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https://issues.apache.org/jira/browse/FLINK-11335?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16781360#comment-16781360
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Dawid Wysakowicz commented on FLINK-11335:
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Unfortunately the {{repeated.log}} is not very helpful it does not show when
was the checkpoint completed and if there were any exceptions in between.
Could you share full logs(not just a slices) showing the problem?
Some other suggestions what you could check:
* kafka offsets comitted to kafka (not via flink)
* connection between kafka and task manager nodes
* increase the checkpoint interval to see if it is not the case that committing
checkpoints take just too much time
I would also recommend posting this on the user mailling list, maybe somebody
had similar problem before. I really don't believe there is anything wrong with
Flink, but is rather a problem with some configuration of your environment. If
you still think there is some bug with Flink, could you provide us with some
minimal reproducible example, which we could use to verify this bug?
> Kafka consumer can not commit offset at checkpoint
> --------------------------------------------------
>
> Key: FLINK-11335
> URL: https://issues.apache.org/jira/browse/FLINK-11335
> Project: Flink
> Issue Type: Bug
> Components: Connectors / Kafka
> Affects Versions: 1.6.2
> Environment: AWS EMR 5.20: hadoop, flink plugin
> flink: 1.62
> run under yarn-cluster
> Kafka cluster: 1.0
>
> Reporter: andy hoang
> Priority: Critical
> Attachments: repeated.log
>
>
> When trying to commit offset to kafka, I always get warning
> {noformat}
> 2019-01-15 11:18:55,405 WARN
> org.apache.flink.streaming.connectors.kafka.internal.Kafka09Fetcher -
> Committing offsets to Kafka takes longer than the checkpoint interval.
> Skipping commit of previous offsets because newer complete checkpoint offsets
> are available. This does not compromise Flink's checkpoint integrity.
> {noformat}
> The result is not commiting any message to kafka
> The code was simplified be remove business
> {code:java}
> val env = StreamExecutionEnvironment.getExecutionEnvironment
> env.setStateBackend(new FsStateBackend("s3://pp-andy-test/checkpoint"))
> env.enableCheckpointing(6000, CheckpointingMode.AT_LEAST_ONCE)
> env.getCheckpointConfig.setCheckpointingMode(CheckpointingMode.AT_LEAST_ONCE)
> env.getCheckpointConfig.setMinPauseBetweenCheckpoints(500)
> env.getCheckpointConfig.setMaxConcurrentCheckpoints(1)
>
> env.getCheckpointConfig.enableExternalizedCheckpoints(ExternalizedCheckpointCleanup.RETAIN_ON_CANCELLATION)
> val properties = new Properties()
> properties.setProperty("group.id", "my_groupid")
> //properties.setProperty("enable.auto.commit", "false")
> val consumer = new FlinkKafkaConsumer011[ObjectNode]("my_topic",
> new JSONKeyValueDeserializationSchema(true),
>
> properties).setStartFromGroupOffsets().setCommitOffsetsOnCheckpoints(true)
> val stream = env.addSource(consumer)
>
> stream.map(new MapFunction[ObjectNode, Either[(Exception, ObjectNode),
> (Int, ujson.Value)]] {
> override def map(node:ObjectNode): scala.Either[(Exception,
> ObjectNode), (Int, ujson.Value)] = {
> logger.info("##################
> %s".format(node.get("metadata").toString))
> Thread.sleep(3000)
> return Right(200, writeJs(node.toString))
> }
> }).print()
> env.execute("pp_convoy_flink")
> }
> {code}
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