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Posted to issues@spark.apache.org by "Erik Krogen (Jira)" <ji...@apache.org> on 2021/09/20 18:01:00 UTC
[jira] [Updated] (SPARK-36810) Handle HDFS read inconsistencies on
Spark when observer Namenode is used
[ https://issues.apache.org/jira/browse/SPARK-36810?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Erik Krogen updated SPARK-36810:
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Summary: Handle HDFS read inconsistencies on Spark when observer Namenode is used (was: Handle HDSF read inconsistencies on Spark when observer Namenode is used)
> Handle HDFS read inconsistencies on Spark when observer Namenode is used
> ------------------------------------------------------------------------
>
> Key: SPARK-36810
> URL: https://issues.apache.org/jira/browse/SPARK-36810
> Project: Spark
> Issue Type: Bug
> Components: Spark Core, SQL
> Affects Versions: 3.2.0
> Reporter: Venkata krishnan Sowrirajan
> Priority: Major
>
> In short, with HDFS HA and with the use of [Observer Namenode|https://hadoop.apache.org/docs/stable/hadoop-project-dist/hadoop-hdfs/ObserverNameNode.html] the read-after-write consistency is only available when both the write and the read happens from the same client.
> But if the write happens on executor and the read happens on the driver, then the reads would be inconsistent causing application failure issues. This can be fixed by calling `FileSystem.msync` before making any read calls where the client thinks the write could have possibly happened elsewhere.
> This issue is discussed in greater detail in this [discussion|https://mail-archives.apache.org/mod_mbox/spark-dev/202108.mbox/browser]
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