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From João Peixoto <joao.harti...@gmail.com>
Subject Re: Kafka Stream stops polling new messages
Date Wed, 03 May 2017 15:16:28 GMT
Actually I need to apologize, I pasted the wrong issue, I meant to paste
https://github.com/facebook/rocksdb/issues/261.

RocksDB did not produce a crash report since it didn't actually crash. I
performed thread dumps on stale and not-stale instances which revealed the
common behavior and I collect and plot several Kafka metrics, including
"punctuate" durations, therefore I know it took a long time and eventually
finished.

Joao

On Wed, May 3, 2017 at 6:22 AM Eno Thereska <eno.thereska@gmail.com> wrote:

> Hi there,
>
> Thanks for double checking. Does RocksDB actually crash or produce a crash
> dump? I’m curious how you know that the issue is
> https://github.com/facebook/rocksdb/issues/1121 <
> https://github.com/facebook/rocksdb/issues/1121>, so just double checking
> with you.
>
> If that’s indeed the case, do you mind opening a JIRA (a copy-paste of the
> below should suffice)? Alternatively let us know and we’ll open it. Sounds
> like we should handle this better.
>
> Thanks,
> Eno
>
>
> > On May 3, 2017, at 5:49 AM, João Peixoto <joao.hartimer@gmail.com>
> wrote:
> >
> > I believe I found the root cause of my problem. I seem to have hit this
> > RocksDB bug https://github.com/facebook/rocksdb/issues/1121
> >
> > On my stream configuration I have a custom transformer used for
> > deduplicating records, highly inspired in the
> > EventDeduplicationLambdaIntegrationTest
> > <
> https://github.com/confluentinc/examples/blob/3.2.x/kafka-streams/src/test/java/io/confluent/examples/streams/EventDeduplicationLambdaIntegrationTest.java#L161
> >
> > but
> > adjusted to my use case, special emphasis on the "punctuate" method.
> >
> > All the stale instances had the main stream thread "RUNNING" the
> > "punctuate" method of this transformer, which in term was running RocksDB
> > "seekToFirst".
> >
> > Also during my debugging one such instance finished the "punctuate"
> method,
> > which took ~11h, exactly the time the instance was stuck for.
> > Changing the backing state store from "persistent" to "inMemory" solved
> my
> > issue, at least after several days running, no stuck instances.
> >
> > This leads me to ask, shouldn't Kafka detect such a situation fairly
> > quickly? Instead of just stopping polling? My guess is that the heartbeat
> > thread which now is separate continues working fine, since by definition
> > the stream runs a message through the whole pipeline this step probably
> > just looked like it was VERY slow. Not sure what the best approach here
> > would be.
> >
> > PS The linked code clearly states "This code is for demonstration
> purposes
> > and was not tested for production usage" so that's on me
> >
> > On Tue, May 2, 2017 at 11:20 AM Matthias J. Sax <matthias@confluent.io>
> > wrote:
> >
> >> Did you check the logs? Maybe you need to increase log level to DEBUG to
> >> get some more information.
> >>
> >> Did you double check committed offsets via bin/kafka-consumer-groups.sh?
> >>
> >> -Matthias
> >>
> >> On 4/28/17 9:22 AM, João Peixoto wrote:
> >>> My stream gets stale after a while and it simply does not receive any
> new
> >>> messages, aka does not poll.
> >>>
> >>> I'm using Kafka Streams 0.10.2.1 (same happens with 0.10.2.0) and the
> >>> brokers are running 0.10.1.1.
> >>>
> >>> The stream state is RUNNING and there are no exceptions in the logs.
> >>>
> >>> Looking at the JMX metrics, the threads are there and running, just not
> >>> doing anything.
> >>> The metric "consumer-coordinator-metrics > heartbeat-response-time-max"
> >>> (The max time taken to receive a response to a heartbeat request) reads
> >>> 43,361 seconds (almost 12 hours) which is consistent with the time of
> the
> >>> hang. Shouldn't this trigger a failure somehow?
> >>>
> >>> The stream configuration looks something like this:
> >>>
> >>> Properties props = new Properties();
> >>>    props.put(StreamsConfig.TIMESTAMP_EXTRACTOR_CLASS_CONFIG,
> >>>              CustomTimestampExtractor.class.getName());
> >>>    props.put(StreamsConfig.APPLICATION_ID_CONFIG, streamName);
> >>>    props.put(StreamsConfig.CLIENT_ID_CONFIG, streamName);
> >>>    props.put(StreamsConfig.BOOTSTRAP_SERVERS_CONFIG,
> >>> myConfig.getBrokerList());
> >>>    props.put(StreamsConfig.KEY_SERDE_CLASS_CONFIG,
> >>> Serdes.String().getClass().getName());
> >>>    props.put(StreamsConfig.VALUE_SERDE_CLASS_CONFIG,
> >>> Serdes.ByteArray().getClass().getName());
> >>>    props.put(StreamsConfig.COMMIT_INTERVAL_MS_CONFIG,
> >>> myConfig.getCommitIntervalMs()); // 5000
> >>>    props.put(StreamsConfig.METRICS_RECORDING_LEVEL_CONFIG, "DEBUG");
> >>>    props.put(StreamsConfig.NUM_STREAM_THREADS_CONFIG,
> >>> myConfig.getStreamThreadsCount()); // 1
> >>>    props.put(StreamsConfig.CACHE_MAX_BYTES_BUFFERING_CONFIG,
> >>> myConfig.getMaxCacheBytes()); // 524_288_000L
> >>>    props.put(ConsumerConfig.AUTO_OFFSET_RESET_CONFIG, "earliest");
> >>>    props.put(ConsumerConfig.MAX_POLL_RECORDS_CONFIG, 50);
> >>>
> >>> The stream LEFT JOINs 2 topics, one of them being a KTable, and outputs
> >> to
> >>> another topic.
> >>>
> >>> Thanks in advance for the help!
> >>>
> >>
> >>
>
>

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