl SegmentAggregationCollector for TermMissingAgg {
};
if let Some(sub_agg) = self.sub_agg {
let mut res = IntermediateAggregationResults::default();
sub_agg.add_intermediate_aggregation_result(agg_data, &mut res)?;
sub_agg.add_intermediate_aggregation_result(
&agg_with_accessor.sub_aggregation,
&mut res,
)?;
missing_entry.sub_aggregation = res;
}
entries.insert(missing.into(), missing_entry);
@@ -99,10 +80,7 @@ impl SegmentAggregationCollector for TermMissingAgg {
},
};
results.push(
req_data.name.to_string(),
IntermediateAggregationResult::Bucket(bucket),
)?;
results.push(name, IntermediateAggregationResult::Bucket(bucket))?;
Ok(())
}
@@ -110,17 +88,17 @@ impl SegmentAggregationCollector for TermMissingAgg {
fn collect(
&mut self,
doc: crate::DocId,
agg_data: &mut AggregationsSegmentCtx,
agg_with_accessor: &mut AggregationsWithAccessor,
) -> crate::Result<()> {
let req_data = agg_data.get_missing_term_req_data(self.accessor_idx);
let has_value = req_data
let agg = &mut agg_with_accessor.aggs.values[self.accessor_idx];
let has_value = agg
.accessors
.iter()
.any(|(acc, _)| acc.index.has_value(doc));
if !has_value {
self.missing_count += 1;
if let Some(sub_agg) = self.sub_agg.as_mut() {
sub_agg.collect(doc, agg_data)?;
sub_agg.collect(doc, &mut agg.sub_aggregation)?;
}
}
Ok(())
@@ -129,10 +107,10 @@ impl SegmentAggregationCollector for TermMissingAgg {
fn collect_block(
&mut self,
docs: &[crate::DocId],
agg_data: &mut AggregationsSegmentCtx,
agg_with_accessor: &mut AggregationsWithAccessor,
) -> crate::Result<()> {
for doc in docs {
self.collect(*doc, agg_data)?;
self.collect(*doc, agg_with_accessor)?;
}
Ok(())
}

View File

@@ -1,6 +1,6 @@
use super::agg_req_with_accessor::AggregationsWithAccessor;
use super::intermediate_agg_result::IntermediateAggregationResults;
use super::segment_agg_result::SegmentAggregationCollector;
use crate::aggregation::agg_data::AggregationsSegmentCtx;
use crate::DocId;
pub(crate) const DOC_BLOCK_SIZE: usize = 64;
@@ -37,23 +37,23 @@ impl SegmentAggregationCollector for BufAggregationCollector {
#[inline]
fn add_intermediate_aggregation_result(
self: Box<Self>,
agg_data: &AggregationsSegmentCtx,
agg_with_accessor: &AggregationsWithAccessor,
results: &mut IntermediateAggregationResults,
) -> crate::Result<()> {
Box::new(self.collector).add_intermediate_aggregation_result(agg_data, results)
Box::new(self.collector).add_intermediate_aggregation_result(agg_with_accessor, results)
}
#[inline]
fn collect(
&mut self,
doc: crate::DocId,
agg_data: &mut AggregationsSegmentCtx,
agg_with_accessor: &mut AggregationsWithAccessor,
) -> crate::Result<()> {
self.staged_docs[self.num_staged_docs] = doc;
self.num_staged_docs += 1;
if self.num_staged_docs == self.staged_docs.len() {
self.collector
.collect_block(&self.staged_docs[..self.num_staged_docs], agg_data)?;
.collect_block(&self.staged_docs[..self.num_staged_docs], agg_with_accessor)?;
self.num_staged_docs = 0;
}
Ok(())
@@ -63,20 +63,20 @@ impl SegmentAggregationCollector for BufAggregationCollector {
fn collect_block(
&mut self,
docs: &[crate::DocId],
agg_data: &mut AggregationsSegmentCtx,
agg_with_accessor: &mut AggregationsWithAccessor,
) -> crate::Result<()> {
self.collector.collect_block(docs, agg_data)?;
self.collector.collect_block(docs, agg_with_accessor)?;
Ok(())
}
#[inline]
fn flush(&mut self, agg_data: &mut AggregationsSegmentCtx) -> crate::Result<()> {
fn flush(&mut self, agg_with_accessor: &mut AggregationsWithAccessor) -> crate::Result<()> {
self.collector
.collect_block(&self.staged_docs[..self.num_staged_docs], agg_data)?;
.collect_block(&self.staged_docs[..self.num_staged_docs], agg_with_accessor)?;
self.num_staged_docs = 0;
self.collector.flush(agg_data)?;
self.collector.flush(agg_with_accessor)?;
Ok(())
}

View File

@@ -1,12 +1,12 @@
use super::agg_req::Aggregations;
use super::agg_req_with_accessor::AggregationsWithAccessor;
use super::agg_result::AggregationResults;
use super::buf_collector::BufAggregationCollector;
use super::intermediate_agg_result::IntermediateAggregationResults;
use super::segment_agg_result::SegmentAggregationCollector;
use super::AggContextParams;
use crate::aggregation::agg_data::{
build_aggregations_data_from_req, build_segment_agg_collectors_root, AggregationsSegmentCtx,
use super::segment_agg_result::{
build_segment_agg_collector, AggregationLimitsGuard, SegmentAggregationCollector,
};
use crate::aggregation::agg_req_with_accessor::get_aggs_with_segment_accessor_and_validate;
use crate::collector::{Collector, SegmentCollector};
use crate::index::SegmentReader;
use crate::{DocId, SegmentOrdinal, TantivyError};
@@ -22,7 +22,7 @@ pub const DEFAULT_MEMORY_LIMIT: u64 = 500_000_000;
/// The collector collects all aggregations by the underlying aggregation request.
pub struct AggregationCollector {
agg: Aggregations,
context: AggContextParams,
limits: AggregationLimitsGuard,
}
impl AggregationCollector {
@@ -30,8 +30,8 @@ impl AggregationCollector {
///
/// Aggregation fails when the limits in `AggregationLimits` is exceeded. (memory limit and
/// bucket limit)
pub fn from_aggs(agg: Aggregations, context: AggContextParams) -> Self {
Self { agg, context }
pub fn from_aggs(agg: Aggregations, limits: AggregationLimitsGuard) -> Self {
Self { agg, limits }
}
}
@@ -45,7 +45,7 @@ impl AggregationCollector {
/// into the final `AggregationResults` via the `into_final_result()` method.
pub struct DistributedAggregationCollector {
agg: Aggregations,
context: AggContextParams,
limits: AggregationLimitsGuard,
}
impl DistributedAggregationCollector {
@@ -53,8 +53,8 @@ impl DistributedAggregationCollector {
///
/// Aggregation fails when the limits in `AggregationLimits` is exceeded. (memory limit and
/// bucket limit)
pub fn from_aggs(agg: Aggregations, context: AggContextParams) -> Self {
Self { agg, context }
pub fn from_aggs(agg: Aggregations, limits: AggregationLimitsGuard) -> Self {
Self { agg, limits }
}
}
@@ -72,7 +72,7 @@ impl Collector for DistributedAggregationCollector {
&self.agg,
reader,
segment_local_id,
&self.context,
&self.limits,
)
}
@@ -102,7 +102,7 @@ impl Collector for AggregationCollector {
&self.agg,
reader,
segment_local_id,
&self.context,
&self.limits,
)
}
@@ -115,7 +115,7 @@ impl Collector for AggregationCollector {
segment_fruits: Vec<<Self::Child as SegmentCollector>::Fruit>,
) -> crate::Result<Self::Fruit> {
let res = merge_fruits(segment_fruits)?;
res.into_final_result(self.agg.clone(), self.context.limits.clone())
res.into_final_result(self.agg.clone(), self.limits.clone())
}
}
@@ -135,7 +135,7 @@ fn merge_fruits(
/// `AggregationSegmentCollector` does the aggregation collection on a segment.
pub struct AggregationSegmentCollector {
aggs_with_accessor: AggregationsSegmentCtx,
aggs_with_accessor: AggregationsWithAccessor,
agg_collector: BufAggregationCollector,
error: Option<TantivyError>,
}
@@ -147,15 +147,14 @@ impl AggregationSegmentCollector {
agg: &Aggregations,
reader: &SegmentReader,
segment_ordinal: SegmentOrdinal,
context: &AggContextParams,
limits: &AggregationLimitsGuard,
) -> crate::Result<Self> {
let mut agg_data =
build_aggregations_data_from_req(agg, reader, segment_ordinal, context.clone())?;
let mut aggs_with_accessor =
get_aggs_with_segment_accessor_and_validate(agg, reader, segment_ordinal, limits)?;
let result =
BufAggregationCollector::new(build_segment_agg_collectors_root(&mut agg_data)?);
BufAggregationCollector::new(build_segment_agg_collector(&mut aggs_with_accessor)?);
Ok(AggregationSegmentCollector {
aggs_with_accessor: agg_data,
aggs_with_accessor,
agg_collector: result,
error: None,
})

View File

@@ -24,9 +24,7 @@ use super::metric::{
};
use super::segment_agg_result::AggregationLimitsGuard;
use super::{format_date, AggregationError, Key, SerializedKey};
use crate::aggregation::agg_result::{
AggregationResults, BucketEntries, BucketEntry, FilterBucketResult,
};
use crate::aggregation::agg_result::{AggregationResults, BucketEntries, BucketEntry};
use crate::aggregation::bucket::TermsAggregationInternal;
use crate::aggregation::metric::CardinalityCollector;
use crate::TantivyError;
@@ -181,17 +179,12 @@ impl IntermediateAggregationResults {
}
/// Merge another intermediate aggregation result into this result.
pub fn merge_fruits(&mut self, mut other: IntermediateAggregationResults) -> crate::Result<()> {
for (key, left) in self.aggs_res.iter_mut() {
if let Some(key) = other.aggs_res.remove(key) {
left.merge_fruits(key)?;
}
}
// Move remainder of other aggs_res into self.
// Note: Currently we don't expect this to happen, as we create empty intermediate results
// via [IntermediateAggregationResults::empty_from_req].
for (key, value) in other.aggs_res {
self.aggs_res.insert(key, value);
///
/// The order of the values need to be the same on both results. This is ensured when the same
/// (key values) are present on the underlying `VecWithNames` struct.
pub fn merge_fruits(&mut self, other: IntermediateAggregationResults) -> crate::Result<()> {
for (left, right) in self.aggs_res.values_mut().zip(other.aggs_res.into_values()) {
left.merge_fruits(right)?;
}
Ok(())
}
@@ -248,16 +241,11 @@ pub(crate) fn empty_from_req(req: &Aggregation) -> IntermediateAggregationResult
Cardinality(_) => IntermediateAggregationResult::Metric(
IntermediateMetricResult::Cardinality(CardinalityCollector::default()),
),
Filter(_) => IntermediateAggregationResult::Bucket(IntermediateBucketResult::Filter {
doc_count: 0,
sub_aggregations: IntermediateAggregationResults::default(),
}),
}
}
/// An aggregation is either a bucket or a metric.
#[derive(Clone, Debug, PartialEq, Serialize, Deserialize)]
#[allow(clippy::large_enum_variant)]
pub enum IntermediateAggregationResult {
/// Bucket variant
Bucket(IntermediateBucketResult),
@@ -438,13 +426,6 @@ pub enum IntermediateBucketResult {
/// The term buckets
buckets: IntermediateTermBucketResult,
},
/// Filter aggregation - a single bucket with sub-aggregations
Filter {
/// Document count in the filter bucket
doc_count: u64,
/// Sub-aggregation results
sub_aggregations: IntermediateAggregationResults,
},
}
impl IntermediateBucketResult {
@@ -528,18 +509,6 @@ impl IntermediateBucketResult {
req.sub_aggregation(),
limits,
),
IntermediateBucketResult::Filter {
doc_count,
sub_aggregations,
} => {
// Convert sub-aggregation results to final format
let final_sub_aggregations = sub_aggregations
.into_final_result(req.sub_aggregation().clone(), limits.clone())?;
Ok(BucketResult::Filter(FilterBucketResult {
doc_count,
sub_aggregations: final_sub_aggregations,
}))
}
}
}
@@ -593,19 +562,6 @@ impl IntermediateBucketResult {
*buckets_left = buckets?;
}
(
IntermediateBucketResult::Filter {
doc_count: doc_count_left,
sub_aggregations: sub_aggs_left,
},
IntermediateBucketResult::Filter {
doc_count: doc_count_right,
sub_aggregations: sub_aggs_right,
},
) => {
*doc_count_left += doc_count_right;
sub_aggs_left.merge_fruits(sub_aggs_right)?;
}
(IntermediateBucketResult::Range(_), _) => {
panic!("try merge on different types")
}
@@ -615,9 +571,6 @@ impl IntermediateBucketResult {
(IntermediateBucketResult::Terms { .. }, _) => {
panic!("try merge on different types")
}
(IntermediateBucketResult::Filter { .. }, _) => {
panic!("try merge on different types")
}
}
Ok(())
}

