mirror of
https://github.com/GreptimeTeam/greptimedb.git
synced 2026-01-04 12:22:55 +00:00
refactor: remove per series scan from SeqScan
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@@ -30,7 +30,7 @@ use datatypes::schema::SchemaRef;
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use snafu::ResultExt;
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use store_api::metadata::RegionMetadataRef;
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use store_api::region_engine::{PartitionRange, PrepareRequest, RegionScanner, ScannerProperties};
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use store_api::storage::{TimeSeriesDistribution, TimeSeriesRowSelector};
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use store_api::storage::TimeSeriesRowSelector;
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use tokio::sync::Semaphore;
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use crate::error::{PartitionOutOfRangeSnafu, Result};
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@@ -207,10 +207,6 @@ impl SeqScan {
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));
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}
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if self.stream_ctx.input.distribution == Some(TimeSeriesDistribution::PerSeries) {
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return self.scan_partition_by_series(metrics_set, partition);
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}
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let stream_ctx = self.stream_ctx.clone();
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let semaphore = self.new_semaphore();
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let partition_ranges = self.properties.partitions[partition].clone();
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@@ -307,97 +303,6 @@ impl SeqScan {
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Ok(stream)
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}
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/// Scans all ranges in the given partition and merge by time series.
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/// Otherwise the returned stream might not contains any data.
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fn scan_partition_by_series(
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&self,
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metrics_set: &ExecutionPlanMetricsSet,
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partition: usize,
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) -> Result<SendableRecordBatchStream, BoxedError> {
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let stream_ctx = self.stream_ctx.clone();
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let semaphore = self.new_semaphore();
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let partition_ranges = self.properties.partitions[partition].clone();
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let distinguish_range = self.properties.distinguish_partition_range;
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let part_metrics = self.new_partition_metrics(metrics_set, partition);
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debug_assert!(!self.compaction);
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let stream = try_stream! {
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part_metrics.on_first_poll();
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let range_builder_list = Arc::new(RangeBuilderList::new(
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stream_ctx.input.num_memtables(),
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stream_ctx.input.num_files(),
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));
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// Scans all parts.
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let mut sources = Vec::with_capacity(partition_ranges.len());
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for part_range in partition_ranges {
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build_sources(
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&stream_ctx,
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&part_range,
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false,
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&part_metrics,
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range_builder_list.clone(),
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&mut sources,
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);
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}
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// Builds a reader that merge sources from all parts.
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let mut reader =
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Self::build_reader_from_sources(&stream_ctx, sources, semaphore.clone())
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.await
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.map_err(BoxedError::new)
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.context(ExternalSnafu)?;
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let cache = &stream_ctx.input.cache_strategy;
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let mut metrics = ScannerMetrics::default();
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let mut fetch_start = Instant::now();
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while let Some(batch) = reader
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.next_batch()
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.await
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.map_err(BoxedError::new)
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.context(ExternalSnafu)?
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{
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metrics.scan_cost += fetch_start.elapsed();
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metrics.num_batches += 1;
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metrics.num_rows += batch.num_rows();
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debug_assert!(!batch.is_empty());
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if batch.is_empty() {
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continue;
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}
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let convert_start = Instant::now();
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let record_batch = stream_ctx.input.mapper.convert(&batch, cache)?;
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metrics.convert_cost += convert_start.elapsed();
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let yield_start = Instant::now();
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yield record_batch;
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metrics.yield_cost += yield_start.elapsed();
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fetch_start = Instant::now();
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}
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// Yields an empty part to indicate this range is terminated.
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// The query engine can use this to optimize some queries.
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if distinguish_range {
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let yield_start = Instant::now();
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yield stream_ctx.input.mapper.empty_record_batch();
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metrics.yield_cost += yield_start.elapsed();
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}
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metrics.scan_cost += fetch_start.elapsed();
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part_metrics.merge_metrics(&metrics);
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part_metrics.on_finish();
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};
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let stream = Box::pin(RecordBatchStreamWrapper::new(
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self.stream_ctx.input.mapper.output_schema(),
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Box::pin(stream),
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));
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Ok(stream)
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}
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fn new_semaphore(&self) -> Option<Arc<Semaphore>> {
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if self.properties.target_partitions() > self.properties.num_partitions() {
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// We can use additional tasks to read the data if we have more target partitions than actual partitions.
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@@ -509,8 +414,8 @@ pub(crate) fn build_sources(
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// Gets range meta.
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let range_meta = &stream_ctx.ranges[part_range.identifier];
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#[cfg(debug_assertions)]
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if compaction || stream_ctx.input.distribution == Some(TimeSeriesDistribution::PerSeries) {
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// Compaction or per series distribution expects input sources are not been split.
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if compaction {
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// Compaction expects input sources are not been split.
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debug_assert_eq!(range_meta.indices.len(), range_meta.row_group_indices.len());
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for (i, row_group_idx) in range_meta.row_group_indices.iter().enumerate() {
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// It should scan all row groups.
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