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From dev loper <spark...@gmail.com>
Subject Re: Kafka Streams application Unable to Horizontally scale and the application on other instances refusing to start.
Date Sat, 16 Sep 2017 15:21:02 GMT
Hi Ted,

 I will try out 0.11.0.1 version. Is there any upgrade which needs to be
done on kafka broker side as well ?

On Sat, Sep 16, 2017 at 5:18 AM, Ted Yu <yuzhihong@gmail.com> wrote:

> Hi,
> Were you using 0.11.0.0 ?
>
> I ask this because some related fixes, KAFKA-5167 and KAFKA-5152, are only
> in 0.11.0.1
>
> Mind trying out 0.11.0.1 release and see whether the problem persists ?
>
> On Fri, Sep 15, 2017 at 12:52 PM, Ted Yu <yuzhihong@gmail.com> wrote:
>
> > bq. 1)  Reduced  MAX_POLL_RECORDS_CONFIG to 5000  (previously 50000)
> >
> > Was there a typo ? (the two parameters in your email had the same name)
> >
> > Is it possible that you were hitting KAFKA-5397 ?
> >
> > On Fri, Sep 15, 2017 at 12:40 PM, dev loper <sparkemr@gmail.com> wrote:
> >
> >> Hi Damian,
> >>
> >> I have repeated my tests with slight configuration change. The current
> >> logs captured for "StreamThread"  keyword has more relevant logs when
> >> compared to logs which i shared previously. I started the application on
> >> instances 100,101 and 102 simultaneously with below configuration
> >>
> >> 1)  Reduced  MAX_POLL_RECORDS_CONFIG to 5000  (previously 50000)
> >>  2) Reduced MAX_POLL_RECORDS_CONFIG =60000 (Ipreviously nteger.MAXVALUE)
> >>
> >> When the application started all three instances started processing for
> >> first few minutes everything went well. After that I could see that
> >> "StreamThread100" error consumer was going for a toss and it started
> >> closing and creating the consumers for a while exactly with the pattern
> of
> >> logs I mentioned in my previous email and after some time I could see
> that
> >> " StreamThread100" stopped processing messages with below exception and
> the
> >> other two continued processing messages without any issues.
> >>
> >> org.apache.kafka.clients.consumer.CommitFailedException: Commit cannot
> >> be completed since the group has already rebalanced and assigned the
> >> partitions to another member. This means that the time between
> subsequent
> >> calls to poll() was longer than the configured max.poll.interval.ms,
> >> which typically implies that the poll loop is spending too much time
> >> message processing. You can address this either by increasing the
> session
> >> timeout or by reducing the maximum size of batches returned in poll()
> with
> >> max.poll.records.
> >>
> >> I think since the consumers were starting and stopping there was no poll
> >> made form the system . Since I reduced Reduced MAX_POLL_RECORDS_CONFIG
> >> =60000  and the processors were getting closed and started which might
> have
> >> resulted in the   "CommitFailedException due to non avialability of
> >> processing processors.
> >>
> >> After some time the issue got propagated to other servers, I have
> >> attached the relevant logs with this mail Kindly go through this and
> let me
> >> know how I can  solve this issue ?
> >>
> >>
> >>
> >>
> >> <https://mail.google.com/mail/?ui=2&ik=6aa5d30a60&view=att&
> th=15e8701650e040b7&attid=0.3&disp=safe&realattid=f_j7m9sld82&zw>
> >>
> >> On Fri, Sep 15, 2017 at 10:33 PM, dev loper <sparkemr@gmail.com> wrote:
> >>
> >>> Hi Ted,
> >>>
> >>> What should I be looking in broker logs ? I haven't looked at the
> broker
> >>> side since my spark application processing from the same topic with a
> >>> different group id is able to process well.
> >>>
> >>> On Fri, Sep 15, 2017 at 3:30 PM, Ted Yu <yuzhihong@gmail.com> wrote:
> >>>
> >>>> Is there some clue in broker logs ?
> >>>>
> >>>> Thanks
> >>>>
> >>>> On Thu, Sep 14, 2017 at 11:19 PM, dev loper <sparkemr@gmail.com>
> wrote:
> >>>>
> >>>>> Dear Kafka Users,
> >>>>>
> >>>>> I am fairly new to Kafka Streams . I have deployed two instances
of
> >>>>> Kafka 0.11 brokers on AWS M3.Xlarge insatnces. I have created a
> topic with
> >>>>> 36 partitions .and speperate application writes to this topic and
it
> >>>>> produces records at the rate of 10000 messages per second. I have
> threes
> >>>>> instances of AWS  M4.xlarge instance  where my Kafka streams
> application is
> >>>>> running which consumes these messages produced by the other
> application.