View File

@@ -2,13 +2,15 @@ use std::collections::hash_map::DefaultHasher;
use std::hash::{BuildHasher, Hasher};
use columnar::column_values::CompactSpaceU64Accessor;
use columnar::{Column, ColumnBlockAccessor, ColumnType, Dictionary, StrColumn};
use columnar::Dictionary;
use common::f64_to_u64;
use hyperloglogplus::{HyperLogLog, HyperLogLogPlus};
use rustc_hash::FxHashSet;
use serde::{Deserialize, Serialize};
use crate::aggregation::agg_data::AggregationsSegmentCtx;
use crate::aggregation::agg_req_with_accessor::{
AggregationWithAccessor, AggregationsWithAccessor,
};
use crate::aggregation::intermediate_agg_result::{
IntermediateAggregationResult, IntermediateAggregationResults, IntermediateMetricResult,
};
@@ -95,32 +97,6 @@ pub struct CardinalityAggregationReq {
pub missing: Option<Key>,
}
/// Contains all information required by the SegmentCardinalityCollector to perform the
/// cardinality aggregation on a segment.
pub struct CardinalityAggReqData {
/// The column accessor to access the fast field values.
pub accessor: Column<u64>,
/// The column_type of the field.
pub column_type: ColumnType,
/// The string dictionary column if the field is of type string.
pub str_dict_column: Option<StrColumn>,
/// The missing value normalized to the internal u64 representation of the field type.
pub missing_value_for_accessor: Option<u64>,
/// The column block accessor to access the fast field values.
pub(crate) column_block_accessor: ColumnBlockAccessor<u64>,
/// The name of the aggregation.
pub name: String,
/// The aggregation request.
pub req: CardinalityAggregationReq,
}
impl CardinalityAggReqData {
/// Estimate the memory consumption of this struct in bytes.
pub fn get_memory_consumption(&self) -> usize {
std::mem::size_of::<Self>()
}
}
impl CardinalityAggregationReq {
/// Creates a new [`CardinalityAggregationReq`] instance from a field name.
pub fn from_field_name(field_name: String) -> Self {
@@ -139,44 +115,47 @@ impl CardinalityAggregationReq {
pub(crate) struct SegmentCardinalityCollector {
cardinality: CardinalityCollector,
entries: FxHashSet<u64>,
column_type: ColumnType,
accessor_idx: usize,
missing: Option<Key>,
}
impl SegmentCardinalityCollector {
pub fn from_req(column_type: ColumnType, accessor_idx: usize) -> Self {
pub fn from_req(column_type: ColumnType, accessor_idx: usize, missing: &Option<Key>) -> Self {
Self {
cardinality: CardinalityCollector::new(column_type as u8),
entries: Default::default(),
column_type,
accessor_idx,
missing: missing.clone(),
}
}
fn fetch_block_with_field(
&mut self,
docs: &[crate::DocId],
agg_data: &mut CardinalityAggReqData,
agg_accessor: &mut AggregationWithAccessor,
) {
if let Some(missing) = agg_data.missing_value_for_accessor {
agg_data.column_block_accessor.fetch_block_with_missing(
if let Some(missing) = agg_accessor.missing_value_for_accessor {
agg_accessor.column_block_accessor.fetch_block_with_missing(
docs,
&agg_data.accessor,
&agg_accessor.accessor,
missing,
);
} else {
agg_data
agg_accessor
.column_block_accessor
.fetch_block(docs, &agg_data.accessor);
.fetch_block(docs, &agg_accessor.accessor);
}
}
fn into_intermediate_metric_result(
mut self,
agg_data: &AggregationsSegmentCtx,
agg_with_accessor: &AggregationWithAccessor,
) -> crate::Result<IntermediateMetricResult> {
let req_data = &agg_data.get_cardinality_req_data(self.accessor_idx);
if req_data.column_type == ColumnType::Str {
if self.column_type == ColumnType::Str {
let fallback_dict = Dictionary::empty();
let dict = req_data
let dict = agg_with_accessor
.str_dict_column
.as_ref()
.map(|el| el.dictionary())
@@ -201,10 +180,10 @@ impl SegmentCardinalityCollector {
})?;
if has_missing {
// Replace missing with the actual value provided
let missing_key =
req_data.req.missing.as_ref().expect(
"Found sentinel value u64::MAX for term_ord but `missing` is not set",
);
let missing_key = self
.missing
.as_ref()
.expect("Found sentinel value u64::MAX for term_ord but `missing` is not set");
match missing_key {
Key::Str(missing) => {
self.cardinality.sketch.insert_any(&missing);
@@ -230,13 +209,13 @@ impl SegmentCardinalityCollector {
impl SegmentAggregationCollector for SegmentCardinalityCollector {
fn add_intermediate_aggregation_result(
self: Box<Self>,
agg_data: &AggregationsSegmentCtx,
agg_with_accessor: &AggregationsWithAccessor,
results: &mut IntermediateAggregationResults,
) -> crate::Result<()> {
let req_data = &agg_data.get_cardinality_req_data(self.accessor_idx);
let name = req_data.name.to_string();
let name = agg_with_accessor.aggs.keys[self.accessor_idx].to_string();
let agg_with_accessor = &agg_with_accessor.aggs.values[self.accessor_idx];
let intermediate_result = self.into_intermediate_metric_result(agg_data)?;
let intermediate_result = self.into_intermediate_metric_result(agg_with_accessor)?;
results.push(
name,
IntermediateAggregationResult::Metric(intermediate_result),
@@ -248,26 +227,26 @@ impl SegmentAggregationCollector for SegmentCardinalityCollector {
fn collect(
&mut self,
doc: crate::DocId,
agg_data: &mut AggregationsSegmentCtx,
agg_with_accessor: &mut AggregationsWithAccessor,
) -> crate::Result<()> {
self.collect_block(&[doc], agg_data)
self.collect_block(&[doc], agg_with_accessor)
}
fn collect_block(
&mut self,
docs: &[crate::DocId],
agg_data: &mut AggregationsSegmentCtx,
agg_with_accessor: &mut AggregationsWithAccessor,
) -> crate::Result<()> {
let req_data = agg_data.get_cardinality_req_data_mut(self.accessor_idx);
self.fetch_block_with_field(docs, req_data);
let bucket_agg_accessor = &mut agg_with_accessor.aggs.values[self.accessor_idx];
self.fetch_block_with_field(docs, bucket_agg_accessor);
let col_block_accessor = &req_data.column_block_accessor;
if req_data.column_type == ColumnType::Str {
let col_block_accessor = &bucket_agg_accessor.column_block_accessor;
if self.column_type == ColumnType::Str {
for term_ord in col_block_accessor.iter_vals() {
self.entries.insert(term_ord);
}
} else if req_data.column_type == ColumnType::IpAddr {
let compact_space_accessor = req_data
} else if self.column_type == ColumnType::IpAddr {
let compact_space_accessor = bucket_agg_accessor
.accessor
.values
.clone()

View File

@@ -4,11 +4,12 @@ use std::mem;
use serde::{Deserialize, Serialize};
use super::*;
use crate::aggregation::agg_data::AggregationsSegmentCtx;
use crate::aggregation::agg_req_with_accessor::{
AggregationWithAccessor, AggregationsWithAccessor,
};
use crate::aggregation::intermediate_agg_result::{
IntermediateAggregationResult, IntermediateAggregationResults, IntermediateMetricResult,
};
use crate::aggregation::metric::MetricAggReqData;
use crate::aggregation::segment_agg_result::SegmentAggregationCollector;
use crate::aggregation::*;
use crate::{DocId, TantivyError};
@@ -347,20 +348,20 @@ impl SegmentExtendedStatsCollector {
pub(crate) fn collect_block_with_field(
&mut self,
docs: &[DocId],
req_data: &mut MetricAggReqData,
agg_accessor: &mut AggregationWithAccessor,
) {
if let Some(missing) = self.missing.as_ref() {
req_data.column_block_accessor.fetch_block_with_missing(
agg_accessor.column_block_accessor.fetch_block_with_missing(
docs,
&req_data.accessor,
&agg_accessor.accessor,
*missing,
);
} else {
req_data
agg_accessor
.column_block_accessor
.fetch_block(docs, &req_data.accessor);
.fetch_block(docs, &agg_accessor.accessor);
}
for val in req_data.column_block_accessor.iter_vals() {
for val in agg_accessor.column_block_accessor.iter_vals() {
let val1 = f64_from_fastfield_u64(val, &self.field_type);
self.extended_stats.collect(val1);
}
@@ -371,10 +372,10 @@ impl SegmentAggregationCollector for SegmentExtendedStatsCollector {
#[inline]
fn add_intermediate_aggregation_result(
self: Box<Self>,
agg_data: &AggregationsSegmentCtx,
agg_with_accessor: &AggregationsWithAccessor,
results: &mut IntermediateAggregationResults,
) -> crate::Result<()> {
let name = agg_data.get_metric_req_data(self.accessor_idx).name.clone();
let name = agg_with_accessor.aggs.keys[self.accessor_idx].to_string();
results.push(
name,
IntermediateAggregationResult::Metric(IntermediateMetricResult::ExtendedStats(
@@ -389,12 +390,12 @@ impl SegmentAggregationCollector for SegmentExtendedStatsCollector {
fn collect(
&mut self,
doc: crate::DocId,
agg_data: &mut AggregationsSegmentCtx,
agg_with_accessor: &mut AggregationsWithAccessor,
) -> crate::Result<()> {
let req_data = agg_data.get_metric_req_data(self.accessor_idx);
let field = &agg_with_accessor.aggs.values[self.accessor_idx].accessor;
if let Some(missing) = self.missing {
let mut has_val = false;
for val in req_data.accessor.values_for_doc(doc) {
for val in field.values_for_doc(doc) {
let val1 = f64_from_fastfield_u64(val, &self.field_type);
self.extended_stats.collect(val1);
has_val = true;
@@ -404,7 +405,7 @@ impl SegmentAggregationCollector for SegmentExtendedStatsCollector {
.collect(f64_from_fastfield_u64(missing, &self.field_type));
}
} else {
for val in req_data.accessor.values_for_doc(doc) {
for val in field.values_for_doc(doc) {
let val1 = f64_from_fastfield_u64(val, &self.field_type);
self.extended_stats.collect(val1);
}
@@ -417,10 +418,10 @@ impl SegmentAggregationCollector for SegmentExtendedStatsCollector {
fn collect_block(
&mut self,
docs: &[crate::DocId],
agg_data: &mut AggregationsSegmentCtx,
agg_with_accessor: &mut AggregationsWithAccessor,
) -> crate::Result<()> {
let req_data = agg_data.get_metric_req_data_mut(self.accessor_idx);
self.collect_block_with_field(docs, req_data);
let field = &mut agg_with_accessor.aggs.values[self.accessor_idx];
self.collect_block_with_field(docs, field);
Ok(())
}
}

