tedyu opened a new pull request, #37952:
URL: https://github.com/apache/spark/pull/37952
### What changes were proposed in this pull request?
When running spark application against spark 3.3, I see the following :
```
java.lang.IllegalArgumentException: Unsupported data source V2 partitioning
type: CustomPartitioning
at
org.apache.spark.sql.execution.datasources.v2.V2ScanPartitioning$$anonfun$apply$1.applyOrElse(V2ScanPartitioning.scala:46)
at
org.apache.spark.sql.execution.datasources.v2.V2ScanPartitioning$$anonfun$apply$1.applyOrElse(V2ScanPartitioning.scala:34)
at
org.apache.spark.sql.catalyst.trees.TreeNode.$anonfun$transformDownWithPruning$1(TreeNode.scala:584)
```
The `CustomPartitioning` works fine with Spark 3.2.1
This PR proposes to relax the code and treat all unknown partitioning the
same way as that for `UnknownPartitioning`.
### Why are the changes needed?
3.3.0 doesn't seem to warrant such behavioral change (from that of 3.2.1
release).
### Does this PR introduce _any_ user-facing change?
This would allow user's custom partitioning to continue to work with 3.3.x
releases.
### How was this patch tested?
Existing test suite.
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