[jira] [Created] (FLINK-21876) Provide a way to handle when the returned value of Python UDF doesn't match the defined result type

["Dian Fu (Jira)" <ji...@apache.org>]

Dian Fu created FLINK-21876:
-------------------------------

             Summary: Provide a way to handle when the returned value of Python UDF doesn't match the defined result type
                 Key: FLINK-21876
                 URL: https://issues.apache.org/jira/browse/FLINK-21876
             Project: Flink
          Issue Type: Improvement
          Components: API / Python
    Affects Versions: 1.12.0, 1.11.0, 1.10.0
            Reporter: Dian Fu
            Assignee: Dian Fu
             Fix For: 1.13.0, 1.12.3


Currently, when the returned value of Python UDF doesn't match the defined result type of the Python UDF, it will thrown the following exception during execution:
{code}
Caused by: java.io.EOFException
at java.io.DataInputStream.readFully(DataInputStream.java:197)
at java.io.DataInputStream.readFully(DataInputStream.java:169)
at org.apache.flink.table.runtime.typeutils.StringDataSerializer.deserializeInternal(StringDataSerializer.java:88)
at org.apache.flink.table.runtime.typeutils.StringDataSerializer.deserialize(StringDataSerializer.java:82)
at org.apache.flink.table.runtime.typeutils.StringDataSerializer.deserialize(StringDataSerializer.java:34)
at org.apache.flink.table.runtime.typeutils.serializers.python.MapDataSerializer.deserializeInternal(MapDataSerializer.java:129)
at org.apache.flink.table.runtime.typeutils.serializers.python.MapDataSerializer.deserialize(MapDataSerializer.java:110)
at org.apache.flink.table.runtime.typeutils.serializers.python.MapDataSerializer.deserialize(MapDataSerializer.java:46)
at org.apache.flink.table.runtime.typeutils.serializers.python.RowDataSerializer.deserialize(RowDataSerializer.java:106)
at org.apache.flink.table.runtime.typeutils.serializers.python.RowDataSerializer.deserialize(RowDataSerializer.java:49)
at org.apache.flink.table.runtime.operators.python.scalar.RowDataPythonScalarFunctionOperator.emitResult(RowDataPythonScalarFunctionOperator.java:81)
at org.apache.flink.streaming.api.operators.python.AbstractPythonFunctionOperator.emitResults(AbstractPythonFunctionOperator.java:250)
at org.apache.flink.streaming.api.operators.python.AbstractPythonFunctionOperator.invokeFinishBundle(AbstractPythonFunctionOperator.java:273)
at org.apache.flink.streaming.api.operators.python.AbstractPythonFunctionOperator.processWatermark(AbstractPythonFunctionOperator.java:199)
at org.apache.flink.streaming.runtime.tasks.ChainingOutput.emitWatermark(ChainingOutput.java:123)
at org.apache.flink.streaming.runtime.tasks.SourceOperatorStreamTask$AsyncDataOutputToOutput.emitWatermark(SourceOperatorStreamTask.java:170)
at org.apache.flink.streaming.runtime.tasks.SourceOperatorStreamTask.advanceToEndOfEventTime(SourceOperatorStreamTask.java:110)
at org.apache.flink.streaming.runtime.tasks.SourceOperatorStreamTask.afterInvoke(SourceOperatorStreamTask.java:116)
at org.apache.flink.streaming.runtime.tasks.StreamTask.invoke(StreamTask.java:589)
at org.apache.flink.runtime.taskmanager.Task.doRun(Task.java:755)
at org.apache.flink.runtime.taskmanager.Task.run(Task.java:570)
at java.lang.Thread.run(Thread.java:748)
{code}

As Python is dynamic language and so this is very common and we should provide a proper way to handle this case.



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