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Posted to issues@spark.apache.org by "Martin Andersson (Jira)" <ji...@apache.org> on 2022/03/08 09:53:00 UTC
[jira] [Updated] (SPARK-38445) Are hadoop committers used in Structured Streaming?
[ https://issues.apache.org/jira/browse/SPARK-38445?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Martin Andersson updated SPARK-38445:
-------------------------------------
Description:
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?
was:
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 later versions also recommends 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?
> 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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