[GitHub] [arrow-datafusion] Dandandan commented on a diff in pull request #2132: Reduce SortExec memory usage by void constructing single huge batch

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

Dandandan commented on code in PR #2132:
URL: https://github.com/apache/arrow-datafusion/pull/2132#discussion_r842129926


##########
datafusion/core/src/physical_plan/sorts/sort.rs:
##########
@@ -268,36 +282,220 @@ impl MemoryConsumer for ExternalSorter {
 
 /// consume the non-empty `sorted_bathes` and do in_mem_sort
 fn in_mem_partial_sort(
-    buffered_batches: &mut Vec<RecordBatch>,
+    buffered_batches: &mut Vec<BatchWithSortArray>,
     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().sorted_batch)],
+            tracking_metrics,
+        )))
+    } else {
+        let (sorted_arrays, batches): (Vec<Vec<ArrayRef>>, Vec<RecordBatch>) =
+            buffered_batches
+                .drain(..)
+                .into_iter()
+                .map(|b| {
+                    let BatchWithSortArray {
+                        sort_arrays,
+                        sorted_batch: batch,
+                    } = b;
+                    (sort_arrays, batch)
+                })
+                .unzip();
+
+        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(&sorted_arrays, expressions, batch_size)?
+        };
+        Ok(Box::pin(SortedSizedRecordBatchStream::new(
+            schema,
+            batches,
+            sorted_iter,
+            tracking_metrics,
+        )))
+    }
+}
 
-    let result = {
-        // NB timer records time taken on drop, so there are no
-        // calls to `timer.done()` below.
-        let _timer = tracking_metrics.elapsed_compute().timer();
+#[derive(Debug, Copy, Clone)]
+struct CompositeIndex {
+    batch_idx: u32,
+    row_idx: u32,
+}
 
-        let pre_sort = if buffered_batches.len() == 1 {
-            buffered_batches.pop()
-        } else {
-            let batches = buffered_batches.drain(..).collect::<Vec<_>>();
-            // combine all record batches into one for each column
-            common::combine_batches(&batches, schema.clone())?
-        };
+/// Get sorted iterator by sort concatenated `SortColumn`s
+fn get_sorted_iter(
+    sort_arrays: &[Vec<ArrayRef>],
+    expr: &[PhysicalSortExpr],
+    batch_size: usize,
+) -> Result<SortedIterator> {
+    let row_indices = sort_arrays
+        .iter()
+        .enumerate()
+        .flat_map(|(i, arrays)| {
+            (0..arrays[0].len())
+                .map(|r| CompositeIndex {
+                    // since we original use UInt32Array to index the combined mono batch,
+                    // component record batches won't overflow as well,
+                    // use u32 here for space efficiency.
+                    batch_idx: i as u32,
+                    row_idx: r as u32,
+                })
+                .collect::<Vec<CompositeIndex>>()

Review Comment:
   Doing a collect here while flattening it later seems doing some extra allocations. I think we should be able to generate this in one go?



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