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https://issues.apache.org/jira/browse/SPARK-38445?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Martin Andersson resolved SPARK-38445.
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Resolution: Resolved
Closing this since it's inactive and looks resolved in the linked issue.
> Are hadoop committers used in Structured Streaming?
> ---------------------------------------------------
>
> Key: SPARK-38445
> URL: https://issues.apache.org/jira/browse/SPARK-38445
> Project: Spark
> Issue Type: Question
> Components: Spark Core
> Affects Versions: 3.2.1
> Reporter: Martin Andersson
> Priority: Major
> Labels: structured-streaming
>
> At the company I work at we're using Spark Structured Streaming to sink
> messages on kafka to HDFS. We're in the late stages of migrating this
> component to instead sink messages to AWS S3, and in connection with that we
> hit upon a couple of issues regarding hadoop committers.
> I've come to understand that the default "file" committer (documented
> [here|https://hadoop.apache.org/docs/stable/hadoop-aws/tools/hadoop-aws/committers.html#Switching_to_an_S3A_Committer])
> is unsafe to use in S3, which is why [this page in the spark
> documentation|https://spark.apache.org/docs/3.2.1/cloud-integration.html]
> recommends using the "directory" (i.e. staging) committer, and in later
> versions of hadoop they also recommend to use the "magic" committer.
> However, it's not clear whether spark structured streaming even use
> committers. There's no "_SUCCESS" file in destination (as compared to normal
> spark jobs), and the documentation regarding committers used in streaming is
> non-existent.
> Can anyone please shed some light on this?
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