Hi Robert, Thanks for the workaround. Unfortunately I think I found a bug in the code that controls the metrics logic.
Should Boolean.getBoolean be Boolean.valueOf instead? https://github.com/apache/flink/blob/81320c1c7ee98b9a663998df51cc4d5aa73d9b2a/flink-streaming-connectors/flink-connector-kafka-base/src/main/java/org/apache/flink/streaming/connectors/kafka/FlinkKafkaProducerBase.java#L192 Thanks! David On Fri, Jan 22, 2016 at 2:17 AM, Robert Metzger <rmetz...@apache.org> wrote: > Hi David, > > thank you for reporting the issue. I'll look into it. In the meantime, you > can set "flink.disable-metrics" to "true" in the properties. This way, you > disable the metrics. > I'll probably have to introduce something like a client id to > differentiate between the producers. > > Robert > > On Thu, Jan 21, 2016 at 11:51 PM, David Kim < > david....@braintreepayments.com> wrote: > >> Hi Robert! >> >> Thanks for reaching out. I ran into an issue and wasn't sure if this was >> due to a misconfiguration on my end of if this is a real bug. I have one >> DataStream and I'm sinking to two different kafka sinks. When the job >> starts, I run into this error: >> >> org.apache.flink.runtime.client.JobExecutionException: Job execution >> failed. >> at >> org.apache.flink.runtime.jobmanager.JobManager$$anonfun$handleMessage$1$$anonfun$applyOrElse$7.apply$mcV$sp(JobManager.scala:659) >> at >> org.apache.flink.runtime.jobmanager.JobManager$$anonfun$handleMessage$1$$anonfun$applyOrElse$7.apply(JobManager.scala:605) >> at >> org.apache.flink.runtime.jobmanager.JobManager$$anonfun$handleMessage$1$$anonfun$applyOrElse$7.apply(JobManager.scala:605) >> at >> scala.concurrent.impl.Future$PromiseCompletingRunnable.liftedTree1$1(Future.scala:24) >> at >> scala.concurrent.impl.Future$PromiseCompletingRunnable.run(Future.scala:24) >> at akka.dispatch.TaskInvocation.run(AbstractDispatcher.scala:41) >> at >> akka.dispatch.ForkJoinExecutorConfigurator$AkkaForkJoinTask.exec(AbstractDispatcher.scala:401) >> at scala.concurrent.forkjoin.ForkJoinTask.doExec(ForkJoinTask.java:260) >> at >> scala.concurrent.forkjoin.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:1339) >> at >> scala.concurrent.forkjoin.ForkJoinPool.runWorker(ForkJoinPool.java:1979) >> at >> scala.concurrent.forkjoin.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:107) >> Caused by: java.lang.UnsupportedOperationException: The accumulator >> 'producer-record-retry-rate' already exists and cannot be added. >> at >> org.apache.flink.api.common.functions.util.AbstractRuntimeUDFContext.addAccumulator(AbstractRuntimeUDFContext.java:121) >> at >> org.apache.flink.streaming.connectors.kafka.FlinkKafkaProducerBase.open(FlinkKafkaProducerBase.java:204) >> at >> org.apache.flink.api.common.functions.util.FunctionUtils.openFunction(FunctionUtils.java:36) >> at >> org.apache.flink.streaming.api.operators.AbstractUdfStreamOperator.open(AbstractUdfStreamOperator.java:89) >> at >> org.apache.flink.streaming.runtime.tasks.StreamTask.openAllOperators(StreamTask.java:305) >> at >> org.apache.flink.streaming.runtime.tasks.StreamTask.invoke(StreamTask.java:227) >> at org.apache.flink.runtime.taskmanager.Task.run(Task.java:567) >> at java.lang.Thread.run(Thread.java:745) >> >> >> The particular accumulator the exception is complains about changes, >> meaning it's not always 'producer-record-retry-rate' -- most likely due to >> the non-deterministic ordering of the collection. Any guidance appreciated! >> >> I'm using 1.0-SNAPSHOT and my two sinks are FlinkKafkaProducer08. >> >> The flink code looks something like this: >> >> >> val stream: DataStream[Foo] = ... >> >> val kafkaA = new FlinkKafkaProducer08[Foo]... >> >> val kafkaB = new FlinkKafkaProducer08[Foo]... >> >> >> stream >> .addSink(kafkaA) >> >> stream. >> .addSink(kafkaB) >> >> >> Thanks, >> David >> >> On Wed, Jan 20, 2016 at 1:34 PM, Robert Metzger <rmetz...@apache.org> >> wrote: >> >>> I've now merged the pull request. DeserializationSchema.isEndOfStream() >>> should now be evaluated correctly by the Kafka 0.9 and 0.8 connectors. >>> >>> Please let me know if the updated code has any issues. I'll fix the >>> issues asap. >>> >>> On Wed, Jan 13, 2016 at 5:06 PM, David Kim < >>> david....@braintreepayments.com> wrote: >>> >>>> Thanks Robert! I'll be keeping tabs on the PR. >>>> >>>> Cheers, >>>> David >>>> >>>> On Mon, Jan 11, 2016 at 4:04 PM, Robert Metzger <metrob...@gmail.com> >>>> wrote: >>>> >>>>> Hi David, >>>>> >>>>> In theory isEndOfStream() is absolutely the right way to go for >>>>> stopping data sources in Flink. >>>>> That its not working as expected is a bug. I have a pending pull >>>>> request for adding a Kafka 0.9 connector, which fixes this issue as well >>>>> (for all supported Kafka versions). >>>>> >>>>> Sorry for the inconvenience. If you want, you can check out the branch >>>>> of the PR and build Flink yourself to get the fix. >>>>> I hope that I can merge the connector to master this week, then, the >>>>> fix will be available in 1.0-SNAPSHOT as well. >>>>> >>>>> Regards, >>>>> Robert >>>>> >>>>> >>>>> >>>>> Sent from my iPhone >>>>> >>>>> On 11.01.2016, at 21:39, David Kim <david....@braintreepayments.com> >>>>> wrote: >>>>> >>>>> Hello all, >>>>> >>>>> I saw that DeserializationSchema has an API "isEndOfStream()". >>>>> >>>>> >>>>> https://github.com/apache/flink/blob/master/flink-streaming-java/src/main/java/org/apache/flink/streaming/util/serialization/DeserializationSchema.java >>>>> >>>>> Can *isEndOfStream* be utilized to somehow terminate a streaming >>>>> flink job? >>>>> >>>>> I was under the impression that if we return "true" we can control >>>>> when a stream can close. The use case I had in mind was controlling when >>>>> unit/integration tests would terminate a flink job. We can rely on the >>>>> fact >>>>> that a test/spec would know how many items it expects to consume and then >>>>> switch *isEndOfStream* to return true. >>>>> >>>>> Am I misunderstanding the intention for *isEndOfStream*? >>>>> >>>>> I also set a breakpoint on *isEndOfStream* and saw that it never was >>>>> hit when using "FlinkKafkaConsumer082" to pass in a DeserializationSchema >>>>> implementation. >>>>> >>>>> Currently testing on 1.0-SNAPSHOT. >>>>> >>>>> Cheers! >>>>> David >>>>> >>>>> >>>> >>>> >>>> -- >>>> Note: this information is confidential. It is prohibited to share, post >>>> online or otherwise publicize without Braintree's prior written consent. >>>> >>> >>> >> >> >> -- >> Note: this information is confidential. It is prohibited to share, post >> online or otherwise publicize without Braintree's prior written consent. >> > > -- Note: this information is confidential. It is prohibited to share, post online or otherwise publicize without Braintree's prior written consent.
