LuciferYang opened a new pull request, #54484:
URL: https://github.com/apache/spark/pull/54484

   ### What changes were proposed in this pull request?
   This pr updates a test case in `DataFrameAggregateSuite` regarding `max_by` 
and `min_by` functions. Specifically, it refines the assertion logic for 
invalid `k` input (non-numeric string) to account for different behaviors 
depending on `spark.sql.ansi.enabled`.
   
   - **ANSI Enabled**: Expects `CAST_INVALID_INPUT` or "cannot be cast" error, 
as the string `'two'` cannot be cast to an integer.
   - **ANSI Disabled**: Expects `VALUE_OUT_OF_RANGE` error. In legacy mode, the 
invalid cast returns `0` (default for integer), which then triggers a 
validation error because `k` must be positive.
   
   
   ### Why are the changes needed?
   Resume daily testing in non-ANSI mode
   
   - https://github.com/apache/spark/actions/runs/22247813526/job/64365502163
   
   ```
   [info] - max_by and min_by with k *** FAILED *** (1 second, 431 milliseconds)
   [info]   "[DATATYPE_MISMATCH.VALUE_OUT_OF_RANGE] Cannot resolve "max_by(x, 
y, two)" due to data type mismatch: The `k` must be between [1, 100000] 
(current value = 0). SQLSTATE: 42K09; line 1 pos 7;
   [info]   'Aggregate [unresolvedalias(max_by(x#628078, y#628079, cast(two as 
int), false, 0, 0))]
   [info]   +- SubqueryAlias tab
   [info]      +- LocalRelation [x#628078, y#628079]
   [info]   " did not contain "CAST_INVALID_INPUT", and 
"[DATATYPE_MISMATCH.VALUE_OUT_OF_RANGE] Cannot resolve "max_by(x, y, two)" due 
to data type mismatch: The `k` must be between [1, 100000] (current value = 0). 
SQLSTATE: 42K09; line 1 pos 7;
   [info]   'Aggregate [unresolvedalias(max_by(x#628078, y#628079, cast(two as 
int), false, 0, 0))]
   [info]   +- SubqueryAlias tab
   [info]      +- LocalRelation [x#628078, y#628079]
   [info]   " did not contain "cannot be cast" 
(DataFrameAggregateSuite.scala:1386)
   ...
   [info] *** 4 TESTS FAILED ***
   [error] Failed: Total 4096, Failed 4, Errors 0, Passed 4092, Ignored 13
   [error] Failed tests:
   [error]      org.apache.spark.sql.SingleLevelAggregateHashMapSuite
   [error]      org.apache.spark.sql.DataFrameAggregateSuite
   [error]      org.apache.spark.sql.TwoLevelAggregateHashMapSuite
   [error]      
org.apache.spark.sql.TwoLevelAggregateHashMapWithVectorizedMapSuite
   [error] (sql / Test / test) sbt.TestsFailedException: Tests unsuccessful
   ```
   
   ### Does this PR introduce _any_ user-facing change?
   No
   
   
   ### How was this patch tested?
   Manually verify by running the command `SPARK_ANSI_SQL_MODE=false build/sbt 
"sql/testOnly org.apache.spark.sql.SingleLevelAggregateHashMapSuite 
org.apache.spark.sql.DataFrameAggregateSuite 
org.apache.spark.sql.TwoLevelAggregateHashMapSuite 
org.apache.spark.sql.TwoLevelAggregateHashMapWithVectorizedMapSuite"`, and all 
tests pass successfully.
   
   ### Was this patch authored or co-authored using generative AI tooling?
   No
   


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