alink1.5.2 getOutputTable().to_pandas() raise ERROR

[ygean]

sample code as below:

input_users = [[617127], [4841758], [382730], [1399180]]
df_users = pd.DataFrame(input_users)
sdata = StreamOperator.fromDataframe(df_users, schemaStr='user bigint')
predictor = ItemCfItemsPerUserRecommStreamOp(model)\
    .setUserCol("user")\
    .setReservedCols(["user"])\
    .setK(3)\
    .setRecommCol("prediction_result");
b = predictor.linkFrom(sdata).getOutputTable()
StreamOperator.execute()
b.to_pandas()

Get ERROR:

---------------------------------------------------------------------------
Py4JJavaError                             Traceback (most recent call last)
Input In [37], in <module>
----> 1 b.to_pandas()

File ~/.local/lib/python3.8/site-packages/pyflink/table/table.py:998, in Table.to_pandas(self)
    995 gateway = get_gateway()
    996 max_arrow_batch_size = self._j_table.getTableEnvironment().getConfig().getConfiguration()\
    997     .getInteger(gateway.jvm.org.apache.flink.python.PythonOptions.MAX_ARROW_BATCH_SIZE)
--> 998 batches_iterator = gateway.jvm.org.apache.flink.table.runtime.arrow.ArrowUtils\
    999     .collectAsPandasDataFrame(self._j_table, max_arrow_batch_size)
   1000 if batches_iterator.hasNext():
   1001     import pytz

File ~/.local/lib/python3.8/site-packages/py4j/java_gateway.py:1285, in JavaMember.__call__(self, *args)
   1279 command = proto.CALL_COMMAND_NAME +\
   1280     self.command_header +\
   1281     args_command +\
   1282     proto.END_COMMAND_PART
   1284 answer = self.gateway_client.send_command(command)
-> 1285 return_value = get_return_value(
   1286     answer, self.gateway_client, self.target_id, self.name)
   1288 for temp_arg in temp_args:
   1289     temp_arg._detach()

File ~/.local/lib/python3.8/site-packages/py4j/protocol.py:326, in get_return_value(answer, gateway_client, target_id, name)
    324 value = OUTPUT_CONVERTER[type](answer[2:], gateway_client)
    325 if answer[1] == REFERENCE_TYPE:
--> 326     raise Py4JJavaError(
    327         "An error occurred while calling {0}{1}{2}.\n".
    328         format(target_id, ".", name), value)
    329 else:
    330     raise Py4JError(
    331         "An error occurred while calling {0}{1}{2}. Trace:\n{3}\n".
    332         format(target_id, ".", name, value))

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 LEGACY('RAW', 'ANY<com.alibaba.alink.common.MTable>') currently.
	at org.apache.flink.table.runtime.arrow.ArrowUtils$LogicalTypeToArrowTypeConverter.defaultMethod(ArrowUtils.java:947)
	at org.apache.flink.table.runtime.arrow.ArrowUtils$LogicalTypeToArrowTypeConverter.defaultMethod(ArrowUtils.java:821)
	at org.apache.flink.table.types.logical.utils.LogicalTypeDefaultVisitor.visit(LogicalTypeDefaultVisitor.java:202)
	at org.apache.flink.table.types.logical.LegacyTypeInformationType.accept(LegacyTypeInformationType.java:107)
	at org.apache.flink.table.runtime.arrow.ArrowUtils.toArrowField(ArrowUtils.java:227)
	at org.apache.flink.table.runtime.arrow.ArrowUtils.lambda$toArrowSchema$0(ArrowUtils.java:218)
	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:219)
	at org.apache.flink.table.runtime.arrow.ArrowUtils.collectAsPandasDataFrame(ArrowUtils.java:662)
	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 py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
	at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
	at py4j.Gateway.invoke(Gateway.java:282)
	at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
	at py4j.commands.CallCommand.execute(CallCommand.java:79)
	at py4j.GatewayConnection.run(GatewayConnection.java:238)
	at java.lang.Thread.run(Thread.java:748)

dependency list:
pandas==1.3.5

[ygean]

downgrade alink at 1.4.0 and reinstall pandas==1.1.5, it works.

[Fanoid]

Hi.
to_pandas is provided by PyFlink, not PyAlink.
From the error message, it seems to_pandas does not support Alink-defined types:
: java.lang.UnsupportedOperationException: Python vectorized UDF doesn't support logical type LEGACY('RAW', 'ANY<com.alibaba.alink.common.MTable>') currently.

In previous PyAlink version, this operator didn't use the Alink-defined type (MTable), so it worked.

[ygean]

@Fanoid Thanks.