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Issue of Kafka Balancing at high load


Kafka consumer configuration / performance issuesCommitFailedException Commit cannot be completed since the group has already rebalanced and assigned the partitions to another memberKafka client can't receive messagesKafka010JsonTableSource will not auto commit kafka offset when checkpoint is disableKafka console consumer ERROR “Offset commit failed on partition”Spring Boot Kafka: Commit cannot be completed since the group has already rebalancedkafka Python - CommitFailedErrorWhat is negative effects of setting max.poll.interval.ms larger than request.timeout.ms in Kafka consumer configsApache Kafka clash between enable.auto.commit and session.timeout.msGetting Kafka Error while message processing













0















Using kafka version 2.11-0.11.0.3 to publish 10,000 messages (total size of all messages are 10MB), there will be 2 consumers (with same group-id) to consume the message as a parallel processing.
While consuming, same message was consumed by both the consumers.



Below errors/warning were throws by kafka




WARN: This member will leave the group because consumer poll timeout
has expired. This means 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 processing
messages. You can address this either by increasing
max.poll.interval.ms or by reducing the maximum size of batches
returned in poll() with max.poll.records.



INFO: Attempt to heartbeat failed since group is rebalancing



INFO: Sending LeaveGroup request to coordinator



WARN: Synchronous auto-commit of offsets
ingest-data-1=OffsetAndMetadataoffset=5506, leaderEpoch=null,
metadata='' failed: 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 max.poll.interval.ms or by reducing
the maximum size of batches returned in poll() with max.poll.records.




Below configurations were provided to kafka



server.properties



max.poll.interval.ms=30000
group.initial.rebalance.delay.ms=0
group.max.session.timeout.ms=120000
group.min.session.timeout.ms=6000


consumer.properties



session.timeout.ms=30000 
request.timeout.ms=40000


What should have changed to resolve the multiple consumptions?










share|improve this question




























    0















    Using kafka version 2.11-0.11.0.3 to publish 10,000 messages (total size of all messages are 10MB), there will be 2 consumers (with same group-id) to consume the message as a parallel processing.
    While consuming, same message was consumed by both the consumers.



    Below errors/warning were throws by kafka




    WARN: This member will leave the group because consumer poll timeout
    has expired. This means 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 processing
    messages. You can address this either by increasing
    max.poll.interval.ms or by reducing the maximum size of batches
    returned in poll() with max.poll.records.



    INFO: Attempt to heartbeat failed since group is rebalancing



    INFO: Sending LeaveGroup request to coordinator



    WARN: Synchronous auto-commit of offsets
    ingest-data-1=OffsetAndMetadataoffset=5506, leaderEpoch=null,
    metadata='' failed: 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 max.poll.interval.ms or by reducing
    the maximum size of batches returned in poll() with max.poll.records.




    Below configurations were provided to kafka



    server.properties



    max.poll.interval.ms=30000
    group.initial.rebalance.delay.ms=0
    group.max.session.timeout.ms=120000
    group.min.session.timeout.ms=6000


    consumer.properties



    session.timeout.ms=30000 
    request.timeout.ms=40000


    What should have changed to resolve the multiple consumptions?










    share|improve this question


























      0












      0








      0








      Using kafka version 2.11-0.11.0.3 to publish 10,000 messages (total size of all messages are 10MB), there will be 2 consumers (with same group-id) to consume the message as a parallel processing.
      While consuming, same message was consumed by both the consumers.



      Below errors/warning were throws by kafka




      WARN: This member will leave the group because consumer poll timeout
      has expired. This means 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 processing
      messages. You can address this either by increasing
      max.poll.interval.ms or by reducing the maximum size of batches
      returned in poll() with max.poll.records.



      INFO: Attempt to heartbeat failed since group is rebalancing



      INFO: Sending LeaveGroup request to coordinator



      WARN: Synchronous auto-commit of offsets
      ingest-data-1=OffsetAndMetadataoffset=5506, leaderEpoch=null,
      metadata='' failed: 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 max.poll.interval.ms or by reducing
      the maximum size of batches returned in poll() with max.poll.records.




