[SPARK-49386][CORE][SQL][FOLLOWUP] More accurate memory tracking for memory based spill threshold #52190
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cloud-fan
commented
Sep 1, 2025
| @@ -149,7 +149,7 @@ class ArrowWindowPythonEvaluatorFactory( | |||
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| private val inMemoryThreshold = conf.windowExecBufferInMemoryThreshold | |||
| private val spillThreshold = conf.windowExecBufferSpillThreshold | |||
| private val spillSizeThreshold = conf.windowExecBufferSpillSizeThreshold | |||
| private val sizeInBytesSpillThreshold = conf.windowExecBufferSpillSizeThreshold | |||
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For now I reuse the spill threshold config for the ExternalAppendOnlyUnsafeRowArray in-memory buffer threshold as well. We can add new configs if we want (but it will be a lot of configs).
cloud-fan
commented
Sep 2, 2025
core/src/main/java/org/apache/spark/shuffle/sort/ShuffleExternalSorter.java
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cloud-fan
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Sep 2, 2025
core/src/main/java/org/apache/spark/shuffle/sort/ShuffleExternalSorter.java
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What changes were proposed in this pull request?
This is a followup of #47856 . It makes the memory tracking more accurate in several places:
ShuffleExternalSorter/UnsafeExternalSorter, the memory is used by both the sorter itself, and its underlying in-memort sorter (for sorting shuffle partition ids). We need to add them up to calcuate the current memory usage.ExternalAppendOnlyUnsafeRowArray, the records are inserted to an in-memory buffer first. If the buffer gets too large (currently based on num records), we switch toUnsafeExternalSorter. The in-memory buffer also needs a memory based thresholdWhy are the changes needed?
More accurate memory tracking results to better spill decisions
Does this PR introduce any user-facing change?
No, the feature is not released yet.
How was this patch tested?
existing tests
Was this patch authored or co-authored using generative AI tooling?
no