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

["Sasaki Toru (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/SPARK-20050?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15938988#comment-15938988 ] 

Sasaki Toru edited comment on SPARK-20050 at 3/23/17 6:45 PM:
--------------------------------------------------------------

Thank you for your comment, but I can't understand your advice, sorry.

I want to say some offset set in {{commitAsync}} will not commit to Kafka.
I think callback function will be invoked when committed to Kafka completely (success or failed),
so I think this function will not be invoked in this case.

If I am wrong, please correct, thanks.


was (Author: sasakitoa):
Thank you for your comment, but I can't understand your advice, sorry.

I want to say some offset set in {{commitAsync}} will not commit to Kafka.
I think callback function will invoke when committed to Kafka completely (success or failed),
so I think this function will not be invoked in this case.

If I am wrong, please correct, thanks.

> 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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