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https://issues.apache.org/jira/browse/CASSANDRA-10643?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15408038#comment-15408038
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Vishy Kasar commented on CASSANDRA-10643:
-----------------------------------------
Thanks Marcus.
Bit surprised that it was not doing any compaction. The test that I added here
LeveledCompactionStrategyTest#testTokenRangeCompaction ran for me before your
changes.
That said, your changes look good. Please commit.
> Implement compaction for a specific token range
> -----------------------------------------------
>
> Key: CASSANDRA-10643
> URL: https://issues.apache.org/jira/browse/CASSANDRA-10643
> Project: Cassandra
> Issue Type: Improvement
> Components: Compaction
> Reporter: Vishy Kasar
> Assignee: Vishy Kasar
> Labels: lcs
> Attachments: 10643-trunk-REV01.txt, 10643-trunk-REV02.txt,
> 10643-trunk-REV03.txt
>
>
> We see repeated cases in production (using LCS) where small number of users
> generate a large number repeated updates or tombstones. Reading data of such
> users brings in large amounts of data in to java process. Apart from the read
> itself being slow for the user, the excessive GC affects other users as well.
> Our solution so far is to move from LCS to SCS and back. This takes long and
> is an over kill if the number of outliers is small. For such cases, we can
> implement the point compaction of a token range. We make the nodetool compact
> take a starting and ending token range and compact all the SSTables that fall
> with in that range. We can refuse to compact if the number of sstables is
> beyond a max_limit.
> Example:
> nodetool -st 3948291562518219268 -et 3948291562518219269 compact keyspace
> table
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