View File

@@ -31,7 +31,6 @@ use std::collections::HashMap;
pub use average::*;
pub use cardinality::*;
use columnar::{Column, ColumnBlockAccessor, ColumnType};
pub use count::*;
pub use extended_stats::*;
pub use max::*;
@@ -45,35 +44,6 @@ pub use top_hits::*;
use crate::schema::OwnedValue;
/// Contains all information required by metric aggregations like avg, min, max, sum, stats,
/// extended_stats, count, percentiles.
#[repr(C)]
pub struct MetricAggReqData {
/// True if the field is of number or date type.
pub is_number_or_date_type: bool,
/// The type of the field.
pub field_type: ColumnType,
/// The missing value normalized to the internal u64 representation of the field type.
pub missing_u64: Option<u64>,
/// The column block accessor to access the fast field values.
pub column_block_accessor: ColumnBlockAccessor<u64>,
/// The column accessor to access the fast field values.
pub accessor: Column<u64>,
/// Used when converting to intermediate result
pub collecting_for: StatsType,
/// The missing value
pub missing: Option<f64>,
/// The name of the aggregation.
pub name: String,
}
impl MetricAggReqData {
/// Estimate the memory consumption of this struct in bytes.
pub fn get_memory_consumption(&self) -> usize {
std::mem::size_of::<Self>()
}
}
/// Single-metric aggregations use this common result structure.
///
/// Main reason to wrap it in value is to match elasticsearch output structure.

View File

@@ -3,11 +3,12 @@ use std::fmt::Debug;
use serde::{Deserialize, Serialize};
use super::*;
use crate::aggregation::agg_data::AggregationsSegmentCtx;
use crate::aggregation::agg_req_with_accessor::{
AggregationWithAccessor, AggregationsWithAccessor,
};
use crate::aggregation::intermediate_agg_result::{
IntermediateAggregationResult, IntermediateAggregationResults, IntermediateMetricResult,
};
use crate::aggregation::metric::MetricAggReqData;
use crate::aggregation::segment_agg_result::SegmentAggregationCollector;
use crate::aggregation::*;
use crate::{DocId, TantivyError};
@@ -111,8 +112,7 @@ impl PercentilesAggregationReq {
&self.field
}
/// Validates the request parameters.
pub fn validate(&self) -> crate::Result<()> {
fn validate(&self) -> crate::Result<()> {
if let Some(percents) = self.percents.as_ref() {
let all_in_range = percents
.iter()
@@ -133,8 +133,10 @@ impl PercentilesAggregationReq {
#[derive(Clone, Debug, PartialEq)]
pub(crate) struct SegmentPercentilesCollector {
field_type: ColumnType,
pub(crate) percentiles: PercentilesCollector,
pub(crate) accessor_idx: usize,
missing: Option<u64>,
}
#[derive(Clone, Serialize, Deserialize)]
@@ -229,32 +231,43 @@ impl PercentilesCollector {
}
impl SegmentPercentilesCollector {
pub fn from_req_and_validate(accessor_idx: usize) -> crate::Result<Self> {
pub fn from_req_and_validate(
req: &PercentilesAggregationReq,
field_type: ColumnType,
accessor_idx: usize,
) -> crate::Result<Self> {
req.validate()?;
let missing = req
.missing
.and_then(|val| f64_to_fastfield_u64(val, &field_type));
Ok(Self {
field_type,
percentiles: PercentilesCollector::new(),
accessor_idx,
missing,
})
}
#[inline]
pub(crate) fn collect_block_with_field(
&mut self,
docs: &[DocId],
req_data: &mut MetricAggReqData,
agg_accessor: &mut AggregationWithAccessor,
) {
if let Some(missing) = req_data.missing_u64.as_ref() {
req_data.column_block_accessor.fetch_block_with_missing(
if let Some(missing) = self.missing.as_ref() {
agg_accessor.column_block_accessor.fetch_block_with_missing(
docs,
&req_data.accessor,
&agg_accessor.accessor,
*missing,
);
} else {
req_data
agg_accessor
.column_block_accessor
.fetch_block(docs, &req_data.accessor);
.fetch_block(docs, &agg_accessor.accessor);
}
for val in req_data.column_block_accessor.iter_vals() {
let val1 = f64_from_fastfield_u64(val, &req_data.field_type);
for val in agg_accessor.column_block_accessor.iter_vals() {
let val1 = f64_from_fastfield_u64(val, &self.field_type);
self.percentiles.collect(val1);
}
}
@@ -264,10 +277,10 @@ impl SegmentAggregationCollector for SegmentPercentilesCollector {
#[inline]
fn add_intermediate_aggregation_result(
self: Box<Self>,
agg_data: &AggregationsSegmentCtx,
agg_with_accessor: &AggregationsWithAccessor,
results: &mut IntermediateAggregationResults,
) -> crate::Result<()> {
let name = agg_data.get_metric_req_data(self.accessor_idx).name.clone();
let name = agg_with_accessor.aggs.keys[self.accessor_idx].to_string();
let intermediate_metric_result = IntermediateMetricResult::Percentiles(self.percentiles);
results.push(
@@ -282,24 +295,24 @@ impl SegmentAggregationCollector for SegmentPercentilesCollector {
fn collect(
&mut self,
doc: crate::DocId,
agg_data: &mut AggregationsSegmentCtx,
agg_with_accessor: &mut AggregationsWithAccessor,
) -> crate::Result<()> {
let req_data = agg_data.get_metric_req_data(self.accessor_idx);
let field = &agg_with_accessor.aggs.values[self.accessor_idx].accessor;
if let Some(missing) = req_data.missing_u64 {
if let Some(missing) = self.missing {
let mut has_val = false;
for val in req_data.accessor.values_for_doc(doc) {
let val1 = f64_from_fastfield_u64(val, &req_data.field_type);
for val in field.values_for_doc(doc) {
let val1 = f64_from_fastfield_u64(val, &self.field_type);
self.percentiles.collect(val1);
has_val = true;
}
if !has_val {
self.percentiles
.collect(f64_from_fastfield_u64(missing, &req_data.field_type));
.collect(f64_from_fastfield_u64(missing, &self.field_type));
}
} else {
for val in req_data.accessor.values_for_doc(doc) {
let val1 = f64_from_fastfield_u64(val, &req_data.field_type);
for val in field.values_for_doc(doc) {
let val1 = f64_from_fastfield_u64(val, &self.field_type);
self.percentiles.collect(val1);
}
}
@@ -311,10 +324,10 @@ impl SegmentAggregationCollector for SegmentPercentilesCollector {
fn collect_block(
&mut self,
docs: &[crate::DocId],
agg_data: &mut AggregationsSegmentCtx,
agg_with_accessor: &mut AggregationsWithAccessor,
) -> crate::Result<()> {
let req_data = agg_data.get_metric_req_data_mut(self.accessor_idx);
self.collect_block_with_field(docs, req_data);
let field = &mut agg_with_accessor.aggs.values[self.accessor_idx];
self.collect_block_with_field(docs, field);
Ok(())
}
}

