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Posted to issues@spark.apache.org by "Saisai Shao (JIRA)" <ji...@apache.org> on 2017/03/23 07:05:41 UTC

[jira] [Commented] (SPARK-20050) Kafka 0.10 DirectStream doesn't commit last processed batch's offset when graceful shutdown

    [ https://issues.apache.org/jira/browse/SPARK-20050?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15937845#comment-15937845 ] 

Saisai Shao commented on SPARK-20050:
-------------------------------------

I think you could register a commit callback function in {{commitAsync}}, this callback function will be invoked once offset is committed into Kafka, I think you could use this to know when to stop the application.

> Kafka 0.10 DirectStream doesn't commit last processed batch's offset when graceful shutdown
> -------------------------------------------------------------------------------------------
>
>                 Key: SPARK-20050
>                 URL: https://issues.apache.org/jira/browse/SPARK-20050
>             Project: Spark
>          Issue Type: Bug
>          Components: DStreams
>    Affects Versions: 2.2.0
>            Reporter: Sasaki Toru
>
> I use Kafka 0.10 DirectStream with properties 'enable.auto.commit=false' and call 'DirectKafkaInputDStream#commitAsync' finally in each batches,  such below
> {code}
> val kafkaStream = KafkaUtils.createDirectStream[String, String](...)
> kafkaStream.map { input =>
>   "key: " + input.key.toString + " value: " + input.value.toString + " offset: " + input.offset.toString
>   }.foreachRDD { rdd =>
>     rdd.foreach { input =>
>     println(input)
>   }
> }
> kafkaStream.foreachRDD { rdd =>
>   val offsetRanges = rdd.asInstanceOf[HasOffsetRanges].offsetRanges
>   kafkaStream.asInstanceOf[CanCommitOffsets].commitAsync(offsetRanges)
> }
> {\code}
> Some records which processed in the last batch before Streaming graceful shutdown reprocess in the first batch after Spark Streaming restart.
> It may cause offsets specified in commitAsync will commit in the head of next batch.



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