      Below configurations were provided to kafka



      server.properties



      max.poll.interval.ms=30000
      group.initial.rebalance.delay.ms=0
      group.max.session.timeout.ms=120000
      group.min.session.timeout.ms=6000


      consumer.properties



      session.timeout.ms=30000 
      request.timeout.ms=40000


      What should have changed to resolve the multiple consumptions?










      share|improve this question
















      Using kafka version 2.11-0.11.0.3 to publish 10,000 messages (total size of all messages are 10MB), there will be 2 consumers (with same group-id) to consume the message as a parallel processing.
      While consuming, same message was consumed by both the consumers.



      Below errors/warning were throws by kafka




      WARN: This member will leave the group because consumer poll timeout
      has expired. This means 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 processing
      messages. You can address this either by increasing
      max.poll.interval.ms or by reducing the maximum size of batches
      returned in poll() with max.poll.records.



      INFO: Attempt to heartbeat failed since group is rebalancing



      INFO: Sending LeaveGroup request to coordinator



      WARN: Synchronous auto-commit of offsets
      ingest-data-1=OffsetAndMetadataoffset=5506, leaderEpoch=null,
      metadata='' failed: 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 max.poll.interval.ms or by reducing
      the maximum size of batches returned in poll() with max.poll.records.




      Below configurations were provided to kafka



      server.properties



      max.poll.interval.ms=30000
      group.initial.rebalance.delay.ms=0
      group.max.session.timeout.ms=120000
      group.min.session.timeout.ms=6000


      consumer.properties



      session.timeout.ms=30000 
      request.timeout.ms=40000


      What should have changed to resolve the multiple consumptions?







      apache-kafka






      share|improve this question















      share|improve this question













      share|improve this question




      share|improve this question








      edited yesterday







      Venkata Madhu

















      asked yesterday









      Venkata MadhuVenkata Madhu

      53




      53






















          1 Answer
          1






          active

          oldest

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          0














          Are your consumers in the same group? If yes you will have multiple consumption if a consumer leaves/dies/timeouts without having committed some messages it has processed.



          If all your messages are consumed by both consumers you probably have not set the same group id for them.



          More info:



          So you have set the same group id for all consumers, good. You are in the situation where the cluster/broker thinks that a consumer died and therefore rebalances the load to another one. This other one will start consuming where the last commit was done.



          So lets say consumer C_A read offsets up to 100 from partition P_1 then processed them then committed '100' then read offsets up to 200 then processed them but could not commit because the broker considered C_A as dead.



          The broker reassigns partition P_1 to consumer C_B which will start from the last commit for the group, which is 100, will read up to 200, process and commit 200.



          So your question is how to avoid that the consumer is considered as dead (I assume it is not dead)?



          The answer is already in the yellow WARN message in your question: you can tell your consumer to consume less messages (max.poll.records) in one poll to reduce the processing time between two polls to the broker AND/OR you can increase the max.poll.interval.ms telling the broker to wait longer before considering your consumer as dead...






          share|improve this answer

























          • The consumer are consuming under the same group-id (same was updated to the post) for the parallel consumption. Do you see any issue with the properties?

            – Venkata Madhu
            yesterday










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          1 Answer
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          1 Answer
          1






          active

          oldest

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          active

          oldest

          votes






          active

          oldest

          votes









          0














          Are your consumers in the same group? If yes you will have multiple consumption if a consumer leaves/dies/timeouts without having committed some messages it has processed.



          If all your messages are consumed by both consumers you probably have not set the same group id for them.



          More info:



          So you have set the same group id for all consumers, good. You are in the situation where the cluster/broker thinks that a consumer died and therefore rebalances the load to another one. This other one will start consuming where the last commit was done.



          So lets say consumer C_A read offsets up to 100 from partition P_1 then processed them then committed '100' then read offsets up to 200 then processed them but could not commit because the broker considered C_A as dead.



          The broker reassigns partition P_1 to consumer C_B which will start from the last commit for the group, which is 100, will read up to 200, process and commit 200.



          So your question is how to avoid that the consumer is considered as dead (I assume it is not dead)?



          The answer is already in the yellow WARN message in your question: you can tell your consumer to consume less messages (max.poll.records) in one poll to reduce the processing time between two polls to the broker AND/OR you can increase the max.poll.interval.ms telling the broker to wait longer before considering your consumer as dead...






          share|improve this answer

























          • The consumer are consuming under the same group-id (same was updated to the post) for the parallel consumption. Do you see any issue with the properties?