View File

@@ -3,11 +3,12 @@ use std::fmt::Debug;
use serde::{Deserialize, Serialize};
use super::*;
use crate::aggregation::agg_data::AggregationsSegmentCtx;
use crate::aggregation::agg_req_with_accessor::{
AggregationWithAccessor, AggregationsWithAccessor,
};
use crate::aggregation::intermediate_agg_result::{
IntermediateAggregationResult, IntermediateAggregationResults, IntermediateMetricResult,
};
use crate::aggregation::metric::MetricAggReqData;
use crate::aggregation::segment_agg_result::SegmentAggregationCollector;
use crate::aggregation::*;
use crate::{DocId, TantivyError};
@@ -165,65 +166,74 @@ impl IntermediateStats {
}
}
/// The type of stats aggregation to perform.
/// Note that not all stats types are supported in the stats aggregation.
#[derive(Clone, Copy, Debug)]
pub enum StatsType {
/// The average of the values.
#[derive(Clone, Debug, PartialEq)]
pub(crate) enum SegmentStatsType {
Average,
/// The count of the values.
Count,
/// The maximum value.
Max,
/// The minimum value.
Min,
/// The stats (count, sum, min, max, avg) of the values.
Stats,
/// The extended stats (count, sum, min, max, avg, sum_of_squares, variance, std_deviation,
ExtendedStats(Option<f64>), // sigma
/// The sum of the values.
Sum,
/// The percentiles of the values.
Percentiles,
}
#[derive(Clone, Debug)]
#[derive(Clone, Debug, PartialEq)]
pub(crate) struct SegmentStatsCollector {
missing: Option<u64>,
field_type: ColumnType,
pub(crate) collecting_for: SegmentStatsType,
pub(crate) stats: IntermediateStats,
pub(crate) accessor_idx: usize,
val_cache: Vec<u64>,
}
impl SegmentStatsCollector {
pub fn from_req(accessor_idx: usize) -> Self {
pub fn from_req(
field_type: ColumnType,
collecting_for: SegmentStatsType,
accessor_idx: usize,
missing: Option<f64>,
) -> Self {
let missing = missing.and_then(|val| f64_to_fastfield_u64(val, &field_type));
Self {
field_type,
collecting_for,
stats: IntermediateStats::default(),
accessor_idx,
missing,
val_cache: Default::default(),
}
}
#[inline]
pub(crate) fn collect_block_with_field(
&mut self,
docs: &[DocId],
req_data: &mut MetricAggReqData,
agg_accessor: &mut AggregationWithAccessor,
) {
if let Some(missing) = req_data.missing_u64.as_ref() {
req_data.column_block_accessor.fetch_block_with_missing(
if let Some(missing) = self.missing.as_ref() {
agg_accessor.column_block_accessor.fetch_block_with_missing(
docs,
&req_data.accessor,
&agg_accessor.accessor,
*missing,
);
} else {
req_data
agg_accessor
.column_block_accessor
.fetch_block(docs, &req_data.accessor);
.fetch_block(docs, &agg_accessor.accessor);
}
if req_data.is_number_or_date_type {
for val in req_data.column_block_accessor.iter_vals() {
let val1 = f64_from_fastfield_u64(val, &req_data.field_type);
if [
ColumnType::I64,
ColumnType::U64,
ColumnType::F64,
ColumnType::DateTime,
]
.contains(&self.field_type)
{
for val in agg_accessor.column_block_accessor.iter_vals() {
let val1 = f64_from_fastfield_u64(val, &self.field_type);
self.stats.collect(val1);
}
} else {
for _val in req_data.column_block_accessor.iter_vals() {
for _val in agg_accessor.column_block_accessor.iter_vals() {
// we ignore the value and simply record that we got something
self.stats.collect(0.0);
}
@@ -235,28 +245,27 @@ impl SegmentAggregationCollector for SegmentStatsCollector {
#[inline]
fn add_intermediate_aggregation_result(
self: Box<Self>,
agg_data: &AggregationsSegmentCtx,
agg_with_accessor: &AggregationsWithAccessor,
results: &mut IntermediateAggregationResults,
) -> crate::Result<()> {
let req = agg_data.get_metric_req_data(self.accessor_idx);
let name = req.name.clone();
let name = agg_with_accessor.aggs.keys[self.accessor_idx].to_string();
let intermediate_metric_result = match req.collecting_for {
StatsType::Average => {
let intermediate_metric_result = match self.collecting_for {
SegmentStatsType::Average => {
IntermediateMetricResult::Average(IntermediateAverage::from_collector(*self))
}
StatsType::Count => {
SegmentStatsType::Count => {
IntermediateMetricResult::Count(IntermediateCount::from_collector(*self))
}
StatsType::Max => IntermediateMetricResult::Max(IntermediateMax::from_collector(*self)),
StatsType::Min => IntermediateMetricResult::Min(IntermediateMin::from_collector(*self)),
StatsType::Stats => IntermediateMetricResult::Stats(self.stats),
StatsType::Sum => IntermediateMetricResult::Sum(IntermediateSum::from_collector(*self)),
_ => {
return Err(TantivyError::InvalidArgument(format!(
"Unsupported stats type for stats aggregation: {:?}",
req.collecting_for
)))
SegmentStatsType::Max => {
IntermediateMetricResult::Max(IntermediateMax::from_collector(*self))
}
SegmentStatsType::Min => {
IntermediateMetricResult::Min(IntermediateMin::from_collector(*self))
}
SegmentStatsType::Stats => IntermediateMetricResult::Stats(self.stats),
SegmentStatsType::Sum => {
IntermediateMetricResult::Sum(IntermediateSum::from_collector(*self))
}
};
@@ -272,23 +281,23 @@ impl SegmentAggregationCollector for SegmentStatsCollector {
fn collect(
&mut self,
doc: crate::DocId,
agg_data: &mut AggregationsSegmentCtx,
agg_with_accessor: &mut AggregationsWithAccessor,
) -> crate::Result<()> {
let req_data = agg_data.get_metric_req_data(self.accessor_idx);
if let Some(missing) = req_data.missing_u64 {
let field = &agg_with_accessor.aggs.values[self.accessor_idx].accessor;
if let Some(missing) = self.missing {
let mut has_val = false;
for val in req_data.accessor.values_for_doc(doc) {
let val1 = f64_from_fastfield_u64(val, &req_data.field_type);
for val in field.values_for_doc(doc) {
let val1 = f64_from_fastfield_u64(val, &self.field_type);
self.stats.collect(val1);
has_val = true;
}
if !has_val {
self.stats
.collect(f64_from_fastfield_u64(missing, &req_data.field_type));
.collect(f64_from_fastfield_u64(missing, &self.field_type));
}
} else {
for val in req_data.accessor.values_for_doc(doc) {
let val1 = f64_from_fastfield_u64(val, &req_data.field_type);
for val in field.values_for_doc(doc) {
let val1 = f64_from_fastfield_u64(val, &self.field_type);
self.stats.collect(val1);
}
}
@@ -300,10 +309,10 @@ impl SegmentAggregationCollector for SegmentStatsCollector {
fn collect_block(
&mut self,
docs: &[crate::DocId],
agg_data: &mut AggregationsSegmentCtx,
agg_with_accessor: &mut AggregationsWithAccessor,
) -> crate::Result<()> {
let req_data = agg_data.get_metric_req_data_mut(self.accessor_idx);
self.collect_block_with_field(docs, req_data);
let field = &mut agg_with_accessor.aggs.values[self.accessor_idx];
self.collect_block_with_field(docs, field);
Ok(())
}
}

View File

@@ -9,7 +9,6 @@ use serde::ser::SerializeMap;
use serde::{Deserialize, Deserializer, Serialize, Serializer};
use super::{TopHitsMetricResult, TopHitsVecEntry};
use crate::aggregation::agg_data::AggregationsSegmentCtx;
use crate::aggregation::bucket::Order;
use crate::aggregation::intermediate_agg_result::{
IntermediateAggregationResult, IntermediateMetricResult,
@@ -19,30 +18,6 @@ use crate::aggregation::AggregationError;
use crate::collector::TopNComputer;
use crate::schema::OwnedValue;
use crate::{DocAddress, DocId, SegmentOrdinal};
// duplicate import removed; already imported above
/// Contains all information required by the TopHitsSegmentCollector to perform the
/// top_hits aggregation on a segment.
#[derive(Default)]
pub struct TopHitsAggReqData {
/// The accessors to access the fast field values.
pub accessors: Vec<(Column<u64>, ColumnType)>,
/// The accessors to access the fast field values for retrieving document fields.
pub value_accessors: HashMap<String, Vec<DynamicColumn>>,
/// The ordinal of the segment this request data is for.
pub segment_ordinal: SegmentOrdinal,
/// The name of the aggregation.
pub name: String,
/// The top_hits aggregation request.
pub req: TopHitsAggregationReq,
}
impl TopHitsAggReqData {
/// Estimate the memory consumption of this struct in bytes.
pub fn get_memory_consumption(&self) -> usize {
std::mem::size_of::<Self>()
}
}
/// # Top Hits
///
@@ -591,18 +566,23 @@ impl TopHitsSegmentCollector {
impl SegmentAggregationCollector for TopHitsSegmentCollector {
fn add_intermediate_aggregation_result(
self: Box<Self>,
agg_data: &AggregationsSegmentCtx,
agg_with_accessor: &crate::aggregation::agg_req_with_accessor::AggregationsWithAccessor,
results: &mut crate::aggregation::intermediate_agg_result::IntermediateAggregationResults,
) -> crate::Result<()> {
let req_data = agg_data.get_top_hits_req_data(self.accessor_idx);
let name = agg_with_accessor.aggs.keys[self.accessor_idx].to_string();
let value_accessors = &req_data.value_accessors;
let value_accessors = &agg_with_accessor.aggs.values[self.accessor_idx].value_accessors;
let tophits_req = &agg_with_accessor.aggs.values[self.accessor_idx]
.agg
.agg
.as_top_hits()
.expect("aggregation request must be of type top hits");
let intermediate_result = IntermediateMetricResult::TopHits(
self.into_top_hits_collector(value_accessors, &req_data.req),
self.into_top_hits_collector(value_accessors, tophits_req),
);
results.push(
req_data.name.to_string(),
name,
IntermediateAggregationResult::Metric(intermediate_result),
)
}
@@ -611,22 +591,32 @@ impl SegmentAggregationCollector for TopHitsSegmentCollector {
fn collect(
&mut self,
doc_id: crate::DocId,
agg_data: &mut AggregationsSegmentCtx,
agg_with_accessor: &mut crate::aggregation::agg_req_with_accessor::AggregationsWithAccessor,
) -> crate::Result<()> {
let req_data = agg_data.get_top_hits_req_data(self.accessor_idx);
self.collect_with(doc_id, &req_data.req, &req_data.accessors)?;
let tophits_req = &agg_with_accessor.aggs.values[self.accessor_idx]
.agg
.agg
.as_top_hits()
.expect("aggregation request must be of type top hits");
let accessors = &agg_with_accessor.aggs.values[self.accessor_idx].accessors;
self.collect_with(doc_id, tophits_req, accessors)?;
Ok(())
}
fn collect_block(
&mut self,
docs: &[crate::DocId],
agg_data: &mut AggregationsSegmentCtx,
agg_with_accessor: &mut crate::aggregation::agg_req_with_accessor::AggregationsWithAccessor,
) -> crate::Result<()> {
let req_data = agg_data.get_top_hits_req_data(self.accessor_idx);
let tophits_req = &agg_with_accessor.aggs.values[self.accessor_idx]
.agg
.agg
.as_top_hits()
.expect("aggregation request must be of type top hits");
let accessors = &agg_with_accessor.aggs.values[self.accessor_idx].accessors;
// TODO: Consider getting fields with the column block accessor.
for doc in docs {
self.collect_with(*doc, &req_data.req, &req_data.accessors)?;
self.collect_with(*doc, tophits_req, accessors)?;
}
Ok(())
}

