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 <[email protected]> wrote: > Great! Thanks for letting me know~ > > 2021年4月15日 上午11:01，Yik San Chan <[email protected]> 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 <[email protected]> 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 <[email protected]> >> 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 >>> >> >
