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Posted to reviews@spark.apache.org by "ulysses-you (via GitHub)" <gi...@apache.org> on 2026/07/23 10:30:23 UTC
[PR] [SPARK-58290][SQL] Fix O(n^2) partition index access in ShufflePartitionsUtil.coalescePartitionsWithSkew [spark]
ulysses-you opened a new pull request, #57459:
URL: https://github.com/apache/spark/pull/57459
### What changes were proposed in this pull request?
In `ShufflePartitionsUtil.coalescePartitionsWithSkew`, the local `partitionIndices` is materialized from `inputPartitionSpecs`, whose inner collection is a `List` in practice. The coalescing loop then repeatedly accesses this sequence by index (`partitionIndices(i - 1)`, `partitionIndices(i)`, and the inner skew-section scan `partitionIndices(repeatIndex)`). Because `List.apply(i)` is O(i), the loop degrades to O(n^2) in the number of shuffle partitions.
This PR calls `.toArray` on `partitionIndices` so all indexed accesses become O(1), restoring the loop to O(n). The change is local; all downstream usages (`.head`, `.last`, indexed access, `.length`) are valid on `Array`, and the sequence is only read.
### Why are the changes needed?
A production job hung, and the driver thread dump showed it stuck in `ShufflePartitionsUtil.coalescePartitionsWithSkew`, spinning inside `List.drop` / `List.apply` (indexed list access):
```
scala.collection.immutable.List.drop(List.scala:79)
scala.collection.LinearSeqOps.apply(LinearSeq.scala:130)
scala.collection.immutable.List.apply(List.scala:79)
org.apache.spark.sql.execution.adaptive.ShufflePartitionsUtil$.coalescePartitionsWithSkew(ShufflePartitionsUtil.scala:166)
org.apache.spark.sql.execution.adaptive.ShufflePartitionsUtil$.coalescePartitions(ShufflePartitionsUtil.scala:75)
```
With a large number of shuffle partitions (skew join scenarios often produce many), the O(n^2) behavior can hang the driver during AQE planning.
Local micro-benchmark driving `coalescePartitions` on the skew path, `List` vs `Array` (same machine, same inputs):
| partitions | List (ms) | Array (ms) |
|-----------:|----------:|-----------:|
| 5000 | 72 | <1 |
| 10000 | 291 | <1 |
| 20000 | 1166 | 1 |
The `List` version's per-element cost grows linearly with partition count (confirming O(n^2)), while the `Array` version stays flat (O(n)).
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Existing tests, all passing locally (39 tests):
```
build/sbt "sql/testOnly *ShufflePartitionsUtilSuite *CoalesceShufflePartitionsSuite"
```
This is a pure performance fix with no behavior change.
### Was this patch authored or co-authored using generative AI tooling?
Generated-by: Claude Code (Claude Opus 4.8)
🤖 Generated with [Claude Code](https://claude.com/claude-code)
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Re: [PR] [SPARK-58290][SQL] Fix O(n^2) partition index access in ShufflePartitionsUtil.coalescePartitionsWithSkew [spark]
Posted by "cloud-fan (via GitHub)" <gi...@apache.org>.
cloud-fan commented on PR #57459:
URL: https://github.com/apache/spark/pull/57459#issuecomment-5058725715
**Merge Summary:**
- merged into master https://github.com/apache/spark/commit/3082cdfda92f4507542ccbf99cf777a51f29414c
- merged into branch-4.x https://github.com/apache/spark/commit/f52852becd4cdcc4e13d2ef85a9b9fc2f8e62ee2
*Posted by `merge_spark_pr.py`*
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Re: [PR] [SPARK-58290][SQL] Fix O(n^2) partition index access in ShufflePartitionsUtil.coalescePartitionsWithSkew [spark]
Posted by "cloud-fan (via GitHub)" <gi...@apache.org>.
cloud-fan closed pull request #57459: [SPARK-58290][SQL] Fix O(n^2) partition index access in ShufflePartitionsUtil.coalescePartitionsWithSkew
URL: https://github.com/apache/spark/pull/57459
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Re: [PR] [SPARK-58290][SQL] Fix O(n^2) partition index access in ShufflePartitionsUtil.coalescePartitionsWithSkew [spark]
Posted by "ulysses-you (via GitHub)" <gi...@apache.org>.
ulysses-you commented on PR #57459:
URL: https://github.com/apache/spark/pull/57459#issuecomment-5058211203
alco cc @dongjoon-hyun @cloud-fan @viirya thank you
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