View File

@@ -127,10 +127,9 @@
//! [`AggregationResults`](agg_result::AggregationResults) via the
//! [`into_final_result`](intermediate_agg_result::IntermediateAggregationResults::into_final_result) method.
mod accessor_helpers;
mod agg_data;
mod agg_limits;
pub mod agg_req;
mod agg_req_with_accessor;
pub mod agg_result;
pub mod bucket;
mod buf_collector;
@@ -141,6 +140,7 @@ pub mod intermediate_agg_result;
pub mod metric;
mod segment_agg_result;
use std::collections::HashMap;
use std::fmt::Display;
#[cfg(test)]
@@ -160,28 +160,6 @@ use itertools::Itertools;
use serde::de::{self, Visitor};
use serde::{Deserialize, Deserializer, Serialize};
use crate::tokenizer::TokenizerManager;
/// Context parameters for aggregation execution
///
/// This struct holds shared resources needed during aggregation execution:
/// - `limits`: Memory and bucket limits for the aggregation
/// - `tokenizers`: TokenizerManager for parsing query strings in filter aggregations
#[derive(Clone, Default)]
pub struct AggContextParams {
/// Aggregation limits (memory and bucket count)
pub limits: AggregationLimitsGuard,
/// Tokenizer manager for query string parsing
pub tokenizers: TokenizerManager,
}
impl AggContextParams {
/// Create new aggregation context parameters
pub fn new(limits: AggregationLimitsGuard, tokenizers: TokenizerManager) -> Self {
Self { limits, tokenizers }
}
}
fn parse_str_into_f64<E: de::Error>(value: &str) -> Result<f64, E> {
let parsed = value
.parse::<f64>()
@@ -279,6 +257,80 @@ where D: Deserializer<'de> {
deserializer.deserialize_any(StringOrFloatVisitor)
}
/// Represents an associative array `(key => values)` in a very efficient manner.
#[derive(PartialEq, Serialize, Deserialize)]
pub(crate) struct VecWithNames<T> {
pub(crate) values: Vec<T>,
keys: Vec<String>,
}
impl<T: Clone> Clone for VecWithNames<T> {
fn clone(&self) -> Self {
Self {
values: self.values.clone(),
keys: self.keys.clone(),
}
}
}
impl<T> Default for VecWithNames<T> {
fn default() -> Self {
Self {
values: Default::default(),
keys: Default::default(),
}
}
}
impl<T: std::fmt::Debug> std::fmt::Debug for VecWithNames<T> {
fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
f.debug_map().entries(self.iter()).finish()
}
}
impl<T> From<HashMap<String, T>> for VecWithNames<T> {
fn from(map: HashMap<String, T>) -> Self {
VecWithNames::from_entries(map.into_iter().collect_vec())
}
}
impl<T> VecWithNames<T> {
fn from_entries(mut entries: Vec<(String, T)>) -> Self {
// Sort to ensure order of elements match across multiple instances
entries.sort_by(|left, right| left.0.cmp(&right.0));
let mut data = Vec::with_capacity(entries.len());
let mut data_names = Vec::with_capacity(entries.len());
for entry in entries {
data_names.push(entry.0);
data.push(entry.1);
}
VecWithNames {
values: data,
keys: data_names,
}
}
fn iter(&self) -> impl Iterator<Item = (&str, &T)> + '_ {
self.keys().zip(self.values.iter())
}
fn keys(&self) -> impl Iterator<Item = &str> + '_ {
self.keys.iter().map(|key| key.as_str())
}
fn values_mut(&mut self) -> impl Iterator<Item = &mut T> + '_ {
self.values.iter_mut()
}
fn is_empty(&self) -> bool {
self.keys.is_empty()
}
fn len(&self) -> usize {
self.keys.len()
}
fn get(&self, name: &str) -> Option<&T> {
self.keys()
.position(|key| key == name)
.map(|pos| &self.values[pos])
}
}
/// The serialized key is used in a `HashMap`.
pub type SerializedKey = String;
@@ -412,10 +464,7 @@ mod tests {
query: Option<(&str, &str)>,
limits: AggregationLimitsGuard,
) -> crate::Result<Value> {
let collector = AggregationCollector::from_aggs(
agg_req,
AggContextParams::new(limits, index.tokenizers().clone()),
);
let collector = AggregationCollector::from_aggs(agg_req, limits);
let reader = index.reader()?;
let searcher = reader.searcher();

View File

@@ -6,41 +6,48 @@
use std::fmt::Debug;
pub(crate) use super::agg_limits::AggregationLimitsGuard;
use super::agg_req::AggregationVariants;
use super::agg_req_with_accessor::{AggregationWithAccessor, AggregationsWithAccessor};
use super::bucket::{SegmentHistogramCollector, SegmentRangeCollector, SegmentTermCollector};
use super::intermediate_agg_result::IntermediateAggregationResults;
use crate::aggregation::agg_data::AggregationsSegmentCtx;
use super::metric::{
AverageAggregation, CountAggregation, ExtendedStatsAggregation, MaxAggregation, MinAggregation,
SegmentPercentilesCollector, SegmentStatsCollector, SegmentStatsType, StatsAggregation,
SumAggregation,
};
use crate::aggregation::bucket::TermMissingAgg;
use crate::aggregation::metric::{
CardinalityAggregationReq, SegmentCardinalityCollector, SegmentExtendedStatsCollector,
TopHitsSegmentCollector,
};
/// A SegmentAggregationCollector is used to collect aggregation results.
pub trait SegmentAggregationCollector: CollectorClone + Debug {
pub(crate) trait SegmentAggregationCollector: CollectorClone + Debug {
fn add_intermediate_aggregation_result(
self: Box<Self>,
agg_data: &AggregationsSegmentCtx,
agg_with_accessor: &AggregationsWithAccessor,
results: &mut IntermediateAggregationResults,
) -> crate::Result<()>;
#[inline]
fn collect(
&mut self,
doc: crate::DocId,
agg_data: &mut AggregationsSegmentCtx,
) -> crate::Result<()> {
self.collect_block(&[doc], agg_data)
}
agg_with_accessor: &mut AggregationsWithAccessor,
) -> crate::Result<()>;
fn collect_block(
&mut self,
docs: &[crate::DocId],
agg_data: &mut AggregationsSegmentCtx,
agg_with_accessor: &mut AggregationsWithAccessor,
) -> crate::Result<()>;
/// Finalize method. Some Aggregator collect blocks of docs before calling `collect_block`.
/// This method ensures those staged docs will be collected.
fn flush(&mut self, _agg_data: &mut AggregationsSegmentCtx) -> crate::Result<()> {
fn flush(&mut self, _agg_with_accessor: &mut AggregationsWithAccessor) -> crate::Result<()> {
Ok(())
}
}
/// A helper trait to enable cloning of Box<dyn SegmentAggregationCollector>
pub trait CollectorClone {
pub(crate) trait CollectorClone {
fn clone_box(&self) -> Box<dyn SegmentAggregationCollector>;
}
@@ -58,6 +65,119 @@ impl Clone for Box<dyn SegmentAggregationCollector> {
}
}
pub(crate) fn build_segment_agg_collector(
req: &mut AggregationsWithAccessor,
) -> crate::Result<Box<dyn SegmentAggregationCollector>> {
// Single collector special case
if req.aggs.len() == 1 {
let req = &mut req.aggs.values[0];
let accessor_idx = 0;
return build_single_agg_segment_collector(req, accessor_idx);
}
let agg = GenericSegmentAggregationResultsCollector::from_req_and_validate(req)?;
Ok(Box::new(agg))
}
pub(crate) fn build_single_agg_segment_collector(
req: &mut AggregationWithAccessor,
accessor_idx: usize,
) -> crate::Result<Box<dyn SegmentAggregationCollector>> {
use AggregationVariants::*;
match &req.agg.agg {
Terms(terms_req) => {
if req.accessors.is_empty() {
Ok(Box::new(SegmentTermCollector::from_req_and_validate(
terms_req,
&mut req.sub_aggregation,
req.field_type,
accessor_idx,
)?))
} else {
Ok(Box::new(TermMissingAgg::new(
accessor_idx,
&mut req.sub_aggregation,
)?))
}
}
Range(range_req) => Ok(Box::new(SegmentRangeCollector::from_req_and_validate(
range_req,
&mut req.sub_aggregation,
&mut req.limits,
req.field_type,
accessor_idx,
)?)),
Histogram(histogram) => Ok(Box::new(SegmentHistogramCollector::from_req_and_validate(
histogram.clone(),
&mut req.sub_aggregation,
req.field_type,
accessor_idx,
)?)),
DateHistogram(histogram) => Ok(Box::new(SegmentHistogramCollector::from_req_and_validate(
histogram.to_histogram_req()?,
&mut req.sub_aggregation,
req.field_type,
accessor_idx,
)?)),
Average(AverageAggregation { missing, .. }) => {
Ok(Box::new(SegmentStatsCollector::from_req(
req.field_type,
SegmentStatsType::Average,
accessor_idx,
*missing,
)))
}
Count(CountAggregation { missing, .. }) => Ok(Box::new(SegmentStatsCollector::from_req(
req.field_type,
SegmentStatsType::Count,
accessor_idx,
*missing,
))),
Max(MaxAggregation { missing, .. }) => Ok(Box::new(SegmentStatsCollector::from_req(
req.field_type,
SegmentStatsType::Max,
accessor_idx,
*missing,
))),
Min(MinAggregation { missing, .. }) => Ok(Box::new(SegmentStatsCollector::from_req(
req.field_type,
SegmentStatsType::Min,
accessor_idx,
*missing,
))),
Stats(StatsAggregation { missing, .. }) => Ok(Box::new(SegmentStatsCollector::from_req(
req.field_type,
SegmentStatsType::Stats,
accessor_idx,
*missing,
))),
ExtendedStats(ExtendedStatsAggregation { missing, sigma, .. }) => Ok(Box::new(
SegmentExtendedStatsCollector::from_req(req.field_type, *sigma, accessor_idx, *missing),
)),
Sum(SumAggregation { missing, .. }) => Ok(Box::new(SegmentStatsCollector::from_req(
req.field_type,
SegmentStatsType::Sum,
accessor_idx,
*missing,
))),
Percentiles(percentiles_req) => Ok(Box::new(
SegmentPercentilesCollector::from_req_and_validate(
percentiles_req,
req.field_type,
accessor_idx,
)?,
)),
TopHits(top_hits_req) => Ok(Box::new(TopHitsSegmentCollector::from_req(
top_hits_req,
accessor_idx,
req.segment_ordinal,
))),
Cardinality(CardinalityAggregationReq { missing, .. }) => Ok(Box::new(
SegmentCardinalityCollector::from_req(req.field_type, accessor_idx, missing),
)),
}
}
#[derive(Clone, Default)]
/// The GenericSegmentAggregationResultsCollector is the generic version of the collector, which
/// can handle arbitrary complexity of sub-aggregations. Ideally we never have to pick this one
@@ -77,11 +197,11 @@ impl Debug for GenericSegmentAggregationResultsCollector {
impl SegmentAggregationCollector for GenericSegmentAggregationResultsCollector {
fn add_intermediate_aggregation_result(
self: Box<Self>,
agg_data: &AggregationsSegmentCtx,
agg_with_accessor: &AggregationsWithAccessor,
results: &mut IntermediateAggregationResults,
) -> crate::Result<()> {
for agg in self.aggs {
agg.add_intermediate_aggregation_result(agg_data, results)?;
agg.add_intermediate_aggregation_result(agg_with_accessor, results)?;
}
Ok(())
@@ -90,9 +210,9 @@ impl SegmentAggregationCollector for GenericSegmentAggregationResultsCollector {
fn collect(
&mut self,
doc: crate::DocId,
agg_data: &mut AggregationsSegmentCtx,
agg_with_accessor: &mut AggregationsWithAccessor,
) -> crate::Result<()> {
self.collect_block(&[doc], agg_data)?;
self.collect_block(&[doc], agg_with_accessor)?;
Ok(())
}
@@ -100,19 +220,32 @@ impl SegmentAggregationCollector for GenericSegmentAggregationResultsCollector {
fn collect_block(
&mut self,
docs: &[crate::DocId],
agg_data: &mut AggregationsSegmentCtx,
agg_with_accessor: &mut AggregationsWithAccessor,
) -> crate::Result<()> {
for collector in &mut self.aggs {
collector.collect_block(docs, agg_data)?;
collector.collect_block(docs, agg_with_accessor)?;
}
Ok(())
}
fn flush(&mut self, agg_data: &mut AggregationsSegmentCtx) -> crate::Result<()> {
fn flush(&mut self, agg_with_accessor: &mut AggregationsWithAccessor) -> crate::Result<()> {
for collector in &mut self.aggs {
collector.flush(agg_data)?;
collector.flush(agg_with_accessor)?;
}
Ok(())
}
}
impl GenericSegmentAggregationResultsCollector {
pub(crate) fn from_req_and_validate(req: &mut AggregationsWithAccessor) -> crate::Result<Self> {
let aggs = req
.aggs
.values_mut()
.enumerate()
.map(|(accessor_idx, req)| build_single_agg_segment_collector(req, accessor_idx))
.collect::<crate::Result<Vec<Box<dyn SegmentAggregationCollector>>>>()?;
Ok(GenericSegmentAggregationResultsCollector { aggs })
}
}

