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Posted to github@arrow.apache.org by GitBox <gi...@apache.org> on 2022/11/08 08:45:55 UTC
[GitHub] [arrow-datafusion] mingmwang opened a new issue, #4139: JoinSelection Rule to choose physical join implementation: HashJoin(Partitioned or CollectLeft) or SortMergeJoin base on Stats
mingmwang opened a new issue, #4139:
URL: https://github.com/apache/arrow-datafusion/issues/4139
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[GitHub] [arrow-datafusion] mingmwang commented on issue #4139: JoinSelection Rule to choose physical join implementation: HashJoin(Partitioned or CollectLeft) or SortMergeJoin base on Stats
Posted by GitBox <gi...@apache.org>.
mingmwang commented on issue #4139:
URL: https://github.com/apache/arrow-datafusion/issues/4139#issuecomment-1306856449
@alamb @andygrove @isidentical @Dandandan @yahoNanJing
I plan to add a new physical rule for physical join implementation selection based on stats.
The basic idea is if one of side(left or right) is small enough(threshold on size or row count, for example 10M), will choose HashJoin:CollectLeft.
Else if either side exceed that threshold but still smaller than hash join threshold(estimated_size/partition_count <= 128M for example), will choose HashJoin: Partitioned.
Otherwise choose SortMergeJoin.
Please share your thoughts.
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[GitHub] [arrow-datafusion] Dandandan commented on issue #4139: JoinSelection Rule to choose physical join implementation: HashJoin(Partitioned or CollectLeft) or SortMergeJoin base on Stats
Posted by GitBox <gi...@apache.org>.
Dandandan commented on issue #4139:
URL: https://github.com/apache/arrow-datafusion/issues/4139#issuecomment-1306880712
Sounds like a good plan.
For hash join, probably needs some benchmarking to figure out good defaults and avoid performance degradation. `CollectLeft` limits the amount of parellization on the left side: building the hash table is relatively expensive and is done (at least currently) in a single thread. In quite a few cases it might be more beneficial to do a (local) hash repartitioning which is relatively cheap.
It also depends on the size of the probe/right side: if that's e.g. >100x as big as the left side it might be beneficial to avoid the hash repartitioning on the right side by switching to `CollectLeft`.
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[GitHub] [arrow-datafusion] alamb closed issue #4139: JoinSelection Rule to choose physical join implementation: HashJoin(Partitioned or CollectLeft) or SortMergeJoin base on Stats
Posted by GitBox <gi...@apache.org>.
alamb closed issue #4139: JoinSelection Rule to choose physical join implementation: HashJoin(Partitioned or CollectLeft) or SortMergeJoin base on Stats
URL: https://github.com/apache/arrow-datafusion/issues/4139
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[GitHub] [arrow-datafusion] alamb commented on issue #4139: JoinSelection Rule to choose physical join implementation: HashJoin(Partitioned or CollectLeft) or SortMergeJoin base on Stats
Posted by GitBox <gi...@apache.org>.
alamb commented on issue #4139:
URL: https://github.com/apache/arrow-datafusion/issues/4139#issuecomment-1307854196
I agree with @Dandandan that doing some benchmarking on sort merge join is likely a good idea. I don't think we have much at the moment as it is never used.
What I think would be an ideal solution, though maybe harder to implement, is to *NOT* decide between has or sort merge join at plan time, but to decide at runtime
So that would involve starting out using HashJoin but if the hash table spilled (or exceeded some size threshold) sort/spill it and then switch to sort-merge-join
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