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Posted to issues@hbase.apache.org by "Duo Zhang (Jira)" <ji...@apache.org> on 2023/11/29 13:39:00 UTC

[jira] [Updated] (HBASE-28227) Tables to which Stripe Compaction policy is applied cannot be forced to trigger Major Compaction.

     [ https://issues.apache.org/jira/browse/HBASE-28227?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Duo Zhang updated HBASE-28227:
------------------------------
    Issue Type: Improvement  (was: Bug)

> Tables to which Stripe Compaction policy is applied cannot be forced to trigger Major Compaction.
> -------------------------------------------------------------------------------------------------
>
>                 Key: HBASE-28227
>                 URL: https://issues.apache.org/jira/browse/HBASE-28227
>             Project: HBase
>          Issue Type: Improvement
>          Components: regionserver
>    Affects Versions: 2.2.6
>            Reporter: longping_jie
>            Priority: Major
>
>     There is a table and the Stripe Compaction strategy is applied. Each region has an average value of 40G and is divided into 8 Stripes. Each Stripe is 5G. The business deletes a large amount of data. Manually triggering major compaction on the entire table and a single region does not work and cannot be selected.
>     After reading the source code, the merging strategy applied under each Stripe is ExploringCompactionPolicy. This strategy has a key point. It filters the Store file list of a single Stripe. In the candidate file list, as long as there is a file that is too large in size and meets the condition, fileSize > (totalFileSize - fileSize) * (hbase.hstore.compaction.ratio default value 1.2), files will not be filtered out to participate in major compaction.
>     It is necessary to support a forced merging mechanism. For scenarios where a large amount of data is deleted, or where bulkload exists, you can explicitly pass in a parameter such as foreMajor when manually triggering the major, and then perform forced Major Compaction in Stripe units to support the data. Clean up.
>     



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