Sure. I have replied. Let’s discuss it in that thread.
> 2021年4月16日 上午11:40，Yik San Chan <evan.chanyik...@gmail.com> 写道：
>
> Hi Dian,
>
> Thank you so much for tracking the issue!
>
> I run into another NullPointerException when running pandas UDF, but this
> time I add an unit test to ensure the input and output type already ... And
> the new issue looks even more odd ... Do you mind taking a look?
> http://apache-flink-user-mailing-list-archive.2336050.n4.nabble.com/PyFlink-called-already-closed-and-NullPointerException-td42997.html
>
> <http://apache-flink-user-mailing-list-archive.2336050.n4.nabble.com/PyFlink-called-already-closed-and-NullPointerException-td42997.html>
>
> Thank you!
>
> Best,
> Yik San
>
> On Fri, Apr 16, 2021 at 11:05 AM Dian Fu <dian0511...@gmail.com
> <mailto:dian0511...@gmail.com>> wrote:
> Definitely agree with you. Have created
> https://issues.apache.org/jira/browse/FLINK-22297
> <https://issues.apache.org/jira/browse/FLINK-22297> as a following up.
>
>> 2021年4月16日 上午7:10，Yik San Chan <evan.chanyik...@gmail.com
>> <mailto:evan.chanyik...@gmail.com>> 写道：
>>
>> Hi Dian,
>>
>> I wonder if we can improve the error tracing and message so that it becomes
>> more obvious where the problem is? To me, a NPE really says very little.
>>
>> Best,
>> Yik San
>>
>> On Thu, Apr 15, 2021 at 11:07 AM Dian Fu <dian0511...@gmail.com
>> <mailto:dian0511...@gmail.com>> wrote:
>> Great! Thanks for letting me know~
>>
>>> 2021年4月15日 上午11:01，Yik San Chan <evan.chanyik...@gmail.com
>>> <mailto:evan.chanyik...@gmail.com>> 写道：
>>>
>>> Hi Dian,
>>>
>>> Thanks for the reminder. Yes, the original udf implementation does not
>>> qualify the input and output type requirement. After adding a unit test, I
>>> was able to find what's wrong, and fix my UDF implementation. Here is the
>>> new implementation FYI.
>>>
>>> @udf(result_type=DataTypes.DOUBLE(), func_type="pandas")
>>> def predict(users, items):
>>> n_users, n_items = 943, 1682
>>> model = MatrixFactorization(n_users, n_items)
>>> model.load_state_dict(torch.load("model.pth"))
>>> return pd.Series(model(users, items).detach().numpy())
>>>
>>> And here is the unit test.
>>>
>>> def test_predict():
>>> f = predict._func
>>> users = pd.Series([1, 2, 3])
>>> items = pd.Series([1, 4, 9])
>>> preds = f(users, items)
>>> assert isinstance(preds, pd.Series)
>>> assert len(preds) == 3
>>>
>>> Thank you so much!
>>>
>>> Best,
>>> Yik San
>>>
>>> On Wed, Apr 14, 2021 at 11:03 PM Dian Fu <dian0511...@gmail.com
>>> <mailto:dian0511...@gmail.com>> wrote:
>>> Hi Yik San,
>>>
>>> 1) There are two kinds of Python UDFs in PyFlink:
>>> - General Python UDFs which process input elements at row basis. That is,
>>> it will process one row at a time.
>>> - Pandas UDFs which process input elements at batch basis.
>>> So you are correct that you need to use Pandas UDF for your requirements.
>>>
>>> 2) For Pandas UDF, the input type for each input argument is Pandas.Series
>>> and the result type should also be a Pandas.Series. Besides, the length of
>>> the result should be the same as the inputs. Could you check if this is the
>>> case for your Pandas UDF implementation?
