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https://issues.apache.org/jira/browse/SPARK-25213?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16590397#comment-16590397
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Wenchen Fan commented on SPARK-25213:
-------------------------------------
[~rdblue] I think we have a problem here. In
https://github.com/apache/spark/pull/21118 we allow data source to produce
internal row instead of unsafe row, assuming Filter/Project is OK with internal
row. However, we missed python UDF, which can be in Project/Filter and must
work with unsafe row.
If we require python UDF to work with internal row, that is probably a perf
regression as the Python UDF needs to do an extra unsafe projection.
> DataSourceV2 doesn't seem to produce unsafe rows
> -------------------------------------------------
>
> Key: SPARK-25213
> URL: https://issues.apache.org/jira/browse/SPARK-25213
> Project: Spark
> Issue Type: Task
> Components: SQL
> Affects Versions: 2.4.0
> Reporter: Li Jin
> Priority: Major
>
> Reproduce (Need to compile test-classes):
> bin/pyspark --driver-class-path sql/core/target/scala-2.11/test-classes
> {code:java}
> datasource_v2_df = spark.read \
> .format("org.apache.spark.sql.sources.v2.SimpleDataSourceV2")
> \
> .load()
> result = datasource_v2_df.withColumn('x', udf(lambda x: x,
> 'int')(datasource_v2_df['i']))
> result.show()
> {code}
> The above code fails with:
> {code:java}
> Caused by: java.lang.ClassCastException:
> org.apache.spark.sql.catalyst.expressions.GenericInternalRow cannot be cast
> to org.apache.spark.sql.catalyst.expressions.UnsafeRow
> at
> org.apache.spark.sql.execution.python.EvalPythonExec$$anonfun$doExecute$1$$anonfun$5.apply(EvalPythonExec.scala:127)
> at
> org.apache.spark.sql.execution.python.EvalPythonExec$$anonfun$doExecute$1$$anonfun$5.apply(EvalPythonExec.scala:126)
> at scala.collection.Iterator$$anon$11.next(Iterator.scala:410)
> at scala.collection.Iterator$$anon$11.next(Iterator.scala:410)
> {code}
> Seems like Data Source V2 doesn't produce unsafeRows here.
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