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