>>>
>>> Regards,
>>> Dian
>>>
>>>
>>> On Wed, Apr 14, 2021 at 9:44 PM Yik San Chan <evan.chanyik...@gmail.com
>>> <mailto:evan.chanyik...@gmail.com>> wrote:
>>> The question is cross-posted on Stack Overflow
>>> https://stackoverflow.com/questions/67092978/pyflink-vectorized-udf-throws-nullpointerexception
>>>
>>> <https://stackoverflow.com/questions/67092978/pyflink-vectorized-udf-throws-nullpointerexception>.
>>>
>>> I have a ML model that takes two numpy.ndarray - `users` and `items` - and
>>> returns an numpy.ndarray `predictions`. In normal Python code, I would do:
>>>
>>> ```python
>>> model = load_model()
>>>
>>> df = load_data() # the DataFrame includes 4 columns, namely, user_id,
>>> movie_id, rating, and timestamp
>>>
>>> users = df.user_id.values
>>> items = df.movie_id.values
>>>
>>> predictions = model(users, items)
>>> ```
>>>
>>> I am looking into porting this code into Flink to leverage its distributed
>>> nature. My assumption is: by distributing the prediction workload on
>>> multiple Flink nodes, I should be able to run the whole prediction faster.
>>>
>>> So I compose a PyFlink job. Note I implement an UDF called `predict` to run
>>> the prediction.
>>>
>>> ```python
>>> # batch_prediction.py
>>>
>>> model = load_model()
>>>
>>> settings = EnvironmentSettings.new_instance().use_blink_planner().build()
>>> exec_env = StreamExecutionEnvironment.get_execution_environment()
>>> t_env = StreamTableEnvironment.create(exec_env,
>>> environment_settings=settings)
>>>
>>> SOURCE_DDL = """
>>> CREATE TABLE source (
>>> user_id INT,
>>> movie_id INT,
>>> rating TINYINT,
>>> event_ms BIGINT
>>> ) WITH (
>>> 'connector' = 'filesystem',
>>> 'format' = 'csv',
>>> 'csv.field-delimiter' = '\t',
>>> 'path' = 'ml-100k/u1.test'
>>> )
>>> """
>>>
>>> SINK_DDL = """
>>> CREATE TABLE sink (
>>> prediction DOUBLE
>>> ) WITH (
>>> 'connector' = 'print'
>>> )
>>> """
>>>
>>> t_env.execute_sql(SOURCE_DDL)
>>> t_env.execute_sql(SINK_DDL)
>>> t_env.execute_sql(
>>> "INSERT INTO sink SELECT PREDICT(user_id, movie_id) FROM source"
>>> ).wait()
>>> ```
>>>
>>> Here is the UDF.
>>>
>>> ```python
>>> # batch_prediction.py (cont)
>>>
>>> @udf(result_type=DataTypes.DOUBLE())
>>> def predict(user, item):
>>> return model([user], [item]).item()
>>>
>>> t_env.create_temporary_function("predict", predict)
>>> ```
>>>
>>> The job runs fine. However, the prediction actually runs on each and every
>>> row of the `source` table, which is not performant. Instead, I want to
>>> split the 80,000 (user_id, movie_id) pairs into, let's say, 100 batches,
>>> with each batch having 800 rows. The job triggers the `model(users, items)`
>>> function 100 times (= # of batch), where both `users` and `items` have 800
>>> elements.
>>>
>>> I couldn't find a way to do this. By looking at the
>>> [docs](https://ci.apache.org/projects/flink/flink-docs-stable/dev/python/table-api-users-guide/udfs/vectorized_python_udfs.html
>>>
>>> <https://ci.apache.org/projects/flink/flink-docs-stable/dev/python/table-api-users-guide/udfs/vectorized_python_udfs.html>),
>>> vectorized user-defined functions may work.
>>>
>>> ```python
>>> # batch_prediction.py (snippet)
>>>
>>> # I add the func_type="pandas"
>>> @udf(result_type=DataTypes.DOUBLE(), func_type="pandas")
>>> def predict(user, item):
>>> ...
>>> ```
>>>
>>> Unfortunately, it doesn't.
