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Top-K eager batch sorting #7180
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
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@@ -87,8 +87,7 @@ impl ExternalSorterMetrics { | |
| /// 3. when input is exhausted, merge all in memory batches and spills to get a total order. | ||
| struct ExternalSorter { | ||
| schema: SchemaRef, | ||
| in_mem_batches: Vec<RecordBatch>, | ||
| in_mem_batches_sorted: bool, | ||
| in_mem_batches: Vec<(bool, RecordBatch)>, | ||
| spills: Vec<NamedTempFile>, | ||
| /// Sort expressions | ||
| expr: Arc<[PhysicalSortExpr]>, | ||
|
|
@@ -118,7 +117,6 @@ impl ExternalSorter { | |
| Self { | ||
| schema, | ||
| in_mem_batches: vec![], | ||
| in_mem_batches_sorted: true, | ||
| spills: vec![], | ||
| expr: expr.into(), | ||
| metrics, | ||
|
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@@ -133,11 +131,28 @@ impl ExternalSorter { | |
| /// Appends an unsorted [`RecordBatch`] to `in_mem_batches` | ||
| /// | ||
| /// Updates memory usage metrics, and possibly triggers spilling to disk | ||
| async fn insert_batch(&mut self, input: RecordBatch) -> Result<()> { | ||
| async fn insert_batch(&mut self, mut input: RecordBatch) -> Result<()> { | ||
| if input.num_rows() == 0 { | ||
| return Ok(()); | ||
| } | ||
|
|
||
| let mut batch_sorted = false; | ||
| if self.fetch.map_or(false, |f| f < input.num_rows()) { | ||
| // Eagerly sort the batch to potentially reduce the number of rows | ||
| // after applying the fetch parameter; first perform a memory reservation | ||
| // for the sorting procedure. | ||
| let mut reservation = | ||
|
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| MemoryConsumer::new(format!("insert_batch{}", self.partition_id)) | ||
| .register(&self.runtime.memory_pool); | ||
|
|
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| // TODO: This should probably be try_grow (#5885) | ||
| reservation.resize(input.get_array_memory_size()); | ||
| // Maybe we should perform sorting in a parallel task to unblock the caller | ||
|
||
| input = sort_batch(&input, &self.expr, self.fetch)?; | ||
|
Contributor
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. I wonder whether you could recover part of the perf difference by concat + sorting only once every
Contributor
Author
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. Yeah, that's worth trying to benchmark as well. It could also be something like every
Contributor
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. Yes, definitely.
Contributor
Author
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. Fwiw, I did try out a variety of approaches along these lines, but still failed to eliminate the perf difference. There's probably a combination of parameters that is just right and could yield better results, but with the native Top-K operator in the works that likely won't be necessary. |
||
| reservation.free(); | ||
| batch_sorted = true; | ||
| } | ||
|
|
||
| let size = batch_byte_size(&input); | ||
| if self.reservation.try_grow(size).is_err() { | ||
| let before = self.reservation.size(); | ||
|
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@@ -159,8 +174,7 @@ impl ExternalSorter { | |
| } | ||
| } | ||
|
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||
| self.in_mem_batches.push(input); | ||
| self.in_mem_batches_sorted = false; | ||
| self.in_mem_batches.push((batch_sorted, input)); | ||
| Ok(()) | ||
| } | ||
|
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|
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@@ -224,7 +238,11 @@ impl ExternalSorter { | |
| self.in_mem_sort().await?; | ||
|
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| let spillfile = self.runtime.disk_manager.create_tmp_file("Sorting")?; | ||
| let batches = std::mem::take(&mut self.in_mem_batches); | ||
|
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||
| let (sorted, batches): (Vec<bool>, Vec<RecordBatch>) = | ||
| std::mem::take(&mut self.in_mem_batches).into_iter().unzip(); | ||
| assert!(sorted.iter().all(|&s| s)); | ||
|
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| spill_sorted_batches(batches, spillfile.path(), self.schema.clone()).await?; | ||
| let used = self.reservation.free(); | ||
| self.metrics.spill_count.add(1); | ||
|
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@@ -235,23 +253,25 @@ impl ExternalSorter { | |
|
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| /// Sorts the in_mem_batches in place | ||
| async fn in_mem_sort(&mut self) -> Result<()> { | ||
| if self.in_mem_batches_sorted { | ||
| if self.in_mem_batches.iter().all(|(sorted, _)| *sorted) { | ||
| return Ok(()); | ||
| } | ||
|
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||
| self.in_mem_batches = self | ||
| .in_mem_sort_stream(self.metrics.baseline.intermediate())? | ||
| .try_collect() | ||
| .await?; | ||
| .try_collect::<Vec<_>>() | ||
| .await? | ||
| .into_iter() | ||
| .map(|batch| (true, batch)) | ||
| .collect(); | ||
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||
| let size: usize = self | ||
| .in_mem_batches | ||
| .iter() | ||
| .map(|x| x.get_array_memory_size()) | ||
| .map(|(_, x)| x.get_array_memory_size()) | ||
| .sum(); | ||
|
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||
| self.reservation.resize(size); | ||
| self.in_mem_batches_sorted = true; | ||
| Ok(()) | ||
| } | ||
|
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@@ -262,8 +282,8 @@ impl ExternalSorter { | |
| ) -> Result<SendableRecordBatchStream> { | ||
| assert_ne!(self.in_mem_batches.len(), 0); | ||
| if self.in_mem_batches.len() == 1 { | ||
| let batch = self.in_mem_batches.remove(0); | ||
| let stream = self.sort_batch_stream(batch, metrics)?; | ||
| let (sorted, batch) = self.in_mem_batches.remove(0); | ||
| let stream = self.sort_batch_stream(batch, sorted, metrics)?; | ||
| self.in_mem_batches.clear(); | ||
| return Ok(stream); | ||
| } | ||
|
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@@ -273,16 +293,23 @@ impl ExternalSorter { | |
| // This is a very rough heuristic and likely could be refined further | ||
| if self.reservation.size() < 1048576 { | ||
| // Concatenate memory batches together and sort | ||
| let batch = concat_batches(&self.schema, &self.in_mem_batches)?; | ||
| let (_, batches): (Vec<bool>, Vec<RecordBatch>) = | ||
| std::mem::take(&mut self.in_mem_batches).into_iter().unzip(); | ||
| let batch = concat_batches(&self.schema, &batches)?; | ||
| self.in_mem_batches.clear(); | ||
| return self.sort_batch_stream(batch, metrics); | ||
| // Even if all individual batches were themselves sorted the resulting concatenated one | ||
| // isn't guaranteed to be sorted, so we must perform sorting on the stream. | ||
| return self.sort_batch_stream(batch, false, metrics); | ||
|
Contributor
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. Another approach might be be to not use the
Contributor
Author
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. Good point; will try to benchmark that change too.
