fix: Fallback to Spark for unsupported partitioning #759
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Codecov ReportAttention: Patch coverage is
Additional details and impacted files@@ Coverage Diff @@
## main #759 +/- ##
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+ Coverage 53.66% 54.11% +0.45%
- Complexity 810 819 +9
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Files 107 107
Lines 10265 10316 +51
Branches 1930 1947 +17
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+ Hits 5509 5583 +74
+ Misses 3781 3743 -38
- Partials 975 990 +15 ☔ View full report in Codecov by Sentry. |
viirya
commented
Aug 2, 2024
| columns: Array[Column], | ||
| partitions: Array[Transform], | ||
| catalog: InMemoryTableCatalog = catalog): Unit = { | ||
| catalog.createTable(Identifier.of(Array("ns"), table), columns, partitions, emptyProps) |
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Some APIs are added since Spark 3.4. One config is added since Spark 4.0. So this test is only compilable for 3.4+ and only useful for 4.0.
kazuyukitanimura
approved these changes
Aug 2, 2024
| val msg3 = createMessage( | ||
| isShuffleEnabled && columnarShuffleEnabled && !QueryPlanSerde | ||
| .supportPartitioningTypes(s.child.output) | ||
| .supportPartitioningTypes(s.child.output, s.outputPartitioning) |
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nit s.outputPartitioning => outputPartitioning
andygrove
approved these changes
Aug 2, 2024
|
Merged. Thanks @kazuyukitanimura @andygrove |
himadripal
pushed a commit
to himadripal/datafusion-comet
that referenced
this pull request
Sep 7, 2024
* fix: Fallback to Spark for unsupported partitioning * fix * Move test * For review (cherry picked from commit 2d95fea)
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Which issue does this PR close?
Closes #760.
Rationale for this change
What changes are included in this PR?
How are these changes tested?