Question

我正在使用kafka连接器汇合3.0.1版本。我创建了一个名为 new-group 的新组，其中大约有20个主题。这些主题中的大部分都很忙。但它是一个遗憾的是，当我启动连接器框架时，系统无法停止重新平衡，所有主题的重新平衡约为2分钟。我不知道原因。一些错误消息是：

[2017-01-03 21:43:57,718] ERROR Commit of WorkerSinkTask{id=new-connector-0} offsets threw an unexpected exception:  (org.apache.kafka.connect.runtime.WorkerSinkTask:180)
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 session.timeout.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.
        at org.apache.kafka.clients.consumer.internals.ConsumerCoordinator$OffsetCommitResponseHandler.handle(ConsumerCoordinator.java:578)
        at org.apache.kafka.clients.consumer.internals.ConsumerCoordinator$OffsetCommitResponseHandler.handle(ConsumerCoordinator.java:519)
        at org.apache.kafka.clients.consumer.internals.AbstractCoordinator$CoordinatorResponseHandler.onSuccess(AbstractCoordinator.java:679)
        at org.apache.kafka.clients.consumer.internals.AbstractCoordinator$CoordinatorResponseHandler.onSuccess(AbstractCoordinator.java:658)
        at org.apache.kafka.clients.consumer.internals.RequestFuture$1.onSuccess(RequestFuture.java:167)
        at org.apache.kafka.clients.consumer.internals.RequestFuture.fireSuccess(RequestFuture.java:133)
        at org.apache.kafka.clients.consumer.internals.RequestFuture.complete(RequestFuture.java:107)
        at org.apache.kafka.clients.consumer.internals.ConsumerNetworkClient$RequestFutureCompletionHandler.onComplete(ConsumerNetworkClient.java:426)
        at org.apache.kafka.clients.NetworkClient.poll(NetworkClient.java:278)
        at org.apache.kafka.clients.consumer.internals.ConsumerNetworkClient.clientPoll(ConsumerNetworkClient.java:360)
        at org.apache.kafka.clients.consumer.internals.ConsumerNetworkClient.poll(ConsumerNetworkClient.java:224)
        at org.apache.kafka.clients.consumer.internals.ConsumerNetworkClient.poll(ConsumerNetworkClient.java:192)
        at org.apache.kafka.clients.consumer.internals.ConsumerNetworkClient.poll(ConsumerNetworkClient.java:163)
        at org.apache.kafka.clients.consumer.internals.ConsumerCoordinator.commitOffsetsSync(ConsumerCoordinator.java:404)
        at org.apache.kafka.clients.consumer.KafkaConsumer.commitSync(KafkaConsumer.java:1058)
        at org.apache.kafka.connect.runtime.WorkerSinkTask.doCommit(WorkerSinkTask.java:247)
        at org.apache.kafka.connect.runtime.WorkerSinkTask.commitOffsets(WorkerSinkTask.java:293)
        at org.apache.kafka.connect.runtime.WorkerSinkTask.closePartitions(WorkerSinkTask.java:421)
        at org.apache.kafka.connect.runtime.WorkerSinkTask.access$1100(WorkerSinkTask.java:54)
        at org.apache.kafka.connect.runtime.WorkerSinkTask$HandleRebalance.onPartitionsRevoked(WorkerSinkTask.java:465)
        at org.apache.kafka.clients.consumer.internals.ConsumerCoordinator.onJoinPrepare(ConsumerCoordinator.java:283)
        at org.apache.kafka.clients.consumer.internals.AbstractCoordinator.ensureActiveGroup(AbstractCoordinator.java:212)
        at org.apache.kafka.clients.consumer.internals.ConsumerCoordinator.ensurePartitionAssignment(ConsumerCoordinator.java:345)
        at org.apache.kafka.clients.consumer.KafkaConsumer.pollOnce(KafkaConsumer.java:977)
        at org.apache.kafka.clients.consumer.KafkaConsumer.poll(KafkaConsumer.java:937)
        at org.apache.kafka.connect.runtime.WorkerSinkTask.pollConsumer(WorkerSinkTask.java:305)
        at org.apache.kafka.connect.runtime.WorkerSinkTask.poll(WorkerSinkTask.java:222)
        at org.apache.kafka.connect.runtime.WorkerSinkTask.iteration(WorkerSinkTask.java:170)
        at org.apache.kafka.connect.runtime.WorkerSinkTask.execute(WorkerSinkTask.java:142)
        at org.apache.kafka.connect.runtime.WorkerTask.doRun(WorkerTask.java:140)
        at org.apache.kafka.connect.runtime.WorkerTask.run(WorkerTask.java:175)
        at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)
        at java.util.concurrent.FutureTask.run(FutureTask.java:266)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
:

我不知道它是否与持续的再平衡有关。

我知道如果KafkaConsumer.poll（）比配置的超时长，kafka将撤销分区，从而触发重新平衡，但我很确定每次轮询都不会那么长。有谁可以给我一些线索？

Answer 1

我认为max.poll.records可以解决这个问题。它是调整每次循环迭代必须处理的记录数。在0.10中有max.poll.records，它为每次调用返回的记录数设置上限。

同样根据Confluent，consumer.poll（）应具有相当高的会话超时，例如30到60秒。

您可能还想微调：

session.timeout.ms
heartbeat.interval.ms 
max.partition.fetch.bytes

Kafka连接器 - 无法停止重新平衡

1 个答案: