Thank you very much, Gordon. I'll try to run the job without the asynchronous snapshots first thing.
As for the Event data type: it's a case class with 2 fields: a String ID and a composite case class (let's call it RealEvent) containing 3 fields of the following types: Information, which is a case class with String fields, Coordinates, a nested case class with 2 Double and InstantValues, with 3 Integers and a DateTime.This DateTime field in InstantValues is the one being evalued in the maxBy (via InstantValues and RealEvent compareTo implementations, because dot notation is not working in scala as of 1.3.2, FLINK-7629 <https://issues.apache.org/jira/browse/FLINK-7629>) and that was the reason in the first place I had to register the JodaDateTimeSerializer with Kryo. Regards, Federico 2017-09-30 18:08 GMT+02:00 Tzu-Li (Gordon) Tai <tzuli...@apache.org>: > Hi, > > Thanks for the extra info, it was helpful (I’m not sure why your first > logs didn’t have the full trace, though). > > I spent some time digging through the error trace, and currently have some > observations I would like to go through first: > > 1. So it seems like the ArrayIndexOutOfBoundsException was thrown while > trying to access the state and making a copy (via serialization) in the > CopyOnWriteStateTable. > 2. The state that caused the exception seems to be the state of the > reducing window function (i.e. the maxBy). The state type should be the > same as the records in your `events` DataStream, which seems to be a Scala > case class with some nested field that requires Kryo for serialization. > 3. Somehow Kryo failed with the ArrayIndexOutOfBoundsException when trying > to copy that field .. > > My current guess would perhaps be that the serializer internally used may > have been incorrectly shared, which is probably why this exception happens > randomly for you. > I recall that there were similar issues that occurred before due to the > fact that some KryoSerializers aren't thread-safe and was incorrectly > shared in Flink. > > I may need some help from you to be able to look at this a bit more: > - Is it possible that you disable asynchronous snapshots and try running > this job a bit more to see if the problem still occurs? This is mainly to > eliminate my guess on whether or not there is some incorrect serializer > usage in the CopyOnWriteStateTable. > - Could you let us know what your `events` DataStream records type case > class looks like? > > Also looping in Aljoscha and Stefan here, as they would probably have more > insights in this. > > Cheers, > Gordon > > On 30 September 2017 at 10:56:33 AM, Federico D'Ambrosio ( > federico.dambro...@smartlab.ws) wrote: > > Hi Gordon, > > I remembered that I had already seen this kind of exception once during > the testing of the current job and fortunately I had the complete > stacktrace still saved on my pc: > > Caused by: java.lang.ArrayIndexOutOfBoundsException: -1 > at com.esotericsoftware.kryo.util.IntArray.pop(IntArray.java:157) > at com.esotericsoftware.kryo.Kryo.reference(Kryo.java:822) > at com.esotericsoftware.kryo.Kryo.copy(Kryo.java:863) > at org.apache.flink.api.java.typeutils.runtime.kryo. > KryoSerializer.copy(KryoSerializer.java:176) > at org.apache.flink.api.scala.typeutils.CaseClassSerializer. > copy(CaseClassSerializer.scala:101) > at org.apache.flink.api.scala.typeutils.CaseClassSerializer. > copy(CaseClassSerializer.scala:32) > at org.apache.flink.api.scala.typeutils.CaseClassSerializer. > copy(CaseClassSerializer.scala:101) > at