> >>>>> The application  starts up fine working fine and its processing
> messages on
> >>>>> the first instance,  but when I start the same application on other
> >>>>> instances it is not starting even though the process is alive it
is
> not
> >>>>> processing messages.Also I could see the other instances takes a
> long time
> >>>>> to start .
> >>>>>
> >>>>> Apart from first instance,  other instances I could see the consumer
> >>>>> getting added and removed repeatedly and I couldn't see any message
> >>>>> processing at all . I have attached the detailed logs where this
> behavior
> >>>>> is observed.
> >>>>>
> >>>>> Consumer is getting started with below log in these instances and
> >>>>> getting stopped with below log (* detailed logs attached *)
> >>>>>
> >>>>> INFO  | 21:59:30 | consumer.ConsumerConfig (AbstractConfig.java:223)
> -
> >>>>> ConsumerConfig values:
> >>>>>     auto.commit.interval.ms = 5000
> >>>>>     auto.offset.reset = latest
> >>>>>     bootstrap.servers = [l-mykafkainstancekafka5101:9092,
> >>>>> l-mykafkainstancekafka5102:9092]
> >>>>>     check.crcs = true
> >>>>>     client.id =
> >>>>>     connections.max.idle.ms = 540000
> >>>>>     enable.auto.commit = false
> >>>>>     exclude.internal.topics = true
> >>>>>     fetch.max.bytes = 52428800
> >>>>>     fetch.max.wait.ms = 500
> >>>>>     fetch.min.bytes = 1
> >>>>>     group.id = myKafka-kafkareplica101Sept08
> >>>>>     heartbeat.interval.ms = 3000
> >>>>>     interceptor.classes = null
> >>>>>     internal.leave.group.on.close = true
> >>>>>     isolation.level = read_uncommitted
> >>>>>     key.deserializer = class mx.july.jmx.proximity.kafka.Ka
> >>>>> fkaKryoCodec
> >>>>>     max.partition.fetch.bytes = 1048576
> >>>>>     max.poll.interval.ms = 300000
> >>>>>     max.poll.records = 500
> >>>>>     metadata.max.age.ms = 300000
> >>>>>     metric.reporters = []
> >>>>>     metrics.num.samples = 2
> >>>>>     metrics.recording.level = INFO
> >>>>>     metrics.sample.window.ms = 30000
> >>>>>     partition.assignment.strategy = [class
> >>>>> org.apache.kafka.clients.consumer.RangeAssignor]
> >>>>>     receive.buffer.bytes = 65536
> >>>>>     reconnect.backoff.max.ms = 1000
> >>>>>     reconnect.backoff.ms = 50
> >>>>>     request.timeout.ms = 305000
> >>>>>     retry.backoff.ms = 100
> >>>>>     sasl.jaas.config = null
> >>>>>     sasl.kerberos.kinit.cmd = /usr/bin/kinit
> >>>>>     sasl.kerberos.min.time.before.relogin = 60000
> >>>>>     sasl.kerberos.service.name = null
> >>>>>     sasl.kerberos.ticket.renew.jitter = 0.05
> >>>>>     sasl.kerberos.ticket.renew.window.factor = 0.8
> >>>>>     sasl.mechanism = GSSAPI
> >>>>>     security.protocol = PLAINTEXT
> >>>>>     send.buffer.bytes = 131072
> >>>>>     session.timeout.ms = 10000
> >>>>>     ssl.cipher.suites = null
> >>>>>     ssl.enabled.protocols = [TLSv1.2, TLSv1.1, TLSv1]
> >>>>>     ssl.endpoint.identification.algorithm = null
> >>>>>     ssl.key.password = null
> >>>>>     ssl.keymanager.algorithm = SunX509
> >>>>>     ssl.keystore.location = null
> >>>>>     ssl.keystore.password = null
> >>>>>     ssl.keystore.type = JKS
> >>>>>     ssl.protocol = TLS
> >>>>>     ssl.provider = null
> >>>>>     ssl.secure.random.implementation = null
> >>>>>     ssl.trustmanager.algorithm = PKIX
> >>>>>     ssl.truststore.location = null
> >>>>>     ssl.truststore.password = null
> >>>>>     ssl.truststore.type = JKS
> >>>>>     value.deserializer = class my.dev.MessageUpdateCodec
> >>>>>
> >>>>>
> >>>>> DEBUG | 21:59:30 | consumer.KafkaConsumer (KafkaConsumer.java:1617)
-
> >>>>> The Kafka consumer has closed. and the whole process repeats.