>>>
>>> ```
>>> > python batch_prediction.py
>>> ...
>>> Traceback (most recent call last):
>>> File "batch_prediction.py", line 55, in <module>
>>> "INSERT INTO sink SELECT PREDICT(user_id, movie_id) FROM source"
>>> File
>>> "/usr/local/anaconda3/envs/flink-ml/lib/python3.7/site-packages/pyflink/table/table_result.py",
>>> line 76, in wait
>>> get_method(self._j_table_result, "await")()
>>> File
>>> "/usr/local/anaconda3/envs/flink-ml/lib/python3.7/site-packages/py4j/java_gateway.py",
>>> line 1286, in __call__
>>> answer, self.gateway_client, self.target_id, self.name
>>> <http://self.name/>)
>>> File
>>> "/usr/local/anaconda3/envs/flink-ml/lib/python3.7/site-packages/pyflink/util/exceptions.py",
>>> line 147, in deco
>>> return f(*a, **kw)
>>> File
>>> "/usr/local/anaconda3/envs/flink-ml/lib/python3.7/site-packages/py4j/protocol.py",
>>> line 328, in get_return_value
>>> format(target_id, ".", name), value)
>>> py4j.protocol.Py4JJavaError: An error occurred while calling o51.await.
>>> : java.util.concurrent.ExecutionException:
>>> org.apache.flink.table.api.TableException: Failed to wait job finish
>>> at
>>> java.util.concurrent.CompletableFuture.reportGet(CompletableFuture.java:357)
>>> at java.util.concurrent.CompletableFuture.get(CompletableFuture.java:1908)
>>> at
>>> org.apache.flink.table.api.internal.TableResultImpl.awaitInternal(TableResultImpl.java:119)
>>> at
>>> org.apache.flink.table.api.internal.TableResultImpl.await(TableResultImpl.java:86)
>>> 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)
>>> Caused by: org.apache.flink.table.api.TableException: Failed to wait job
>>> finish
>>> at
>>> org.apache.flink.table.api.internal.InsertResultIterator.hasNext(InsertResultIterator.java:59)
>>> at
>>> org.apache.flink.table.api.internal.TableResultImpl$CloseableRowIteratorWrapper.hasNext(TableResultImpl.java:355)
>>> at
>>> org.apache.flink.table.api.internal.TableResultImpl$CloseableRowIteratorWrapper.isFirstRowReady(TableResultImpl.java:368)
>>> at
>>> org.apache.flink.table.api.internal.TableResultImpl.lambda$awaitInternal$1(TableResultImpl.java:107)
>>> at
>>> java.util.concurrent.CompletableFuture$AsyncRun.run(CompletableFuture.java:1640)
>>> at
>>> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
>>> at
>>> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
>>> ... 1 more
>>> Caused by: java.util.concurrent.ExecutionException:
>>> org.apache.flink.runtime.client.JobExecutionException: Job execution failed.
>>> at
>>> java.util.concurrent.CompletableFuture.reportGet(CompletableFuture.java:357)
>>> at java.util.concurrent.CompletableFuture.get(CompletableFuture.java:1908)
>>> at
>>> org.apache.flink.table.api.internal.InsertResultIterator.hasNext(InsertResultIterator.java:57)
>>> ... 7 more
>>> Caused by: org.apache.flink.runtime.client.JobExecutionException: Job
>>> execution failed.
