Feat: support array_except function #1343
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Codecov ReportAttention: Patch coverage is
Additional details and impacted files@@ Coverage Diff @@
## main #1343 +/- ##
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- Coverage 56.12% 39.09% -17.03%
- Complexity 976 2065 +1089
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Files 119 260 +141
Lines 11743 60257 +48514
Branches 2251 12832 +10581
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+ Hits 6591 23560 +16969
- Misses 4012 32216 +28204
- Partials 1140 4481 +3341 ☔ View full report in Codecov by Sentry. |
andygrove
reviewed
Jan 27, 2025
| @@ -818,6 +819,22 @@ impl PhysicalPlanner { | |||
| )); | |||
| Ok(array_join_expr) | |||
| } | |||
| ExprStruct::ArrayExcept(expr) => { | |||
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Because the PR only contains basic tests, could you add a check to enable this expression only if CometConf.COMET_CAST_ALLOW_INCOMPATIBLE is enabled? We can remove this check in a future PR that adds comprehensive tests and demonstrates that we have Spark-compatible behavior for all supported data types.
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COMET_CAST_ALLOW_INCOMPATIBLE check has been added.
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Which issue does this PR close?
Related to Epic: #1042
array_except: SELECT array_except(array(1, 2, 3), array(1, 3, 5)) => array(2)
DataFusion' s array_except has same behavior with Spark 's array_except function
Spark: https://docs.databricks.com/en/sql/language-manual/functions/array_except.html
DataFusion: https://datafusion.apache.org/user-guide/sql/scalar_functions.html#array-except
Rationale for this change
Defined under Epic: #1042
What changes are included in this PR?
planner.rs: Maps Spark 's array_except function to DataFusion array_except_udf physical expression from Spark physical expression
expr.proto: array_except array_except has been added,
QueryPlanSerde.scala: arrays_except pattern matching case has been added,
CometExpressionSuite.scala: A new UT has been added for array_except function.
How are these changes tested?
A new UT has been added.