View File

@@ -87,17 +87,6 @@ pub trait DocSet: Send {
/// length of the docset.
fn size_hint(&self) -> u32;
/// Returns a best-effort hint of the cost to consume the entire docset.
///
/// Consuming means calling advance until [`TERMINATED`] is returned.
/// The cost should be relative to the cost of driving a Term query,
/// which would be the number of documents in the DocSet.
///
/// By default this returns `size_hint()`.
fn cost(&self) -> u64 {
self.size_hint() as u64
}
/// Returns the number documents matching.
/// Calling this method consumes the `DocSet`.
fn count(&mut self, alive_bitset: &AliveBitSet) -> u32 {
@@ -145,10 +134,6 @@ impl DocSet for &mut dyn DocSet {
(**self).size_hint()
}
fn cost(&self) -> u64 {
(**self).cost()
}
fn count(&mut self, alive_bitset: &AliveBitSet) -> u32 {
(**self).count(alive_bitset)
}
@@ -184,11 +169,6 @@ impl<TDocSet: DocSet + ?Sized> DocSet for Box<TDocSet> {
unboxed.size_hint()
}
fn cost(&self) -> u64 {
let unboxed: &TDocSet = self.borrow();
unboxed.cost()
}
fn count(&mut self, alive_bitset: &AliveBitSet) -> u32 {
let unboxed: &mut TDocSet = self.borrow_mut();
unboxed.count(alive_bitset)

View File

@@ -41,6 +41,8 @@ const COMPRESSION_BLOCK_SIZE: usize = BitPacker4x::BLOCK_LEN;
#[cfg(test)]
pub(crate) mod tests {
use std::iter;
use proptest::prelude::*;
use proptest::sample::select;

View File

@@ -667,15 +667,12 @@ mod bench {
.read_postings(&TERM_D, IndexRecordOption::Basic)
.unwrap()
.unwrap();
let mut intersection = Intersection::new(
vec![
segment_postings_a,
segment_postings_b,
segment_postings_c,
segment_postings_d,
],
reader.searcher().num_docs() as u32,
);
let mut intersection = Intersection::new(vec![
segment_postings_a,
segment_postings_b,
segment_postings_c,
segment_postings_d,
]);
while intersection.advance() != TERMINATED {}
});
}

View File

@@ -367,14 +367,10 @@ mod tests {
checkpoints
}
fn compute_checkpoints_manual(
term_scorers: Vec<TermScorer>,
n: usize,
max_doc: u32,
) -> Vec<(DocId, Score)> {
fn compute_checkpoints_manual(term_scorers: Vec<TermScorer>, n: usize) -> Vec<(DocId, Score)> {
let mut heap: BinaryHeap<Float> = BinaryHeap::with_capacity(n);
let mut checkpoints: Vec<(DocId, Score)> = Vec::new();
let mut scorer = BufferedUnionScorer::build(term_scorers, SumCombiner::default, max_doc);
let mut scorer = BufferedUnionScorer::build(term_scorers, SumCombiner::default);
let mut limit = Score::MIN;
loop {
@@ -482,8 +478,7 @@ mod tests {
for top_k in 1..4 {
let checkpoints_for_each_pruning =
compute_checkpoints_for_each_pruning(term_scorers.clone(), top_k);
let checkpoints_manual =
compute_checkpoints_manual(term_scorers.clone(), top_k, 100_000);
let checkpoints_manual = compute_checkpoints_manual(term_scorers.clone(), top_k);
assert_eq!(checkpoints_for_each_pruning.len(), checkpoints_manual.len());
for (&(left_doc, left_score), &(right_doc, right_score)) in checkpoints_for_each_pruning
.iter()

View File

@@ -39,11 +39,9 @@ where
))
}
/// num_docs is the number of documents in the segment.
fn scorer_union<TScoreCombiner>(
scorers: Vec<Box<dyn Scorer>>,
score_combiner_fn: impl Fn() -> TScoreCombiner,
num_docs: u32,
) -> SpecializedScorer
where
TScoreCombiner: ScoreCombiner,
@@ -70,7 +68,6 @@ where
return SpecializedScorer::Other(Box::new(BufferedUnionScorer::build(
scorers,
score_combiner_fn,
num_docs,
)));
}
}
@@ -78,19 +75,16 @@ where
SpecializedScorer::Other(Box::new(BufferedUnionScorer::build(
scorers,
score_combiner_fn,
num_docs,
)))
}
fn into_box_scorer<TScoreCombiner: ScoreCombiner>(
scorer: SpecializedScorer,
score_combiner_fn: impl Fn() -> TScoreCombiner,
num_docs: u32,
) -> Box<dyn Scorer> {
match scorer {
SpecializedScorer::TermUnion(term_scorers) => {
let union_scorer =
BufferedUnionScorer::build(term_scorers, score_combiner_fn, num_docs);
let union_scorer = BufferedUnionScorer::build(term_scorers, score_combiner_fn);
Box::new(union_scorer)
}
SpecializedScorer::Other(scorer) => scorer,
@@ -157,7 +151,6 @@ impl<TScoreCombiner: ScoreCombiner> BooleanWeight<TScoreCombiner> {
boost: Score,
score_combiner_fn: impl Fn() -> TComplexScoreCombiner,
) -> crate::Result<SpecializedScorer> {
let num_docs = reader.num_docs();
let mut per_occur_scorers = self.per_occur_scorers(reader, boost)?;
// Indicate how should clauses are combined with other clauses.
enum CombinationMethod {
@@ -174,16 +167,11 @@ impl<TScoreCombiner: ScoreCombiner> BooleanWeight<TScoreCombiner> {
return Ok(SpecializedScorer::Other(Box::new(EmptyScorer)));
}
match self.minimum_number_should_match {
0 => CombinationMethod::Optional(scorer_union(
should_scorers,
&score_combiner_fn,
num_docs,
)),
1 => CombinationMethod::Required(scorer_union(
should_scorers,
&score_combiner_fn,
num_docs,
)),
0 => CombinationMethod::Optional(scorer_union(should_scorers, &score_combiner_fn)),
1 => {
let scorer_union = scorer_union(should_scorers, &score_combiner_fn);
CombinationMethod::Required(scorer_union)
}
n if num_of_should_scorers == n => {
// When num_of_should_scorers equals the number of should clauses,
// they are no different from must clauses.
@@ -212,21 +200,21 @@ impl<TScoreCombiner: ScoreCombiner> BooleanWeight<TScoreCombiner> {
};
let exclude_scorer_opt: Option<Box<dyn Scorer>> = per_occur_scorers
.remove(&Occur::MustNot)
.map(|scorers| scorer_union(scorers, DoNothingCombiner::default, num_docs))
.map(|scorers| scorer_union(scorers, DoNothingCombiner::default))
.map(|specialized_scorer: SpecializedScorer| {
into_box_scorer(specialized_scorer, DoNothingCombiner::default, num_docs)
into_box_scorer(specialized_scorer, DoNothingCombiner::default)
});
let positive_scorer = match (should_opt, must_scorers) {
(CombinationMethod::Ignored, Some(must_scorers)) => {
SpecializedScorer::Other(intersect_scorers(must_scorers, num_docs))
SpecializedScorer::Other(intersect_scorers(must_scorers))
}
(CombinationMethod::Optional(should_scorer), Some(must_scorers)) => {
let must_scorer = intersect_scorers(must_scorers, num_docs);
let must_scorer = intersect_scorers(must_scorers);
if self.scoring_enabled {
SpecializedScorer::Other(Box::new(
RequiredOptionalScorer::<_, _, TScoreCombiner>::new(
must_scorer,
into_box_scorer(should_scorer, &score_combiner_fn, num_docs),
into_box_scorer(should_scorer, &score_combiner_fn),
),
))
} else {
@@ -234,8 +222,8 @@ impl<TScoreCombiner: ScoreCombiner> BooleanWeight<TScoreCombiner> {
}
}
(CombinationMethod::Required(should_scorer), Some(mut must_scorers)) => {
must_scorers.push(into_box_scorer(should_scorer, &score_combiner_fn, num_docs));
SpecializedScorer::Other(intersect_scorers(must_scorers, num_docs))
must_scorers.push(into_box_scorer(should_scorer, &score_combiner_fn));
SpecializedScorer::Other(intersect_scorers(must_scorers))
}
(CombinationMethod::Ignored, None) => {
return Ok(SpecializedScorer::Other(Box::new(EmptyScorer)))
@@ -245,8 +233,7 @@ impl<TScoreCombiner: ScoreCombiner> BooleanWeight<TScoreCombiner> {
(CombinationMethod::Optional(should_scorer), None) => should_scorer,
};
if let Some(exclude_scorer) = exclude_scorer_opt {
let positive_scorer_boxed =
into_box_scorer(positive_scorer, &score_combiner_fn, num_docs);
let positive_scorer_boxed = into_box_scorer(positive_scorer, &score_combiner_fn);
Ok(SpecializedScorer::Other(Box::new(Exclude::new(
positive_scorer_boxed,
exclude_scorer,
@@ -259,7 +246,6 @@ impl<TScoreCombiner: ScoreCombiner> BooleanWeight<TScoreCombiner> {
impl<TScoreCombiner: ScoreCombiner + Sync> Weight for BooleanWeight<TScoreCombiner> {
fn scorer(&self, reader: &SegmentReader, boost: Score) -> crate::Result<Box<dyn Scorer>> {
let num_docs = reader.num_docs();
if self.weights.is_empty() {
Ok(Box::new(EmptyScorer))
} else if self.weights.len() == 1 {
@@ -272,12 +258,12 @@ impl<TScoreCombiner: ScoreCombiner + Sync> Weight for BooleanWeight<TScoreCombin
} else if self.scoring_enabled {
self.complex_scorer(reader, boost, &self.score_combiner_fn)
.map(|specialized_scorer| {
into_box_scorer(specialized_scorer, &self.score_combiner_fn, num_docs)
into_box_scorer(specialized_scorer, &self.score_combiner_fn)
})
} else {
self.complex_scorer(reader, boost, DoNothingCombiner::default)
.map(|specialized_scorer| {
into_box_scorer(specialized_scorer, DoNothingCombiner::default, num_docs)
into_box_scorer(specialized_scorer, DoNothingCombiner::default)
})
}
}
@@ -310,11 +296,8 @@ impl<TScoreCombiner: ScoreCombiner + Sync> Weight for BooleanWeight<TScoreCombin
let scorer = self.complex_scorer(reader, 1.0, &self.score_combiner_fn)?;
match scorer {
SpecializedScorer::TermUnion(term_scorers) => {
let mut union_scorer = BufferedUnionScorer::build(
term_scorers,
&self.score_combiner_fn,
reader.num_docs(),
);
let mut union_scorer =
BufferedUnionScorer::build(term_scorers, &self.score_combiner_fn);
for_each_scorer(&mut union_scorer, callback);
}
SpecializedScorer::Other(mut scorer) => {
@@ -334,11 +317,8 @@ impl<TScoreCombiner: ScoreCombiner + Sync> Weight for BooleanWeight<TScoreCombin
match scorer {
SpecializedScorer::TermUnion(term_scorers) => {
let mut union_scorer = BufferedUnionScorer::build(
term_scorers,
&self.score_combiner_fn,
reader.num_docs(),
);
let mut union_scorer =
BufferedUnionScorer::build(term_scorers, &self.score_combiner_fn);
for_each_docset_buffered(&mut union_scorer, &mut buffer, callback);
}
SpecializedScorer::Other(mut scorer) => {