            – Venkata Madhu
            yesterday















          0














          Are your consumers in the same group? If yes you will have multiple consumption if a consumer leaves/dies/timeouts without having committed some messages it has processed.



          If all your messages are consumed by both consumers you probably have not set the same group id for them.



          More info:



          So you have set the same group id for all consumers, good. You are in the situation where the cluster/broker thinks that a consumer died and therefore rebalances the load to another one. This other one will start consuming where the last commit was done.



          So lets say consumer C_A read offsets up to 100 from partition P_1 then processed them then committed '100' then read offsets up to 200 then processed them but could not commit because the broker considered C_A as dead.



          The broker reassigns partition P_1 to consumer C_B which will start from the last commit for the group, which is 100, will read up to 200, process and commit 200.



          So your question is how to avoid that the consumer is considered as dead (I assume it is not dead)?



          The answer is already in the yellow WARN message in your question: you can tell your consumer to consume less messages (max.poll.records) in one poll to reduce the processing time between two polls to the broker AND/OR you can increase the max.poll.interval.ms telling the broker to wait longer before considering your consumer as dead...






          share|improve this answer

























          • The consumer are consuming under the same group-id (same was updated to the post) for the parallel consumption. Do you see any issue with the properties?

            – Venkata Madhu
            yesterday













          0












          0








          0







          Are your consumers in the same group? If yes you will have multiple consumption if a consumer leaves/dies/timeouts without having committed some messages it has processed.



          If all your messages are consumed by both consumers you probably have not set the same group id for them.



          More info:



          So you have set the same group id for all consumers, good. You are in the situation where the cluster/broker thinks that a consumer died and therefore rebalances the load to another one. This other one will start consuming where the last commit was done.



          So lets say consumer C_A read offsets up to 100 from partition P_1 then processed them then committed '100' then read offsets up to 200 then processed them but could not commit because the broker considered C_A as dead.



          The broker reassigns partition P_1 to consumer C_B which will start from the last commit for the group, which is 100, will read up to 200, process and commit 200.



          So your question is how to avoid that the consumer is considered as dead (I assume it is not dead)?



          The answer is already in the yellow WARN message in your question: you can tell your consumer to consume less messages (max.poll.records) in one poll to reduce the processing time between two polls to the broker AND/OR you can increase the max.poll.interval.ms telling the broker to wait longer before considering your consumer as dead...






          share|improve this answer















          Are your consumers in the same group? If yes you will have multiple consumption if a consumer leaves/dies/timeouts without having committed some messages it has processed.



          If all your messages are consumed by both consumers you probably have not set the same group id for them.



          More info:



          So you have set the same group id for all consumers, good. You are in the situation where the cluster/broker thinks that a consumer died and therefore rebalances the load to another one. This other one will start consuming where the last commit was done.



          So lets say consumer C_A read offsets up to 100 from partition P_1 then processed them then committed '100' then read offsets up to 200 then processed them but could not commit because the broker considered C_A as dead.



          The broker reassigns partition P_1 to consumer C_B which will start from the last commit for the group, which is 100, will read up to 200, process and commit 200.



          So your question is how to avoid that the consumer is considered as dead (I assume it is not dead)?



          The answer is already in the yellow WARN message in your question: you can tell your consumer to consume less messages (max.poll.records) in one poll to reduce the processing time between two polls to the broker AND/OR you can increase the max.poll.interval.ms telling the broker to wait longer before considering your consumer as dead...







          share|improve this answer














          share|improve this answer



          share|improve this answer








          edited yesterday

























          answered yesterday









          pgraspgras

          10.9k23142




          10.9k23142












          • The consumer are consuming under the same group-id (same was updated to the post) for the parallel consumption. Do you see any issue with the properties?

            – Venkata Madhu
            yesterday

















          • The consumer are consuming under the same group-id (same was updated to the post) for the parallel consumption. Do you see any issue with the properties?

            – Venkata Madhu
            yesterday
















          The consumer are consuming under the same group-id (same was updated to the post) for the parallel consumption. Do you see any issue with the properties?

          – Venkata Madhu
          yesterday





          The consumer are consuming under the same group-id (same was updated to the post) for the parallel consumption. Do you see any issue with the properties?

          – Venkata Madhu
          yesterday



















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