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https://issues.apache.org/jira/browse/FLINK-28742?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Xingbo Huang reassigned FLINK-28742:
------------------------------------
Assignee: Xingbo Huang
> Table.to_pandas fails with lit("xxx")
> -------------------------------------
>
> Key: FLINK-28742
> URL: https://issues.apache.org/jira/browse/FLINK-28742
> Project: Flink
> Issue Type: Bug
> Components: API / Python
> Affects Versions: 1.15.1
> Reporter: Xuannan Su
> Assignee: Xingbo Huang
> Priority: Major
>
> Table.to_pandas method throws the following exception when the table contains
> lit("anyString").
>
> {code:none}
> py4j.protocol.Py4JJavaError: An error occurred while calling
> z:org.apache.flink.table.runtime.arrow.ArrowUtils.collectAsPandasDataFrame.
> : java.lang.UnsupportedOperationException: Python vectorized UDF doesn't
> support logical type CHAR(3) NOT NULL currently.
> at
> org.apache.flink.table.runtime.arrow.ArrowUtils$LogicalTypeToArrowTypeConverter.defaultMethod(ArrowUtils.java:743)
> at
> org.apache.flink.table.runtime.arrow.ArrowUtils$LogicalTypeToArrowTypeConverter.defaultMethod(ArrowUtils.java:617)
> at
> org.apache.flink.table.types.logical.utils.LogicalTypeDefaultVisitor.visit(LogicalTypeDefaultVisitor.java:62)
> at org.apache.flink.table.types.logical.CharType.accept(CharType.java:148)
> at
> org.apache.flink.table.runtime.arrow.ArrowUtils.toArrowField(ArrowUtils.java:189)
> at
> org.apache.flink.table.runtime.arrow.ArrowUtils.lambda$toArrowSchema$0(ArrowUtils.java:180)
> at
> java.util.stream.ReferencePipeline$3$1.accept(ReferencePipeline.java:193)
> at
> java.util.ArrayList$ArrayListSpliterator.forEachRemaining(ArrayList.java:1384)
> at java.util.stream.AbstractPipeline.copyInto(AbstractPipeline.java:482)
> at
> java.util.stream.AbstractPipeline.wrapAndCopyInto(AbstractPipeline.java:472)
> at
> java.util.stream.ReduceOps$ReduceOp.evaluateSequential(ReduceOps.java:708)
> at java.util.stream.AbstractPipeline.evaluate(AbstractPipeline.java:234)
> at java.util.stream.ReferencePipeline.collect(ReferencePipeline.java:566)
> at
> org.apache.flink.table.runtime.arrow.ArrowUtils.toArrowSchema(ArrowUtils.java:181)
> at
> org.apache.flink.table.runtime.arrow.ArrowUtils.collectAsPandasDataFrame(ArrowUtils.java:483)
> at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
> at
> sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
> at
> sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
> at java.lang.reflect.Method.invoke(Method.java:498)
> at
> org.apache.flink.api.python.shaded.py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
> at
> org.apache.flink.api.python.shaded.py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
> at
> org.apache.flink.api.python.shaded.py4j.Gateway.invoke(Gateway.java:282)
> at
> org.apache.flink.api.python.shaded.py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
> at
> org.apache.flink.api.python.shaded.py4j.commands.CallCommand.execute(CallCommand.java:79)
> at
> org.apache.flink.api.python.shaded.py4j.GatewayConnection.run(GatewayConnection.java:238)
> at java.lang.Thread.run(Thread.java:748)
> {code}
>
> The code to reproduce the problem
> {code:python}
> env = StreamExecutionEnvironment.get_execution_environment()
> t_env = StreamTableEnvironment.create(env)
> src_table = t_env.from_data_stream(
> env.from_collection([1, 2], type_info=BasicTypeInfo.INT_TYPE_INFO())
> )
> table = src_table.select(expr.lit("123"))
> # table.execute().print()
> print(table.to_pandas()){code}
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