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 Thank you! Best, Yik San On Fri, Apr 16, 2021 at 11:05 AM Dian Fu <dian0511...@gmail.com> wrote: > Definitely agree with you. Have created > 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> 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> wrote: > >> Great! Thanks for letting me know~ >> >> 2021年4月15日 上午11:01，Yik San Chan <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> 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> >>> wrote: >>> >>>> The question is cross-posted on Stack Overflow >>>> 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), >>>> 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) >>>> 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). >>>> To run the code, you will need Anaconda locally, then: >>>> >>>> ``` >>>> conda env create -f environment.yml >>>> conda activate flink-ml >>>> ``` >>>> >>>> Best, >>>> Yik San >>>> >>> >> >