> >>>>>
> >>>>>
> >>>>>
> >>>>> Below you can find my startup code for kafkastreams and the
> parameters
> >>>>> which I have configured for starting the kafkastreams application
.
> >>>>>
> >>>>>         private static Properties settings = new Properties();
> >>>>>         settings.put(StreamsConfig.APPLICATION_ID_CONFIG,
> >>>>> "mykafkastreamsapplication");
> >>>>>         settings.put(ConsumerConfig.AUTO_OFFSET_RESET_CONFIG,"latest
> >>>>> ");
> >>>>>         settings.put(ConsumerConfig.HEARTBEAT_INTERVAL_MS_CONFIG,"10
> >>>>> 000");
> >>>>>         settings.put(ConsumerConfig.SESSION_TIMEOUT_MS_CONFIG,"30000
> >>>>> ");
> >>>>>         settings.put(ConsumerConfig.MAX_POLL_INTERVAL_MS_CONFIG,Inte
> >>>>> ger.MAX_VALUE);
> >>>>>         settings.put(ConsumerConfig.MAX_POLL_RECORDS_CONFIG,
> "10000");
> >>>>>         settings.put(ConsumerConfig.CONNECTIONS_MAX_IDLE_MS_CONFIG,"
> >>>>> 60000");
> >>>>>
> >>>>>         KStreamBuilder builder = new KStreamBuilder();
> >>>>>         KafkaStreams streams = new KafkaStreams(builder, settings);
> >>>>>         builder.addSource(.....
> >>>>>          .addProcessor  .............
> >>>>>          .addProcessor  ........
> >>>>>
> >>>>>          .addStateStore(...............
> ....).persistent().build(),"my
> >>>>> processor")
> >>>>>          .addSink ..............
> >>>>>          . addSink ..............
> >>>>>           streams.start();
> >>>>>
> >>>>> and I am using a Simple  processor to process my logic ..
> >>>>>
> >>>>> public class InfoProcessor extends AbstractProcessor<Key, Update>
{
> >>>>> private static Logger logger = Logger.getLogger(
> InfoProcessor.class);
> >>>>> private ProcessorContext context;
> >>>>> private KeyValueStore<Key, Info> infoStore;
> >>>>>
> >>>>> @Override
> >>>>> @SuppressWarnings("unchecked")
> >>>>> public void init(ProcessorContext context) {
> >>>>>     this.context = context;
> >>>>>     this.context.schedule(Constants.BATCH_DURATION_SECONDS * 1000);
> >>>>>     infoStore = (KeyValueStore<Key, Info>)
> >>>>> context.getStateStore("InfoStore");
> >>>>> }
> >>>>>
> >>>>> @Override
> >>>>> public void process(Key key, Update update) {
> >>>>>     try {
> >>>>>         if (key != null && update != null) {
> >>>>>             Info info = infoStore.get(key);
> >>>>>             // merge logic
> >>>>>             infoStore.put(key, info);
> >>>>>         }
> >>>>>
> >>>>>     } catch (Exception e) {
> >>>>>         logger.error(e.getMessage(), e);
> >>>>>     } finally {
> >>>>>     }
> >>>>>     context.commit();
> >>>>> }
> >>>>>
> >>>>> @Override
> >>>>> public void punctuate(long timestamp) {
> >>>>>     try {
> >>>>>         KeyValueIterator<Key, Info> iter = this.infoStore.all();
> >>>>>         while (iter.hasNext()) {
> >>>>>             // processing logic
> >>>>>
> >>>>>         }
> >>>>>         iter.close();
> >>>>>         context.commit();
> >>>>>     } catch (Exception e) {
> >>>>>         logger.error(e.getMessage(), e);
> >>>>>     }
> >>>>> }
> >>>>>
> >>>>>
> >>>>>
> >>>>>
> >>>>>
> >>>>
> >>>
> >>
> >
>

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