>>> at
>>> org.apache.flink.runtime.jobmaster.JobResult.toJobExecutionResult(JobResult.java:147)
>>> at
>>> org.apache.flink.runtime.minicluster.MiniClusterJobClient.lambda$getJobExecutionResult$2(MiniClusterJobClient.java:119)
>>> at
>>> java.util.concurrent.CompletableFuture.uniApply(CompletableFuture.java:616)
>>> at
>>> java.util.concurrent.CompletableFuture$UniApply.tryFire(CompletableFuture.java:591)
>>> at
>>> java.util.concurrent.CompletableFuture.postComplete(CompletableFuture.java:488)
>>> at
>>> java.util.concurrent.CompletableFuture.complete(CompletableFuture.java:1975)
>>> at
>>> org.apache.flink.runtime.rpc.akka.AkkaInvocationHandler.lambda$invokeRpc$0(AkkaInvocationHandler.java:229)
>>> at
>>> java.util.concurrent.CompletableFuture.uniWhenComplete(CompletableFuture.java:774)
>>> at
>>> java.util.concurrent.CompletableFuture$UniWhenComplete.tryFire(CompletableFuture.java:750)
>>> at
>>> java.util.concurrent.CompletableFuture.postComplete(CompletableFuture.java:488)
>>> at
>>> java.util.concurrent.CompletableFuture.complete(CompletableFuture.java:1975)
>>> at
>>> org.apache.flink.runtime.concurrent.FutureUtils$1.onComplete(FutureUtils.java:996)
>>> at akka.dispatch.OnComplete.internal(Future.scala:264)
>>> at akka.dispatch.OnComplete.internal(Future.scala:261)
>>> at akka.dispatch.japi$CallbackBridge.apply(Future.scala:191)
>>> at akka.dispatch.japi$CallbackBridge.apply(Future.scala:188)
>>> at scala.concurrent.impl.CallbackRunnable.run(Promise.scala:36)
>>> at
>>> org.apache.flink.runtime.concurrent.Executors$DirectExecutionContext.execute(Executors.java:74)
>>> at scala.concurrent.impl.CallbackRunnable.executeWithValue(Promise.scala:44)
>>> at
>>> scala.concurrent.impl.Promise$DefaultPromise.tryComplete(Promise.scala:252)
>>> at akka.pattern.PromiseActorRef.$bang(AskSupport.scala:572)
>>> at
>>> akka.pattern.PipeToSupport$PipeableFuture$$anonfun$pipeTo$1.applyOrElse(PipeToSupport.scala:22)
>>> at
>>> akka.pattern.PipeToSupport$PipeableFuture$$anonfun$pipeTo$1.applyOrElse(PipeToSupport.scala:21)
>>> at scala.concurrent.Future$$anonfun$andThen$1.apply(Future.scala:436)
>>> at scala.concurrent.Future$$anonfun$andThen$1.apply(Future.scala:435)
>>> at scala.concurrent.impl.CallbackRunnable.run(Promise.scala:36)
>>> at
>>> akka.dispatch.BatchingExecutor$AbstractBatch.processBatch(BatchingExecutor.scala:55)
>>> at
>>> akka.dispatch.BatchingExecutor$BlockableBatch$$anonfun$run$1.apply$mcV$sp(BatchingExecutor.scala:91)
>>> at
>>> akka.dispatch.BatchingExecutor$BlockableBatch$$anonfun$run$1.apply(BatchingExecutor.scala:91)
>>> at
>>> akka.dispatch.BatchingExecutor$BlockableBatch$$anonfun$run$1.apply(BatchingExecutor.scala:91)
>>> at scala.concurrent.BlockContext$.withBlockContext(BlockContext.scala:72)
>>> at
>>> akka.dispatch.BatchingExecutor$BlockableBatch.run(BatchingExecutor.scala:90)
>>> at akka.dispatch.TaskInvocation.run(AbstractDispatcher.scala:40)
>>> at
