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… throw internal error ### What changes were proposed in this pull request? This PR fixes the error messages and classes when Python UDFs are used in higher order functions. ### Why are the changes needed? To show the proper user-facing exceptions with error classes. ### Does this PR introduce _any_ user-facing change? Yes, previously it threw internal error such as: ```python from pyspark.sql.functions import transform, udf, col, array spark.range(1).select(transform(array("id"), lambda x: udf(lambda y: y)(x))).collect() ``` Before: ``` py4j.protocol.Py4JJavaError: An error occurred while calling o74.collectToPython. : org.apache.spark.SparkException: Job aborted due to stage failure: Task 15 in stage 0.0 failed 1 times, most recent failure: Lost task 15.0 in stage 0.0 (TID 15) (ip-192-168-123-103.ap-northeast-2.compute.internal executor driver): org.apache.spark.SparkException: [INTERNAL_ERROR] Cannot evaluate expression: <lambda>(lambda x_0#3L)#2 SQLSTATE: XX000 at org.apache.spark.SparkException$.internalError(SparkException.scala:92) at org.apache.spark.SparkException$.internalError(SparkException.scala:96) ``` After: ``` pyspark.errors.exceptions.captured.AnalysisException: [INVALID_LAMBDA_FUNCTION_CALL.UNEVALUABLE] Invalid lambda function call. Python UDFs should be used in a lambda function at a higher order function. However, "<lambda>(lambda x_0#3L)" was a Python UDF. SQLSTATE: 42K0D; Project [transform(array(id#0L), lambdafunction(<lambda>(lambda x_0#3L)#2, lambda x_0#3L, false)) AS transform(array(id), lambdafunction(<lambda>(lambda x_0#3L), namedlambdavariable()))#4] +- Range (0, 1, step=1, splits=Some(16)) ``` ### How was this patch tested? Unittest was added ### Was this patch authored or co-authored using generative AI tooling? No. Closes apache#47079 from HyukjinKwon/SPARK-48706. Authored-by: Hyukjin Kwon <gurwls223@apache.org> Signed-off-by: Kent Yao <yao@apache.org>
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What changes were proposed in this pull request?
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Was this patch authored or co-authored using generative AI tooling?