View File

@@ -117,10 +117,6 @@ impl<S: Scorer> DocSet for BoostScorer<S> {
self.underlying.size_hint()
}
fn cost(&self) -> u64 {
self.underlying.cost()
}
fn count(&mut self, alive_bitset: &AliveBitSet) -> u32 {
self.underlying.count(alive_bitset)
}

View File

@@ -130,10 +130,6 @@ impl<TDocSet: DocSet> DocSet for ConstScorer<TDocSet> {
fn size_hint(&self) -> u32 {
self.docset.size_hint()
}
fn cost(&self) -> u64 {
self.docset.cost()
}
}
impl<TDocSet: DocSet + 'static> Scorer for ConstScorer<TDocSet> {

View File

@@ -70,10 +70,6 @@ impl<T: Scorer> DocSet for ScorerWrapper<T> {
fn size_hint(&self) -> u32 {
self.scorer.size_hint()
}
fn cost(&self) -> u64 {
self.scorer.cost()
}
}
impl<TScorer: Scorer, TScoreCombiner: ScoreCombiner> Disjunction<TScorer, TScoreCombiner> {
@@ -150,14 +146,6 @@ impl<TScorer: Scorer, TScoreCombiner: ScoreCombiner> DocSet
.max()
.unwrap_or(0u32)
}
fn cost(&self) -> u64 {
self.chains
.iter()
.map(|docset| docset.cost())
.max()
.unwrap_or(0u64)
}
}
impl<TScorer: Scorer, TScoreCombiner: ScoreCombiner> Scorer

View File

@@ -1,5 +1,4 @@
use crate::docset::{DocSet, TERMINATED};
use crate::query::size_hint::estimate_intersection;
use crate::query::term_query::TermScorer;
use crate::query::{EmptyScorer, Scorer};
use crate::{DocId, Score};
@@ -12,18 +11,14 @@ use crate::{DocId, Score};
/// For better performance, the function uses a
/// specialized implementation if the two
/// shortest scorers are `TermScorer`s.
pub fn intersect_scorers(
mut scorers: Vec<Box<dyn Scorer>>,
num_docs_segment: u32,
) -> Box<dyn Scorer> {
pub fn intersect_scorers(mut scorers: Vec<Box<dyn Scorer>>) -> Box<dyn Scorer> {
if scorers.is_empty() {
return Box::new(EmptyScorer);
}
if scorers.len() == 1 {
return scorers.pop().unwrap();
}
// Order by estimated cost to drive each scorer.
scorers.sort_by_key(|scorer| scorer.cost());
scorers.sort_by_key(|scorer| scorer.size_hint());
let doc = go_to_first_doc(&mut scorers[..]);
if doc == TERMINATED {
return Box::new(EmptyScorer);
@@ -39,14 +34,12 @@ pub fn intersect_scorers(
left: *(left.downcast::<TermScorer>().map_err(|_| ()).unwrap()),
right: *(right.downcast::<TermScorer>().map_err(|_| ()).unwrap()),
others: scorers,
num_docs: num_docs_segment,
});
}
Box::new(Intersection {
left,
right,
others: scorers,
num_docs: num_docs_segment,
})
}
@@ -55,7 +48,6 @@ pub struct Intersection<TDocSet: DocSet, TOtherDocSet: DocSet = Box<dyn Scorer>>
left: TDocSet,
right: TDocSet,
others: Vec<TOtherDocSet>,
num_docs: u32,
}
fn go_to_first_doc<TDocSet: DocSet>(docsets: &mut [TDocSet]) -> DocId {
@@ -74,11 +66,10 @@ fn go_to_first_doc<TDocSet: DocSet>(docsets: &mut [TDocSet]) -> DocId {
}
impl<TDocSet: DocSet> Intersection<TDocSet, TDocSet> {
/// num_docs is the number of documents in the segment.
pub(crate) fn new(mut docsets: Vec<TDocSet>, num_docs: u32) -> Intersection<TDocSet, TDocSet> {
pub(crate) fn new(mut docsets: Vec<TDocSet>) -> Intersection<TDocSet, TDocSet> {
let num_docsets = docsets.len();
assert!(num_docsets >= 2);
docsets.sort_by_key(|docset| docset.cost());
docsets.sort_by_key(|docset| docset.size_hint());
go_to_first_doc(&mut docsets);
let left = docsets.remove(0);
let right = docsets.remove(0);
@@ -86,7 +77,6 @@ impl<TDocSet: DocSet> Intersection<TDocSet, TDocSet> {
left,
right,
others: docsets,
num_docs,
}
}
}
@@ -151,19 +141,7 @@ impl<TDocSet: DocSet, TOtherDocSet: DocSet> DocSet for Intersection<TDocSet, TOt
}
fn size_hint(&self) -> u32 {
estimate_intersection(
[self.left.size_hint(), self.right.size_hint()]
.into_iter()
.chain(self.others.iter().map(DocSet::size_hint)),
self.num_docs,
)
}
fn cost(&self) -> u64 {
// What's the best way to compute the cost of an intersection?
// For now we take the cost of the docset driver, which is the first docset.
// If there are docsets that are bad at skipping, they should also influence the cost.
self.left.cost()
self.left.size_hint()
}
}
@@ -191,7 +169,7 @@ mod tests {
{
let left = VecDocSet::from(vec![1, 3, 9]);
let right = VecDocSet::from(vec![3, 4, 9, 18]);
let mut intersection = Intersection::new(vec![left, right], 10);
let mut intersection = Intersection::new(vec![left, right]);
assert_eq!(intersection.doc(), 3);
assert_eq!(intersection.advance(), 9);
assert_eq!(intersection.doc(), 9);
@@ -201,7 +179,7 @@ mod tests {
let a = VecDocSet::from(vec![1, 3, 9]);
let b = VecDocSet::from(vec![3, 4, 9, 18]);
let c = VecDocSet::from(vec![1, 5, 9, 111]);
let mut intersection = Intersection::new(vec![a, b, c], 10);
let mut intersection = Intersection::new(vec![a, b, c]);
assert_eq!(intersection.doc(), 9);
assert_eq!(intersection.advance(), TERMINATED);
}
@@ -211,7 +189,7 @@ mod tests {
fn test_intersection_zero() {
let left = VecDocSet::from(vec![0]);
let right = VecDocSet::from(vec![0]);
let mut intersection = Intersection::new(vec![left, right], 10);
let mut intersection = Intersection::new(vec![left, right]);
assert_eq!(intersection.doc(), 0);
assert_eq!(intersection.advance(), TERMINATED);
}
@@ -220,7 +198,7 @@ mod tests {
fn test_intersection_skip() {
let left = VecDocSet::from(vec![0, 1, 2, 4]);
let right = VecDocSet::from(vec![2, 5]);
let mut intersection = Intersection::new(vec![left, right], 10);
let mut intersection = Intersection::new(vec![left, right]);
assert_eq!(intersection.seek(2), 2);
assert_eq!(intersection.doc(), 2);
}
@@ -231,7 +209,7 @@ mod tests {
|| {
let left = VecDocSet::from(vec![4]);
let right = VecDocSet::from(vec![2, 5]);
Box::new(Intersection::new(vec![left, right], 10))
Box::new(Intersection::new(vec![left, right]))
},
vec![0, 2, 4, 5, 6],
);
@@ -241,22 +219,19 @@ mod tests {
let mut right = VecDocSet::from(vec![2, 5, 10]);
left.advance();
right.advance();
Box::new(Intersection::new(vec![left, right], 10))
Box::new(Intersection::new(vec![left, right]))
},
vec![0, 1, 2, 3, 4, 5, 6, 7, 10, 11],
);
test_skip_against_unoptimized(
|| {
Box::new(Intersection::new(
vec![
VecDocSet::from(vec![1, 4, 5, 6]),
VecDocSet::from(vec![1, 2, 5, 6]),
VecDocSet::from(vec![1, 4, 5, 6]),
VecDocSet::from(vec![1, 5, 6]),
VecDocSet::from(vec![2, 4, 5, 7, 8]),
],
10,
))
Box::new(Intersection::new(vec![
VecDocSet::from(vec![1, 4, 5, 6]),
VecDocSet::from(vec![1, 2, 5, 6]),
VecDocSet::from(vec![1, 4, 5, 6]),
VecDocSet::from(vec![1, 5, 6]),
VecDocSet::from(vec![2, 4, 5, 7, 8]),
]))
},
vec![0, 1, 2, 3, 4, 5, 6, 7, 10, 11],
);
@@ -267,7 +242,7 @@ mod tests {
let a = VecDocSet::from(vec![1, 3]);
let b = VecDocSet::from(vec![1, 4]);
let c = VecDocSet::from(vec![3, 9]);
let intersection = Intersection::new(vec![a, b, c], 10);
let intersection = Intersection::new(vec![a, b, c]);
assert_eq!(intersection.doc(), TERMINATED);
}
}

View File

@@ -23,7 +23,6 @@ mod regex_query;
mod reqopt_scorer;
mod scorer;
mod set_query;
mod size_hint;
mod term_query;
mod union;
mod weight;

View File

@@ -200,10 +200,6 @@ impl<TPostings: Postings> DocSet for PhrasePrefixScorer<TPostings> {
fn size_hint(&self) -> u32 {
self.phrase_scorer.size_hint()
}
fn cost(&self) -> u64 {
self.phrase_scorer.cost()
}
}
impl<TPostings: Postings> Scorer for PhrasePrefixScorer<TPostings> {

