[GitHub] [arrow-datafusion] yjshen commented on a change in pull request #2132: WIP: Reduce sort memory usage v1

[GitBox <gi...@apache.org>]

yjshen commented on a change in pull request #2132:
URL: https://github.com/apache/arrow-datafusion/pull/2132#discussion_r840496480



##########
File path: benchmarks/queries/q1.sql
##########
@@ -1,21 +1,12 @@
 select
     l_returnflag,
     l_linestatus,
-    sum(l_quantity) as sum_qty,
-    sum(l_extendedprice) as sum_base_price,
-    sum(l_extendedprice * (1 - l_discount)) as sum_disc_price,
-    sum(l_extendedprice * (1 - l_discount) * (1 + l_tax)) as sum_charge,
-    avg(l_quantity) as avg_qty,
-    avg(l_extendedprice) as avg_price,
-    avg(l_discount) as avg_disc,
-    count(*) as count_order
+    l_quantity,
+    l_extendedprice,
+    l_discount,
+    l_tax
 from
     lineitem
-where

Review comment:
       tmp change to bench sort

##########
File path: datafusion/core/src/physical_plan/sorts/sort2.rs
##########
@@ -0,0 +1,1147 @@
+// Licensed to the Apache Software Foundation (ASF) under one
+// or more contributor license agreements.  See the NOTICE file
+// distributed with this work for additional information
+// regarding copyright ownership.  The ASF licenses this file
+// to you under the Apache License, Version 2.0 (the
+// "License"); you may not use this file except in compliance
+// with the License.  You may obtain a copy of the License at
+//
+//   http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing,
+// software distributed under the License is distributed on an
+// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+// KIND, either express or implied.  See the License for the
+// specific language governing permissions and limitations
+// under the License.
+
+//! Sort that deals with an arbitrary size of the input.
+//! It will do in-memory sorting if it has enough memory budget
+//! but spills to disk if needed.
+
+use crate::error::{DataFusionError, Result};
+use crate::execution::context::TaskContext;
+use crate::execution::memory_manager::{
+    human_readable_size, ConsumerType, MemoryConsumer, MemoryConsumerId, MemoryManager,
+};
+use crate::execution::runtime_env::RuntimeEnv;
+use crate::physical_plan::common::{batch_byte_size, IPCWriter, SizedRecordBatchStream};
+use crate::physical_plan::expressions::PhysicalSortExpr;
+use crate::physical_plan::metrics::{
+    BaselineMetrics, CompositeMetricsSet, MemTrackingMetrics, MetricsSet,
+};
+use crate::physical_plan::sorts::sort_preserving_merge::SortPreservingMergeStream;
+use crate::physical_plan::sorts::SortedStream;
+use crate::physical_plan::stream::RecordBatchReceiverStream;
+use crate::physical_plan::{
+    DisplayFormatType, Distribution, EmptyRecordBatchStream, ExecutionPlan, Partitioning,
+    RecordBatchStream, SendableRecordBatchStream, Statistics,
+};
+use crate::prelude::SessionConfig;
+use arrow::array::{make_array, Array, ArrayRef, MutableArrayData, UInt32Array};
+pub use arrow::compute::SortOptions;
+use arrow::compute::{concat, lexsort_to_indices, take, SortColumn, TakeOptions};
+use arrow::datatypes::SchemaRef;
+use arrow::error::Result as ArrowResult;
+use arrow::ipc::reader::FileReader;
+use arrow::record_batch::RecordBatch;
+use async_trait::async_trait;
+use futures::lock::Mutex;
+use futures::{Stream, StreamExt};
+use log::{debug, error};
+use std::any::Any;
+use std::cmp::min;
+use std::fmt;
+use std::fmt::{Debug, Formatter};
+use std::fs::File;
+use std::io::BufReader;
+use std::path::{Path, PathBuf};
+use std::sync::Arc;
+use std::task::{Context, Poll};
+use tempfile::NamedTempFile;
+use tokio::sync::mpsc::{Receiver, Sender};
+use tokio::task;
+
+/// Sort arbitrary size of data to get a total order (may spill several times during sorting based on free memory available).
+///
+/// The basic architecture of the algorithm:
+/// 1. get a non-empty new batch from input
+/// 2. check with the memory manager if we could buffer the batch in memory
+/// 2.1 if memory sufficient, then buffer batch in memory, go to 1.
+/// 2.2 if the memory threshold is reached, sort all buffered batches and spill to file.
+///     buffer the batch in memory, go to 1.
+/// 3. when input is exhausted, merge all in memory batches and spills to get a total order.
