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https://issues.apache.org/jira/browse/FLINK-21321?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17436506#comment-17436506
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Yu Li commented on FLINK-21321:
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Since we've upgraded FRocksDB version to 6.20.3 in 1.14, it's possible to
enable this feature in 1.15 (and yes let's do it), while please note that this
could only accelerate the rescaling recovery speed for scaling out but not
scaling in.
> Change RocksDB incremental checkpoint re-scaling to use deleteRange
> -------------------------------------------------------------------
>
> Key: FLINK-21321
> URL: https://issues.apache.org/jira/browse/FLINK-21321
> Project: Flink
> Issue Type: Improvement
> Components: Runtime / State Backends
> Reporter: Joey Pereira
> Priority: Major
> Labels: pull-request-available
> Fix For: 1.15.0
>
>
> In FLINK-8790, it was suggested to use RocksDB's {{deleteRange}} API to more
> efficiently clip the databases for the desired target group.
> During the PR for that ticket,
> [#5582|https://github.com/apache/flink/pull/5582], the change did not end up
> using the {{deleteRange}} method as it was an experimental feature in
> RocksDB.
> At this point {{deleteRange}} is in a far less experimental state now but I
> believe is still formally "experimental". It is heavily by many others like
> CockroachDB and TiKV and they have teased out several bugs in complex
> interactions over the years.
> For certain re-scaling situations where restores trigger
> {{restoreWithScaling}} and the DB clipping logic, this would likely reduce an
> O[n] operation (N = state size/records) to O(1). For large state apps, this
> would potentially represent a non-trivial amount of time spent for
> re-scaling. In the case of my workplace, we have an operator with 100s of
> billions of records in state and re-scaling was taking a long time (>>30min,
> but it has been awhile since doing it).
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