View File

@@ -368,7 +368,6 @@ impl<TPostings: Postings> PhraseScorer<TPostings> {
slop: u32,
offset: usize,
) -> PhraseScorer<TPostings> {
let num_docs = fieldnorm_reader.num_docs();
let max_offset = term_postings_with_offset
.iter()
.map(|&(offset, _)| offset)
@@ -383,7 +382,7 @@ impl<TPostings: Postings> PhraseScorer<TPostings> {
})
.collect::<Vec<_>>();
let mut scorer = PhraseScorer {
intersection_docset: Intersection::new(postings_with_offsets, num_docs),
intersection_docset: Intersection::new(postings_with_offsets),
num_terms: num_docsets,
left_positions: Vec::with_capacity(100),
right_positions: Vec::with_capacity(100),
@@ -536,15 +535,6 @@ impl<TPostings: Postings> DocSet for PhraseScorer<TPostings> {
fn size_hint(&self) -> u32 {
self.intersection_docset.size_hint()
}
/// Returns a best-effort hint of the
/// cost to drive the docset.
fn cost(&self) -> u64 {
// Evaluating phrase matches is generally more expensive than simple term matches,
// as it requires loading and comparing positions. Use a conservative multiplier
// based on the number of terms.
self.intersection_docset.size_hint() as u64 * 10 * self.num_terms as u64
}
}
impl<TPostings: Postings> Scorer for PhraseScorer<TPostings> {

View File

@@ -176,14 +176,6 @@ impl<T: Send + Sync + PartialOrd + Copy + Debug + 'static> DocSet for RangeDocSe
fn size_hint(&self) -> u32 {
self.column.num_docs()
}
/// Returns a best-effort hint of the
/// cost to drive the docset.
fn cost(&self) -> u64 {
// Advancing the docset is relatively expensive since it scans the column.
// Keep cost relative to a term query driver; use num_docs as baseline.
self.column.num_docs() as u64
}
}
#[cfg(test)]

View File

@@ -63,10 +63,6 @@ where
fn size_hint(&self) -> u32 {
self.req_scorer.size_hint()
}
fn cost(&self) -> u64 {
self.req_scorer.cost()
}
}
impl<TReqScorer, TOptScorer, TScoreCombiner> Scorer

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@@ -1,141 +0,0 @@
/// Computes the estimated number of documents in the intersection of multiple docsets
/// given their sizes.
///
/// # Arguments
/// * `docset_sizes` - An iterator over the sizes of the docsets (number of documents in each set).
/// * `max_docs` - The maximum number of docs that can hit, usually number of documents in the
/// segment.
///
/// # Returns
/// The estimated number of documents in the intersection.
pub fn estimate_intersection<I>(mut docset_sizes: I, max_docs: u32) -> u32
where I: Iterator<Item = u32> {
if max_docs == 0u32 {
return 0u32;
}
// Terms tend to be not really randomly distributed.
// This factor is used to adjust the estimate.
let mut co_loc_factor: f64 = 1.3;
let mut intersection_estimate = match docset_sizes.next() {
Some(first_size) => first_size as f64,
None => return 0, // No docsets provided, so return 0.
};
let mut smallest_docset_size = intersection_estimate;
// Assuming random distribution of terms, the probability of a document being in the
// intersection
for size in docset_sizes {
// Diminish the co-location factor for each additional set, or we will overestimate.
co_loc_factor = (co_loc_factor - 0.1).max(1.0);
intersection_estimate *= (size as f64 / max_docs as f64) * co_loc_factor;
smallest_docset_size = smallest_docset_size.min(size as f64);
}
intersection_estimate.round().min(smallest_docset_size) as u32
}
/// Computes the estimated number of documents in the union of multiple docsets
/// given their sizes.
///
/// # Arguments
/// * `docset_sizes` - An iterator over the sizes of the docsets (number of documents in each set).
/// * `max_docs` - The maximum number of docs that can hit, usually number of documents in the
/// segment.
///
/// # Returns
/// The estimated number of documents in the union.
pub fn estimate_union<I>(docset_sizes: I, max_docs: u32) -> u32
where I: Iterator<Item = u32> {
// Terms tend to be not really randomly distributed.
// This factor is used to adjust the estimate.
// Unlike intersection, the co-location reduces the estimate.
let co_loc_factor = 0.8;
// The approach for union is to compute the probability of a document not being in any of the
// sets
let mut not_in_any_set_prob = 1.0;
// Assuming random distribution of terms, the probability of a document being in the
// union is the complement of the probability of it not being in any of the sets.
for size in docset_sizes {
let prob_in_set = (size as f64 / max_docs as f64) * co_loc_factor;
not_in_any_set_prob *= 1.0 - prob_in_set;
}
let union_estimate = (max_docs as f64 * (1.0 - not_in_any_set_prob)).round();
union_estimate.min(max_docs as f64) as u32
}
#[cfg(test)]
mod tests {
use super::*;
#[test]
fn test_estimate_intersection_small1() {
let docset_sizes = &[500, 1000];
let n = 10_000;
let result = estimate_intersection(docset_sizes.iter().copied(), n);
assert_eq!(result, 60);
}
#[test]
fn test_estimate_intersection_small2() {
let docset_sizes = &[500, 1000, 1500];
let n = 10_000;
let result = estimate_intersection(docset_sizes.iter().copied(), n);
assert_eq!(result, 10);
}
#[test]
fn test_estimate_intersection_large_values() {
let docset_sizes = &[100_000, 50_000, 30_000];
let n = 1_000_000;
let result = estimate_intersection(docset_sizes.iter().copied(), n);
assert_eq!(result, 198);
}
#[test]
fn test_estimate_union_small() {
let docset_sizes = &[500, 1000, 1500];
let n = 10000;
let result = estimate_union(docset_sizes.iter().copied(), n);
assert_eq!(result, 2228);
}
#[test]
fn test_estimate_union_large_values() {
let docset_sizes = &[100000, 50000, 30000];
let n = 1000000;
let result = estimate_union(docset_sizes.iter().copied(), n);
assert_eq!(result, 137997);
}
#[test]
fn test_estimate_intersection_large() {
let docset_sizes: Vec<_> = (0..10).map(|_| 4_000_000).collect();
let n = 5_000_000;
let result = estimate_intersection(docset_sizes.iter().copied(), n);
// Check that it doesn't overflow and returns a reasonable result
assert_eq!(result, 708_670);
}
#[test]
fn test_estimate_intersection_overflow_safety() {
let docset_sizes: Vec<_> = (0..100).map(|_| 4_000_000).collect();
let n = 5_000_000;
let result = estimate_intersection(docset_sizes.iter().copied(), n);
// Check that it doesn't overflow and returns a reasonable result
assert_eq!(result, 0);
}
#[test]
fn test_estimate_union_overflow_safety() {
let docset_sizes: Vec<_> = (0..100).map(|_| 1_000_000).collect();
let n = 20_000_000;
let result = estimate_union(docset_sizes.iter().copied(), n);
// Check that it doesn't overflow and returns a reasonable result
assert_eq!(result, 19_662_594);
}
}

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@@ -101,7 +101,7 @@ impl TermQuery {
EnableScoring::Enabled {
statistics_provider,
..
} => Bm25Weight::for_terms(statistics_provider, &[self.term.clone()])?,
} => Bm25Weight::for_terms(statistics_provider, std::slice::from_ref(&self.term))?,
EnableScoring::Disabled { .. } => {
Bm25Weight::new(Explanation::new("<no score>", 1.0f32), 1.0f32)
}

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@@ -2,7 +2,6 @@ use common::TinySet;
use crate::docset::{DocSet, TERMINATED};
use crate::query::score_combiner::{DoNothingCombiner, ScoreCombiner};
use crate::query::size_hint::estimate_union;
use crate::query::Scorer;
use crate::{DocId, Score};
@@ -51,8 +50,6 @@ pub struct BufferedUnionScorer<TScorer, TScoreCombiner = DoNothingCombiner> {
doc: DocId,
/// Combined score for current `doc` as produced by `TScoreCombiner`.
score: Score,
/// Number of documents in the segment.
num_docs: u32,
}
fn refill<TScorer: Scorer, TScoreCombiner: ScoreCombiner>(
@@ -81,11 +78,9 @@ fn refill<TScorer: Scorer, TScoreCombiner: ScoreCombiner>(
}
impl<TScorer: Scorer, TScoreCombiner: ScoreCombiner> BufferedUnionScorer<TScorer, TScoreCombiner> {
/// num_docs is the number of documents in the segment.
pub(crate) fn build(
docsets: Vec<TScorer>,
score_combiner_fn: impl FnOnce() -> TScoreCombiner,
num_docs: u32,
) -> BufferedUnionScorer<TScorer, TScoreCombiner> {
let non_empty_docsets: Vec<TScorer> = docsets
.into_iter()
@@ -99,7 +94,6 @@ impl<TScorer: Scorer, TScoreCombiner: ScoreCombiner> BufferedUnionScorer<TScorer
window_start_doc: 0,
doc: 0,
score: 0.0,
num_docs,
};
if union.refill() {
union.advance();
@@ -224,11 +218,11 @@ where
}
fn size_hint(&self) -> u32 {
estimate_union(self.docsets.iter().map(DocSet::size_hint), self.num_docs)
}
fn cost(&self) -> u64 {
self.docsets.iter().map(|docset| docset.cost()).sum()
self.docsets
.iter()
.map(|docset| docset.size_hint())
.max()
.unwrap_or(0u32)
}
fn count_including_deleted(&mut self) -> u32 {

View File

@@ -27,17 +27,11 @@ mod tests {
docs_list.iter().cloned().map(VecDocSet::from)
}
fn union_from_docs_list(docs_list: &[Vec<DocId>]) -> Box<dyn DocSet> {
let max_doc = docs_list
.iter()
.flat_map(|docs| docs.iter().copied())
.max()
.unwrap_or(0);
Box::new(BufferedUnionScorer::build(
vec_doc_set_from_docs_list(docs_list)
.map(|docset| ConstScorer::new(docset, 1.0))
.collect::<Vec<ConstScorer<VecDocSet>>>(),
DoNothingCombiner::default,
max_doc,
))
}
@@ -279,7 +273,6 @@ mod bench {
.map(|docset| ConstScorer::new(docset, 1.0))
.collect::<Vec<_>>(),
DoNothingCombiner::default,
100_000,
);
while v.doc() != TERMINATED {
v.advance();
@@ -301,7 +294,6 @@ mod bench {
.map(|docset| ConstScorer::new(docset, 1.0))
.collect::<Vec<_>>(),
DoNothingCombiner::default,
100_000,
);
while v.doc() != TERMINATED {
v.advance();

View File

@@ -99,10 +99,6 @@ impl<TDocSet: DocSet> DocSet for SimpleUnion<TDocSet> {
.unwrap_or(0u32)
}
fn cost(&self) -> u64 {
self.docsets.iter().map(|docset| docset.cost()).sum()
}
fn count_including_deleted(&mut self) -> u32 {
if self.doc == TERMINATED {
return 0u32;

View File

@@ -342,7 +342,7 @@ mod tests {
fn test_pack() -> crate::Result<()> {
let mut store_writer = TermInfoStoreWriter::new();
let mut term_infos = vec![];
let offset = |i| i * 13 + i * i;
let offset = |i| (i * 13 + i * i);
for i in 0usize..1000usize {
let term_info = TermInfo {
doc_freq: i as u32,