GitHub user cloud-fan opened a pull request:
https://github.com/apache/spark/pull/18121
[SPARK-20897][SQL] cached self-join should not fail
## What changes were proposed in this pull request?
The failed test case is, we have a `SortMergeJoinExec` for a self-join,
which means we have a `ReusedExchange` node in the query plan. It works fine
without caching, but throws an exception in
`SortMergeJoinExec.outputPartitioning` if we cache it.
The root cause is, `ReusedExchange` doesn't propagate the output
partitioning from its child, so in `SortMergeJoinExec.outputPartitioning` we
create `PartitioningCollection` with a hash partitioning and an unknown
partitioning, and fail.
This bug is mostly fine, because inserting the `ReusedExchange` is the last
step to prepare the physical plan, we won't call
`SortMergeJoinExec.outputPartitioning` anymore after this.
However, if the dataframe is cached, the physical plan of it becomes
`InMemoryTableScanExec`, which contains another physical plan representing the
cached query, and it has gone through the entire planning phase and may have
`ReusedExchange`. Then the planner call
`InMemoryTableScanExec.outputPartitioning`, which then calls
`SortMergeJoinExec.outputPartitioning` and trigger this bug.
## How was this patch tested?
a new regression test
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/cloud-fan/spark bug
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/spark/pull/18121.patch
To close this pull request, make a commit to your master/trunk branch
with (at least) the following in the commit message:
This closes #18121
----
commit ca4a3d1c62b172376694ba2435551653de82a345
Author: Wenchen Fan <[email protected]>
Date: 2017-05-26T15:06:40Z
cached self-join should not fail
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