>>> akka.dispatch.ForkJoinExecutorConfigurator$AkkaForkJoinTask.exec(ForkJoinExecutorConfigurator.scala:44)
>>> at akka.dispatch.forkjoin.ForkJoinTask.doExec(ForkJoinTask.java:260)
>>> at
>>> akka.dispatch.forkjoin.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:1339)
>>> at akka.dispatch.forkjoin.ForkJoinPool.runWorker(ForkJoinPool.java:1979)
>>> at
>>> akka.dispatch.forkjoin.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:107)
>>> Caused by: org.apache.flink.runtime.JobException: Recovery is suppressed by
>>> NoRestartBackoffTimeStrategy
>>> at
>>> org.apache.flink.runtime.executiongraph.failover.flip1.ExecutionFailureHandler.handleFailure(ExecutionFailureHandler.java:116)
>>> at
>>> org.apache.flink.runtime.executiongraph.failover.flip1.ExecutionFailureHandler.getFailureHandlingResult(ExecutionFailureHandler.java:78)
>>> at
>>> org.apache.flink.runtime.scheduler.DefaultScheduler.handleTaskFailure(DefaultScheduler.java:224)
>>> at
>>> org.apache.flink.runtime.scheduler.DefaultScheduler.maybeHandleTaskFailure(DefaultScheduler.java:217)
>>> at
>>> org.apache.flink.runtime.scheduler.DefaultScheduler.updateTaskExecutionStateInternal(DefaultScheduler.java:208)
>>> at
>>> org.apache.flink.runtime.scheduler.SchedulerBase.updateTaskExecutionState(SchedulerBase.java:610)
>>> at
>>> org.apache.flink.runtime.scheduler.SchedulerNG.updateTaskExecutionState(SchedulerNG.java:89)
>>> at
>>> org.apache.flink.runtime.jobmaster.JobMaster.updateTaskExecutionState(JobMaster.java:419)
>>> 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.runtime.rpc.akka.AkkaRpcActor.handleRpcInvocation(AkkaRpcActor.java:286)
>>> at
>>> org.apache.flink.runtime.rpc.akka.AkkaRpcActor.handleRpcMessage(AkkaRpcActor.java:201)
>>> at
>>> org.apache.flink.runtime.rpc.akka.FencedAkkaRpcActor.handleRpcMessage(FencedAkkaRpcActor.java:74)
>>> at
>>> org.apache.flink.runtime.rpc.akka.AkkaRpcActor.handleMessage(AkkaRpcActor.java:154)
>>> at akka.japi.pf.UnitCaseStatement.apply(CaseStatements.scala:26)
>>> at akka.japi.pf.UnitCaseStatement.apply(CaseStatements.scala:21)
>>> at scala.PartialFunction$class.applyOrElse(PartialFunction.scala:123)
>>> at akka.japi.pf.UnitCaseStatement.applyOrElse(CaseStatements.scala:21)
>>> at scala.PartialFunction$OrElse.applyOrElse(PartialFunction.scala:170)
>>> at scala.PartialFunction$OrElse.applyOrElse(PartialFunction.scala:171)
>>> at scala.PartialFunction$OrElse.applyOrElse(PartialFunction.scala:171)
>>> at akka.actor.Actor$class.aroundReceive(Actor.scala:517)
>>> at akka.actor.AbstractActor.aroundReceive(AbstractActor.scala:225)
>>> at akka.actor.ActorCell.receiveMessage(ActorCell.scala:592)
>>> at akka.actor.ActorCell.invoke(ActorCell.scala:561)
>>> at akka.dispatch.Mailbox.processMailbox(Mailbox.scala:258)
>>> at akka.dispatch.Mailbox.run(Mailbox.scala:225)
>>> at akka.dispatch.Mailbox.exec(Mailbox.scala:235)
>>> ... 4 more
>>> Caused by: org.apache.flink.streaming.runtime.tasks.AsynchronousException:
>>> Caught exception while processing timer.