Contributor
Author
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. So I did try to test this approach as well, and then saw some improvements that seemed too good to be true. I went and re-ran the benchmarks again and the improvements held, until they didn't at some point 🤷🏻♂️ (fwiw I'm running the benchmarks on a cloud VM, not dedicated hardware). In hindsight, the sorting benchmarks actually do not use a memory limit and so there were no spills and this code path wasn't exercised. I did try running the benchmarks with memory limits on, but then I hit Either way, I'll add this check now even without doing benchmarking on it because it seems it can only help. |
||
| } | ||
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| let streams = std::mem::take(&mut self.in_mem_batches) | ||
| .into_iter() | ||
| .map(|batch| { | ||
| .map(|(sorted, batch)| { | ||
| let metrics = self.metrics.baseline.intermediate(); | ||
| Ok(spawn_buffered(self.sort_batch_stream(batch, metrics)?, 1)) | ||
| Ok(spawn_buffered( | ||
| self.sort_batch_stream(batch, sorted, metrics)?, | ||
| 1, | ||
| )) | ||
| }) | ||
| .collect::<Result<_>>()?; | ||
|
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@@ -299,27 +326,34 @@ impl ExternalSorter { | |
| fn sort_batch_stream( | ||
| &self, | ||
| batch: RecordBatch, | ||
| sorted: bool, | ||
| metrics: BaselineMetrics, | ||
| ) -> Result<SendableRecordBatchStream> { | ||
| let schema = batch.schema(); | ||
|
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||
| let mut reservation = | ||
| MemoryConsumer::new(format!("sort_batch_stream{}", self.partition_id)) | ||
| .register(&self.runtime.memory_pool); | ||
|
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| // TODO: This should probably be try_grow (#5885) | ||
| reservation.resize(batch.get_array_memory_size()); | ||
|
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| let fetch = self.fetch; | ||
| let expressions = self.expr.clone(); | ||
| let stream = futures::stream::once(futures::future::lazy(move |_| { | ||
| let sorted = sort_batch(&batch, &expressions, fetch)?; | ||
| metrics.record_output(sorted.num_rows()); | ||
| drop(batch); | ||
| reservation.free(); | ||
| Ok(sorted) | ||
| })); | ||
| Ok(Box::pin(RecordBatchStreamAdapter::new(schema, stream))) | ||
| if !sorted { | ||
| // Reserve some memory for sorting the batch | ||
| let mut reservation = | ||
| MemoryConsumer::new(format!("sort_batch_stream{}", self.partition_id)) | ||
| .register(&self.runtime.memory_pool); | ||
|
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| // TODO: This should probably be try_grow (#5885) | ||
| reservation.resize(batch.get_array_memory_size()); | ||
|
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| let fetch = self.fetch; | ||
| let expressions = self.expr.clone(); | ||
| let stream = futures::stream::once(futures::future::lazy(move |_| { | ||
| let output = sort_batch(&batch, &expressions, fetch)?; | ||
| metrics.record_output(output.num_rows()); | ||
| drop(batch); | ||
| reservation.free(); | ||
| Ok(output) | ||
| })); | ||
| Ok(Box::pin(RecordBatchStreamAdapter::new(schema, stream))) | ||
| } else { | ||
| let stream = futures::stream::once(futures::future::lazy(move |_| Ok(batch))); | ||
| Ok(Box::pin(RecordBatchStreamAdapter::new(schema, stream))) | ||
| } | ||
| } | ||
| } | ||
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I'm thinking can we make the heuristic
f < input.num_rows() / 10or something magic numbers to only do eager sort for small `K's?There was a problem hiding this comment.
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I was also thinking something similar but along the lines of
f < input.num_rows() && f <= 100, so that we effectively have a hard cur-off for eager sorting after 100 rows.