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https://issues.apache.org/jira/browse/SPARK-32962?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Amit Menashe updated SPARK-32962:
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Priority: Trivial (was: Major)
> Spark Streaming
> ---------------
>
> Key: SPARK-32962
> URL: https://issues.apache.org/jira/browse/SPARK-32962
> Project: Spark
> Issue Type: Bug
> Components: DStreams
> Affects Versions: 2.4.5
> Reporter: Amit Menashe
> Priority: Trivial
>
> Hey there,
> I'm using this spark streaming job which integrated with Kafka (and manage
> its offsets commitions at Kafka itself),
> The problem is when I have a failure I want to repeat the work on those
> offset ranges (that something went wrong with them) , therefore I catch the
> exception and NOT commit (with commitAsync) this range.
> However I notice it keeps proceeding (without any commit made).
> moreover I removed later all the commitAsync calls and I the stream keep
> proceeding!
> I guess there might be any inner cache or something that helps the streaming
> job to consume the entries from Kafka.
>
> Could you please advice?
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