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https://issues.apache.org/jira/browse/CASSANDRA-2392?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13189802#comment-13189802
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Pavel Yaskevich commented on CASSANDRA-2392:
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bq. Renamed and done recommended changes. Exempt we have all the in-memory
data-structures in one file instead of multiple files. They are handled
differently and will be kind of throw away data so we can regenerate it.
I kind of liked it more when component was Summary because InMemoryData doesn't
really tell what is inside. Please rename SegmentedFile serialize/deserialize
to something like serializeBounds/deserializeBounds.
bq. I do see Keycache working in my tests...
Sorry I wasn't clear when I was saying that. It seems like that summary
save/load is pointless in it's current form because even if we have loaded
summary from disk we would anyway have to loop through *whole* PRIMARY_INDEX if
pre-cache (which is always enabled by default) or re-create-BloomFilter was
enabled, which is practically means that we spend the same time on I/O there as
ibuilder.deserialize and dbuilder.deserialize together. We would need to change
the logic in SSTableReader.load(boolean, Set<DecoratedKey>) the way it doesn't
have such I/O overhead because this will make it even slower comparing to the
time it takes now.
> Saving IndexSummaries to disk
> -----------------------------
>
> Key: CASSANDRA-2392
> URL: https://issues.apache.org/jira/browse/CASSANDRA-2392
> Project: Cassandra
> Issue Type: Improvement
> Reporter: Chris Goffinet
> Assignee: Vijay
> Priority: Minor
> Fix For: 1.1
>
> Attachments: 0001-re-factor-first-and-last.patch,
> 0001-save-summaries-to-disk.patch, 0002-save-summaries-to-disk-v2.patch,
> 0002-save-summaries-to-disk.patch
>
>
> For nodes with millions of keys, doing rolling restarts that take over 10
> minutes per node can be painful if you have 100 node cluster. All of our time
> is spent on doing index summary computations on startup. It would be great if
> we could save those to disk as well. Our indexes are quite large.
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