+struct ExternalSorter2 {
+    id: MemoryConsumerId,
+    schema: SchemaRef,
+    in_mem_batches: Mutex<Vec<RecordBatch>>,
+    spills: Mutex<Vec<NamedTempFile>>,
+    /// Sort expressions
+    expr: Vec<PhysicalSortExpr>,
+    session_config: Arc<SessionConfig>,
+    runtime: Arc<RuntimeEnv>,
+    metrics_set: CompositeMetricsSet,
+    metrics: BaselineMetrics,
+}
+
+impl ExternalSorter2 {
+    pub fn new(
+        partition_id: usize,
+        schema: SchemaRef,
+        expr: Vec<PhysicalSortExpr>,
+        metrics_set: CompositeMetricsSet,
+        session_config: Arc<SessionConfig>,
+        runtime: Arc<RuntimeEnv>,
+    ) -> Self {
+        let metrics = metrics_set.new_intermediate_baseline(partition_id);
+        Self {
+            id: MemoryConsumerId::new(partition_id),
+            schema,
+            in_mem_batches: Mutex::new(vec![]),
+            spills: Mutex::new(vec![]),
+            expr,
+            session_config,
+            runtime,
+            metrics_set,
+            metrics,
+        }
+    }
+
+    async fn insert_batch(
+        &self,
+        input: RecordBatch,
+        tracking_metrics: &MemTrackingMetrics,
+    ) -> Result<()> {
+        if input.num_rows() > 0 {
+            let size = batch_byte_size(&input);
+            self.try_grow(size).await?;
+            self.metrics.mem_used().add(size);
+            let mut in_mem_batches = self.in_mem_batches.lock().await;
+            // NB timer records time taken on drop, so there are no
+            // calls to `timer.done()` below.
+            let _timer = tracking_metrics.elapsed_compute().timer();
+            let partial = sort_batch(input, self.schema.clone(), &self.expr)?;
+            in_mem_batches.push(partial);
+        }
+        Ok(())
+    }
+
+    async fn spilled_before(&self) -> bool {
+        let spills = self.spills.lock().await;
+        !spills.is_empty()
+    }
+
+    /// MergeSort in mem batches as well as spills into total order with `SortPreservingMergeStream`.
+    async fn sort(&self) -> Result<SendableRecordBatchStream> {
+        let partition = self.partition_id();
+        let batch_size = self.session_config.batch_size;
+        let mut in_mem_batches = self.in_mem_batches.lock().await;
+
+        if self.spilled_before().await {
+            let tracking_metrics = self
+                .metrics_set
+                .new_intermediate_tracking(partition, self.runtime.clone());
+            let mut streams: Vec<SortedStream> = vec![];
+            if in_mem_batches.len() > 0 {
+                let in_mem_stream = in_mem_partial_sort(
+                    &mut *in_mem_batches,
+                    self.schema.clone(),
+                    &self.expr,
+                    batch_size,
+                    tracking_metrics,
+                )?;
+                let prev_used = self.metrics.mem_used().set(0);
+                streams.push(SortedStream::new(in_mem_stream, prev_used));
+            }
+
+            let mut spills = self.spills.lock().await;
+
+            for spill in spills.drain(..) {
+                let stream = read_spill_as_stream(spill, self.schema.clone())?;
+                streams.push(SortedStream::new(stream, 0));
+            }
+            let tracking_metrics = self
+                .metrics_set
+                .new_final_tracking(partition, self.runtime.clone());
+            Ok(Box::pin(SortPreservingMergeStream::new_from_streams(
+                streams,
+                self.schema.clone(),
+                &self.expr,
+                tracking_metrics,
+                self.session_config.batch_size,
+            )))
+        } else if in_mem_batches.len() > 0 {
+            let tracking_metrics = self
+                .metrics_set
+                .new_final_tracking(partition, self.runtime.clone());
+            let result = in_mem_partial_sort(
+                &mut *in_mem_batches,
+                self.schema.clone(),
+                &self.expr,
+                batch_size,
+                tracking_metrics,
+            );
+            // Report to the memory manager we are no longer using memory
+            self.metrics.mem_used().set(0);
+            result
