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From "Apache Spark (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 Thu, 15 Mar 2018 17:16:00 GMT

    [ https://issues.apache.org/jira/browse/SPARK-23685?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16400755#comment-16400755
] 

Apache Spark commented on SPARK-23685:
--------------------------------------

User 'sirishaSindri' has created a pull request for this issue:
https://github.com/apache/spark/pull/20836

> 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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