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Posted to issues@hbase.apache.org by "Duo Zhang (Jira)" <ji...@apache.org> on 2022/08/09 07:57:00 UTC

[jira] [Commented] (HBASE-24541) Add support to run LoadIncrementalHFiles in a distributed manner

    [ https://issues.apache.org/jira/browse/HBASE-24541?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17577232#comment-17577232 ] 

Duo Zhang commented on HBASE-24541:
-----------------------------------

The PR against branch-1.4 has been closed as we have already EOL all the 1.x release lines.

Feel free to open a new PR against master.

> Add support to run LoadIncrementalHFiles in a distributed manner
> ----------------------------------------------------------------
>
>                 Key: HBASE-24541
>                 URL: https://issues.apache.org/jira/browse/HBASE-24541
>             Project: HBase
>          Issue Type: Improvement
>          Components: mapreduce, Performance
>    Affects Versions: 1.4.0
>            Reporter: Constantin-Catalin Luca
>            Assignee: Constantin-Catalin Luca
>            Priority: Minor
>         Attachments: HBASE_24541-1.4.0.patch
>
>
> LoadIncrementalHFiles takes a very long time to complete when running HBase on top of S3 and attempting to bulkload 500K-700K files.
> The root cause of this is a combination of the higher latency of S3 (as compared to HDFS) as well as the calls made by LoadIncrementalHFiles to the underlying filesystem(each file is opened, seeked to the trailer offset at the end, and then the trailer is read).
> Increasing the parallelism does not yield any significant improvement. This seems to stem from the fact that once the trailer is read the stream is not consumed to the end. This causes the underlying HTTP connection to be aborted and it cannot be re-used.
>  
> The proposed solution would be to also add support to run LoadIncrementalHFiles on multiple machines as a map reduce job. 



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