+        } else {
+            Ok(Box::pin(EmptyRecordBatchStream::new(self.schema.clone())))
+        }
+    }
+
+    fn used(&self) -> usize {
+        self.metrics.mem_used().value()
+    }
+
+    fn spilled_bytes(&self) -> usize {
+        self.metrics.spilled_bytes().value()
+    }
+
+    fn spill_count(&self) -> usize {
+        self.metrics.spill_count().value()
+    }
+}
+
+impl Debug for ExternalSorter2 {
+    fn fmt(&self, f: &mut Formatter) -> fmt::Result {
+        f.debug_struct("ExternalSorter2")
+            .field("id", &self.id())
+            .field("memory_used", &self.used())
+            .field("spilled_bytes", &self.spilled_bytes())
+            .field("spill_count", &self.spill_count())
+            .finish()
+    }
+}
+
+#[derive(Debug, Copy, Clone)]
+struct CombinedIndex {
+    batch_idx: usize,
+    row_idx: usize,
+}
+
+impl Drop for ExternalSorter2 {
+    fn drop(&mut self) {
+        self.runtime.drop_consumer(self.id(), self.used());
+    }
+}
+
+#[async_trait]
+impl MemoryConsumer for ExternalSorter2 {
+    fn name(&self) -> String {
+        "ExternalSorter2".to_owned()
+    }
+
+    fn id(&self) -> &MemoryConsumerId {
+        &self.id
+    }
+
+    fn memory_manager(&self) -> Arc<MemoryManager> {
+        self.runtime.memory_manager.clone()
+    }
+
+    fn type_(&self) -> &ConsumerType {
+        &ConsumerType::Requesting
+    }
+
+    async fn spill(&self) -> Result<usize> {
+        debug!(
+            "{}[{}] spilling sort data of {} to disk while inserting ({} time(s) so far)",
+            self.name(),
+            self.id(),
+            self.used(),
+            self.spill_count()
+        );
+
+        let partition = self.partition_id();
+        let mut in_mem_batches = self.in_mem_batches.lock().await;
+        // we could always get a chance to free some memory as long as we are holding some
+        if in_mem_batches.len() == 0 {
+            return Ok(0);
+        }
+
+        let tracking_metrics = self
+            .metrics_set
+            .new_intermediate_tracking(partition, self.runtime.clone());
+
+        let spillfile = self.runtime.disk_manager.create_tmp_file()?;
+        let stream = in_mem_partial_sort(
+            &mut *in_mem_batches,
+            self.schema.clone(),
+            &*self.expr,
+            self.session_config.batch_size,
+            tracking_metrics,
+        );
+
+        spill_partial_sorted_stream(&mut stream?, spillfile.path(), self.schema.clone())
+            .await?;
+        let mut spills = self.spills.lock().await;
+        let used = self.metrics.mem_used().set(0);
+        self.metrics.record_spill(used);
+        spills.push(spillfile);
+        Ok(used)
+    }
+
+    fn mem_used(&self) -> usize {
+        self.metrics.mem_used().value()
+    }
+}
+
+/// consume the non-empty `sorted_bathes` and do in_mem_sort
+fn in_mem_partial_sort(
+    buffered_batches: &mut Vec<RecordBatch>,
+    schema: SchemaRef,
+    expressions: &[PhysicalSortExpr],
+    batch_size: usize,
+    tracking_metrics: MemTrackingMetrics,
+) -> Result<SendableRecordBatchStream> {
+    assert_ne!(buffered_batches.len(), 0);
+    if buffered_batches.len() == 1 {
+        let result = buffered_batches.pop();
+        Ok(Box::pin(SizedRecordBatchStream::new(
+            schema,
+            vec![Arc::new(result.unwrap())],
+            tracking_metrics,
+        )))
+    } else {
+        let batches = buffered_batches.drain(..).collect::<Vec<_>>();
+        let sorted_iter = {
+            // NB timer records time taken on drop, so there are no
+            // calls to `timer.done()` below.
+            let _timer = tracking_metrics.elapsed_compute().timer();
+            get_sorted_iter(&batches, expressions, batch_size)?
+        };
+        Ok(Box::pin(SortedSizedRecordBatchStream::new(
+            schema,
+            batches,
+            sorted_iter,
+            tracking_metrics,
+        )))
+    }
+}
+
+fn get_sorted_iter(

Review comment:
       The main changes:
   
   1. concrete all sort-columns
   2. sort to get the index array
   3. use `CombinedIndex` to avoid huge batch construction
   4. construct a small batch at a time.




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