org.apache.flink.api.scala.typeutils.CaseClassSerializer. > copy(CaseClassSerializer.scala:32) > at org.apache.flink.runtime.state.heap.CopyOnWriteStateTable.get( > CopyOnWriteStateTable.java:279) > at org.apache.flink.runtime.state.heap.CopyOnWriteStateTable.get( > CopyOnWriteStateTable.java:296) > at org.apache.flink.runtime.state.heap.HeapReducingState. > get(HeapReducingState.java:68) > at org.apache.flink.streaming.runtime.operators.windowing. > WindowOperator.onEventTime(WindowOperator.java:498) > at org.apache.flink.streaming.api.operators. > HeapInternalTimerService.advanceWatermark(HeapInternalTimerService.java: > 275) > at org.apache.flink.streaming.api.operators. > InternalTimeServiceManager.advanceWatermark(InternalTimeServiceManager. > java:107) > at org.apache.flink.streaming.api.operators. > AbstractStreamOperator.processWatermark(AbstractStreamOperator.java:946) > at org.apache.flink.streaming.runtime.io.StreamInputProcessor$ > ForwardingValveOutputHandler.handleWatermark( > StreamInputProcessor.java:286) > at org.apache.flink.streaming.runtime.io.StreamInputProcessor$ > ForwardingValveOutputHandler.handleWatermark( > StreamInputProcessor.java:289) > at org.apache.flink.streaming.runtime.streamstatus. > StatusWatermarkValve.findAndOutputNewMinWatermarkAcrossAlignedChannels( > StatusWatermarkValve.java:173) > at org.apache.flink.streaming.runtime.streamstatus. > StatusWatermarkValve.inputWatermark(StatusWatermarkValve.java:108) > at org.apache.flink.streaming.runtime.io.StreamInputProcessor. > processInput(StreamInputProcessor.java:188) > at org.apache.flink.streaming.runtime.tasks. > OneInputStreamTask.run(OneInputStreamTask.java:69) > at org.apache.flink.streaming.runtime.tasks.StreamTask. > invoke(StreamTask.java:263) > at org.apache.flink.runtime.taskmanager.Task.run(Task.java:702) > at java.lang.Thread.run(Thread.java:748) > > I don't know why now the stacktrace is getting output only for the first > parts (handleWatermark and HeapReducingState). > > So, it looks like something that has to do with the KryoSerializer. As a > KryoSerializer I'm using JodaDateTimeSerializer, registered as follows: > > env.getConfig.addDefaultKryoSerializer(classOf[DateTime], classOf[ > JodaDateTimeSerializer]) > > I hope this could help. > > Regards, > Federico > > 2017-09-29 15:54 GMT+02:00 Federico D'Ambrosio < > federico.dambro...@smartlab.ws>: > >> Hi Gordon, >> >> I'm currently using Flink 1.3.2 in local mode. >> >> If it's any help I realized from the log that the complete task which is >> failing is: >> >> 2017-09-29 14:17:20,354 INFO org.apache.flink.runtime.taskm >> anager.Task - latest_time -> (map_active_stream, >> map_history_stream) (1/1) (5a6c9f187326f678701f939665db6685) switched >> from RUNNING to FAILED. >> >> val events = keyedStreamByID >> .window(TumblingEventTimeWindows.of(Time.seconds(20))) >> .maxBy("time").name("latest_time").uid("latest_time") >> >> >> val activeStream = events >> //Serialization to JsValue >> .map(event => event.toMongoActiveJsValue).na >> me("map_active_stream").uid("map_active_stream") >> //Global windowing, the cause of exception should be above >> .timeWindowAll(Time.seconds(10)) >> .apply(new MongoWindow(MongoWritingType.UPDATE)).name("active_stream_wi >> ndow").uid("active_stream_window") >> >> val historyStream = airtrafficEvents >> //Serialization to JsValue >> .map(event => event.toMongoHistoryJsValue).n >> ame("map_history_stream").uid("map_history_stream") >> //Global windowing, the cause of exception should be above >> .timeWindowAll(Time.seconds(10)) >> .apply(new MongoWindow(MongoWritingType.UPDATE)).name("history_stream_w >> indow").uid("history_stream_window") >> >> >> >> Regards, >> Federico >> >> 2017-09-29 15:38 GMT+02:00 Tzu-Li (Gordon) Tai <tzuli...