[SPARK-24985][SQL]Avoid full outer join OOM on skewed dataset #29071
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Can one of the admins verify this patch? |
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@viirya Can you review this PR please? |
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We're closing this PR because it hasn't been updated in a while. This isn't a judgement on the merit of the PR in any way. It's just a way of keeping the PR queue manageable. |
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What issue does this pull request address ?
JIRA: https://issues.apache.org/jira/browse/SPARK-24985
In the case of Full Outer Joins of large tables, in the presence of data skew around the join keys for either of the joined tables, OOMs exceptions occur. While its possible to increase the heap size to workaround, Spark should be resilient to such issues as skews can happen arbitrarily.
What changes were proposed in this pull request?
#16909 introduced ExternalAppendOnlyUnsafeRowArray & changed SortMergeJoinExec to use ExternalAppendOnlyUnsafeRowArray for every join, except 'Full Outer Join'. This PR makes changes to make 'Full Outer Joins' to use ExternalAppendOnlyUnsafeRowArray.
Why are the changes needed?
This PR by @sujithjay use ExternalAppendOnlyUnsafeRowArray instead of ArrayBuffer.
But the performance of the code is very poor, because many iterators are created.
This PR hold the iterator to improve performance.
Does this PR introduce any user-facing change?
No.
How was this patch tested?
JoinSuiteandOuterJoinSuite