[
https://issues.apache.org/jira/browse/HIVE-15215?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15671633#comment-15671633
]
Sergio Peña commented on HIVE-15215:
------------------------------------
It might be good to use approach #1 where it sets the staging directory under
the scratch directory only for blobstorage so Hive can do the final move at the
end. This move may be in parallel as renames are not allowed on S3, so it may
be faster.
> Files on S3 are deleted one by one in INSERT OVERWRITE queries
> --------------------------------------------------------------
>
> Key: HIVE-15215
> URL: https://issues.apache.org/jira/browse/HIVE-15215
> Project: Hive
> Issue Type: Sub-task
> Components: Hive
> Reporter: Sahil Takiar
>
> When running {{INSERT OVERWRITE}} queries the files to overwrite are deleted
> one by one. The reason is that, by default, hive.exec.stagingdir is inside
> the target table directory.
> Ideally Hive would just delete the entire table directory, but it can't do
> that since the staging data is also inside the directory. Instead it deletes
> each file one-by-one, which is very slow.
> There are a few ways to fix this:
> 1: Move the staging directory outside the table location. This can be done by
> setting hive.exec.stagingdir to a different location when running on S3. It
> would be nice if users didn't have to explicitly set this when running on S3
> and things just worked out-of-the-box. My understanding is that
> hive.exec.stagingdir was only added to support HDFS encryption zones. Since
> S3 doesn't have encryption zones, there should be no problem with using the
> value of hive.exec.scratchdir to store all intermediate data instead.
> 2: Multi-thread the delete operations
> 3: See if the {{S3AFileSystem}} can expose some type of bulk delete op
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
