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From "Gabor Somogyi (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (SPARK-23685) Spark Structured Streaming Kafka 0.10 Consumer Can't Handle Non-consecutive Offsets (i.e. Log Compaction)
Date Fri, 23 Mar 2018 07:49:00 GMT

    [ https://issues.apache.org/jira/browse/SPARK-23685?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16410939#comment-16410939
] 

Gabor Somogyi commented on SPARK-23685:
---------------------------------------

Jira assignment is not required. You can write a comment when you're working on a jira but
your PR is not ready. Or a PR makes it also clear that you're dealing with it.

> Spark Structured Streaming Kafka 0.10 Consumer Can't Handle Non-consecutive Offsets (i.e.
Log Compaction)
> ---------------------------------------------------------------------------------------------------------
>
>                 Key: SPARK-23685
>                 URL: https://issues.apache.org/jira/browse/SPARK-23685
>             Project: Spark
>          Issue Type: Bug
>          Components: Structured Streaming
>    Affects Versions: 2.2.0
>            Reporter: sirisha
>            Priority: Major
>
> When Kafka does log compaction offsets often end up with gaps, meaning the next requested
offset will be frequently not be offset+1. The logic in KafkaSourceRDD & CachedKafkaConsumer assumes
that the next offset will always be just an increment of 1 .If not, it throws the below exception:
>  
> "Cannot fetch records in [5589, 5693) (GroupId: XXX, TopicPartition:XXXX). Some data
may have been lost because they are not available in Kafka any more; either the data was aged
out by Kafka or the topic may have been deleted before all the data in the topic was processed.
If you don't want your streaming query to fail on such cases, set the source option "failOnDataLoss"
to "false". "
>  
> FYI: This bug is related to https://issues.apache.org/jira/browse/SPARK-17147
>  
>  



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