@apache.org>: >> >>> Hi, >>> >>> I’m looking into this. Could you let us know the Flink version in which >>> the exceptions occurred? >>> >>> Cheers, >>> Gordon >>> >>> >>> On 29 September 2017 at 3:11:30 PM, Federico D'Ambrosio ( >>> federico.dambro...@smartlab.ws) wrote: >>> >>> Hi, I'm coming across these Exceptions while running a pretty simple flink >>> job. >>> >>> First one: >>> java.lang.RuntimeException: Exception occurred while processing valve >>> output watermark: >>> at >>> org.apache.flink.streaming.runtime.io.StreamInputProcessor$ForwardingValveOutputHandler.handleWatermark(StreamInputProcessor.java:289) >>> at >>> org.apache.flink.streaming.runtime.streamstatus.StatusWatermarkValve.findAndOutputNewMinWatermarkAcrossAlignedChannels(StatusWatermarkValve.java:173) >>> at >>> org.apache.flink.streaming.runtime.streamstatus.StatusWatermarkValve.inputWatermark(StatusWatermarkValve.java:108) >>> at >>> org.apache.flink.streaming.runtime.io.StreamInputProcessor.processInput(StreamInputProcessor.java:188) >>> at >>> org.apache.flink.streaming.runtime.tasks.OneInputStreamTask.run(OneInputStreamTask.java:69) >>> at >>> org.apache.flink.streaming.runtime.tasks.StreamTask.invoke(StreamTask.java:263) >>> at org.apache.flink.runtime.taskmanager.Task.run(Task.java:702) >>> at java.lang.Thread.run(Thread.java:748) >>> Caused by: java.lang.ArrayIndexOutOfBoundsException >>> >>> The second one: >>> java.io.IOException: Exception while applying ReduceFunction in reducing >>> state >>> at >>> org.apache.flink.runtime.state.heap.HeapReducingState.add(HeapReducingState.java:82) >>> at >>> org.apache.flink.streaming.runtime.operators.windowing.WindowOperator.processElement(WindowOperator.java:442) >>> at >>> org.apache.flink.streaming.runtime.io.StreamInputProcessor.processInput(StreamInputProcessor.java:206) >>> at >>> org.apache.flink.streaming.runtime.tasks.OneInputStreamTask.run(OneInputStreamTask.java:69) >>> at >>> org.apache.flink.streaming.runtime.tasks.StreamTask.invoke(StreamTask.java:263) >>> at org.apache.flink.runtime.taskmanager.Task.run(Task.java:702) >>> at java.lang.Thread.run(Thread.java:748) >>> Caused by: java.lang.ArrayIndexOutOfBoundsException >>> >>> >>> Since it looks like something is wrong in Watermark processing, in my case >>> Watermarks are generated in my KafkaSource: >>> >>> val stream = env.addSource( >>> new FlinkKafkaConsumer010[Event](topic, new JSONDeserializationSchema(), >>> consumerConfig) >>> .setStartFromLatest() >>> .assignTimestampsAndWatermarks( >>> new BoundedOutOfOrdernessTimestampExtractor[Event](Time.seconds(10)) { >>> def extractTimestamp(element: AirTrafficEvent): Long = >>> element.instantValues.time.getMillis >>> }) >>> ) >>> >>> These exceptions aren't really that informative per se and, from what I >>> see, the task triggering these exceptions is the following operator: >>> >>> val events = keyedStreamByID >>> .window(TumblingEventTimeWindows.of(Time.seconds(20))) >>> .maxBy("timestamp").name("latest_time").uid("latest_time") >>> >>> What could be the problem here in your opinion? It's not emitting >>> watermarks correctly? I'm not even how I could reproduce this exceptions, >>> since it looks like they happen pretty much randomly. >>> >>> Thank you all, >>> Federico D'Ambrosio >>> >>> >> >> >> -- >> Federico D'Ambrosio >> > > > > -- > Federico D'Ambrosio > > -- Federico D'Ambrosio
