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Posted to issues@spark.apache.org by "Dongjoon Hyun (Jira)" <ji...@apache.org> on 2024/03/21 05:21:00 UTC
[jira] [Updated] (SPARK-47008) Spark to support S3 Express One Zone Storage
[ https://issues.apache.org/jira/browse/SPARK-47008?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Dongjoon Hyun updated SPARK-47008:
----------------------------------
Parent Issue: SPARK-44111 (was: SPARK-44124)
> Spark to support S3 Express One Zone Storage
> --------------------------------------------
>
> Key: SPARK-47008
> URL: https://issues.apache.org/jira/browse/SPARK-47008
> Project: Spark
> Issue Type: Sub-task
> Components: Spark Core
> Affects Versions: 4.0.0
> Reporter: Steve Loughran
> Priority: Major
>
> Hadoop 3.4.0 adds support for AWS S3 Express One Zone Storage.
> Most of this is transparent. However, one aspect which can surface as an issue is that these stores report prefixes in a listing when there are pending uploads, *even when there are no files underneath*
> This leads to a situation where a listStatus of a path returns a list of file status entries which appears to contain one or more directories -but a listStatus on that path raises a FileNotFoundException: there is nothing there.
> HADOOP-18996 handles this in all of hadoop code, including FileInputFormat,
> A filesystem can now be probed for inconsistent directoriy listings through {{fs.hasPathCapability(path, "fs.capability.directory.listing.inconsistent")}}
> If true, then treewalking code SHOULD NOT report a failure if, when walking into a subdirectory, a list/getFileStatus on that directory raises a FileNotFoundException.
> Although most of this is handled in the hadoop code, but there some places where treewalking is done inside spark These need to be identified and make resilient to failure on the recurse down the tree
> * SparkHadoopUtil list methods ,
> * especially listLeafStatuses used by OrcFileOperator
> org.apache.spark.util.Utils#fetchHcfsFile
> {{org.apache.hadoop.fs.FileUtil.maybeIgnoreMissingDirectory()}} can assist here, or the logic can be replicated. Using the hadoop implementation would be better from a maintenance perspective
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