Dandandan commented on code in PR #15768:
URL: https://github.com/apache/datafusion/pull/15768#discussion_r2051763714
##########
datafusion/physical-plan/src/repartition/mod.rs:
##########
@@ -298,25 +299,15 @@ impl BatchPartitioner {
.into_iter()
.enumerate()
.filter_map(|(partition, indices)| {
- let indices: PrimitiveArray<UInt32Type> =
indices.into();
(!indices.is_empty()).then_some((partition,
indices))
})
.map(move |(partition, indices)| {
// Tracking time required for repartitioned
batches construction
let _timer = partitioner_timer.timer();
+ let b: Vec<&RecordBatch> =
batches.iter().collect();
// Produce batches based on indices
- let columns = take_arrays(batch.columns(),
&indices, None)?;
-
- let mut options = RecordBatchOptions::new();
- options =
options.with_row_count(Some(indices.len()));
- let batch = RecordBatch::try_new_with_options(
- batch.schema(),
- columns,
- &options,
- )
- .unwrap();
-
+ let batch = interleave_record_batch(&b, &indices)?;
Review Comment:
Yeah the speedup comes from avoiding copying the data a second time in
`concat` / CoalesceBatches. So when using `take_in` we should be careful to use
it once (for a single destination batch) to avoid doing the concat on the small
batches
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