>>> at
>>> org.apache.flink.streaming.runtime.tasks.StreamTask$StreamTaskAsyncExceptionHandler.handleAsyncException(StreamTask.java:1108)
>>> at
>>> org.apache.flink.streaming.runtime.tasks.StreamTask.handleAsyncException(StreamTask.java:1082)
>>> at
>>> org.apache.flink.streaming.runtime.tasks.StreamTask.invokeProcessingTimeCallback(StreamTask.java:1213)
>>> at
>>> org.apache.flink.streaming.runtime.tasks.StreamTask.lambda$null$17(StreamTask.java:1202)
>>> at
>>> org.apache.flink.streaming.runtime.tasks.StreamTaskActionExecutor$SynchronizedStreamTaskActionExecutor.runThrowing(StreamTaskActionExecutor.java:92)
>>> at org.apache.flink.streaming.runtime.tasks.mailbox.Mail.run(Mail.java:78)
>>> at
>>> org.apache.flink.streaming.runtime.tasks.mailbox.MailboxExecutorImpl.tryYield(MailboxExecutorImpl.java:91)
>>> at
>>> org.apache.flink.streaming.runtime.tasks.StreamOperatorWrapper.quiesceTimeServiceAndCloseOperator(StreamOperatorWrapper.java:155)
>>> at
>>> org.apache.flink.streaming.runtime.tasks.StreamOperatorWrapper.close(StreamOperatorWrapper.java:130)
>>> at
>>> org.apache.flink.streaming.runtime.tasks.OperatorChain.closeOperators(OperatorChain.java:412)
>>> at
>>> org.apache.flink.streaming.runtime.tasks.StreamTask.afterInvoke(StreamTask.java:585)
>>> at
>>> org.apache.flink.streaming.runtime.tasks.StreamTask.invoke(StreamTask.java:547)
>>> at org.apache.flink.runtime.taskmanager.Task.doRun(Task.java:722)
>>> at org.apache.flink.runtime.taskmanager.Task.run(Task.java:547)
>>> at java.lang.Thread.run(Thread.java:748)
>>> Caused by: TimerException{java.lang.RuntimeException: Failed to close
>>> remote bundle}
>>> ... 13 more
>>> Caused by: java.lang.RuntimeException: Failed to close remote bundle
>>> at
>>> org.apache.flink.streaming.api.runners.python.beam.BeamPythonFunctionRunner.finishBundle(BeamPythonFunctionRunner.java:371)
>>> at
>>> org.apache.flink.streaming.api.runners.python.beam.BeamPythonFunctionRunner.flush(BeamPythonFunctionRunner.java:325)
>>> at
>>> org.apache.flink.streaming.api.operators.python.AbstractPythonFunctionOperator.invokeFinishBundle(AbstractPythonFunctionOperator.java:291)
>>> at
>>> org.apache.flink.table.runtime.operators.python.scalar.arrow.RowDataArrowPythonScalarFunctionOperator.invokeFinishBundle(RowDataArrowPythonScalarFunctionOperator.java:77)
>>> at
>>> org.apache.flink.streaming.api.operators.python.AbstractPythonFunctionOperator.checkInvokeFinishBundleByTime(AbstractPythonFunctionOperator.java:285)
>>> at
>>> org.apache.flink.streaming.api.operators.python.AbstractPythonFunctionOperator.lambda$open$0(AbstractPythonFunctionOperator.java:134)
>>> at
>>> org.apache.flink.streaming.runtime.tasks.StreamTask.invokeProcessingTimeCallback(StreamTask.java:1211)
>>> ... 12 more
>>> Caused by: java.lang.NullPointerException
>>> at
>>> org.apache.flink.streaming.api.runners.python.beam.BeamPythonFunctionRunner.finishBundle(BeamPythonFunctionRunner.java:369)
>>> ... 18 more
>>> ```
>>>
>>> The error messages are not very helpful. Can anyone help? Thanks!
>>>
>>> Note: source code can be found
>>> [here](https://github.com/YikSanChan/flink-torch/tree/83ea0510172db3d7ff33db19883150f2fe5c1f43
>>>
>>> <https://github.com/YikSanChan/flink-torch/tree/83ea0510172db3d7ff33db19883150f2fe5c1f43>).
>>> To run the code, you will need Anaconda locally, then:
>>>
>>> ```
>>> conda env create -f environment.yml
>>> conda activate flink-ml
>>> ```
>>>
>>> Best,
>>> Yik San
>>
>
