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From "Jonathan Ellis (JIRA)" <>
Subject [jira] [Commented] (CASSANDRA-1608) Redesigned Compaction
Date Wed, 27 Jul 2011 02:23:10 GMT


Jonathan Ellis commented on CASSANDRA-1608:

bq. The interval tree does a good job here making sure that bloom filters are only queried
only for those SSTables that fall into the queried range

Is it even worth keeping bloom filters around with such a drastic reduction in worst-case
number of sstables to check (for read path too)?

bq. Compactions do back up

Not a deal breaker for me -- it's not hard to get old-style compactions to back up under sustained
writes, either.  Given a choice between "block writes until compactions catch up" or "let
them back up and let the operater deal with it how he will," I'll take the latter.

bq. flush size to 64MB and the leveled SSTable size to anywhere between 5-10MB

I'd like to have a better understanding of what the tradeoff is between making these settings
larger/smaller.  Can we make these one-size-fits-all?

bq. For datasets that frequently overwrite old data that has already been flushed to disk
there is the potential for substantial de-duplication of data

Yes, this is a big win.  Even people who will never fill up half their disk, complain about
the worst-case major compaction scenario for old-style compaction.

> Redesigned Compaction
> ---------------------
>                 Key: CASSANDRA-1608
>                 URL:
>             Project: Cassandra
>          Issue Type: Improvement
>          Components: Core
>            Reporter: Chris Goffinet
>            Assignee: Benjamin Coverston
>         Attachments: 1608-v2.txt, 1608-v8.txt, 1609-v10.txt
> After seeing the I/O issues in CASSANDRA-1470, I've been doing some more thinking on
this subject that I wanted to lay out.
> I propose we redo the concept of how compaction works in Cassandra. At the moment, compaction
is kicked off based on a write access pattern, not read access pattern. In most cases, you
want the opposite. You want to be able to track how well each SSTable is performing in the
system. If we were to keep statistics in-memory of each SSTable, prioritize them based on
most accessed, and bloom filter hit/miss ratios, we could intelligently group sstables that
are being read most often and schedule them for compaction. We could also schedule lower priority
maintenance on SSTable's not often accessed.
> I also propose we limit the size of each SSTable to a fix sized, that gives us the ability
to  better utilize our bloom filters in a predictable manner. At the moment after a certain
size, the bloom filters become less reliable. This would also allow us to group data most
accessed. Currently the size of an SSTable can grow to a point where large portions of the
data might not actually be accessed as often.

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