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From "Jonathan Ellis (JIRA)" <j...@apache.org>
Subject [jira] Commented: (CASSANDRA-16) Memory efficient compactions
Date Mon, 17 Aug 2009 23:22:14 GMT

    [ https://issues.apache.org/jira/browse/CASSANDRA-16?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12744277#action_12744277
] 

Jonathan Ellis commented on CASSANDRA-16:
-----------------------------------------

Or, how about this compromise:

We know each row size at the start.  If the sum of these (which will always be equal or greater
than the actual merged size) is greater than some user-defined number of MB, we do a two-pass
merge; first to compute bloom filter, column index, and total row size, and second to actually
write out the merged columns.

Otherwise we do an in-memory merge the way we do now so that narrow rows are not penalized.

This has the added benefit of not requiring a disk format change.


> Memory efficient compactions 
> -----------------------------
>
>                 Key: CASSANDRA-16
>                 URL: https://issues.apache.org/jira/browse/CASSANDRA-16
>             Project: Cassandra
>          Issue Type: Improvement
>          Components: Core
>         Environment: All
>            Reporter: Sandeep Tata
>            Priority: Critical
>             Fix For: 0.5
>
>
> The basic idea is to allow rows to get large enough that they don't have to fit in memory
entirely, but can easily fit on a disk. The compaction algorithm today de-serializes the entire
row in memory before writing out the compacted SSTable (see ColumnFamilyStore.doCompaction()
and associated methods).
> The requirement is to have a compaction method with a lower memory requirement so we
can support rows larger than available main memory. To re-use the old FB example, if we stored
a user's inbox in a row, we'd want the inbox to grow bigger than memory so long as it fit
on disk.

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