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From "Benjamin Coverston (JIRA)" <>
Subject [jira] [Updated] (CASSANDRA-1608) Redesigned Compaction
Date Wed, 29 Jun 2011 22:45:29 GMT


Benjamin Coverston updated CASSANDRA-1608:

    Attachment: 1608-v8.txt

First the good:

1. Modified the code s.t. tombstone purge during minor compactions use the interval tree to
prune the list of SSTables speeding up compactions by at least an order of magnitude where
the number of SSTables in a column family exceeds ~500.

2. Tested reads and writes. Write speeds (unsurprisingly) are not affected by this compaction
strategy. Reads seem to keep up as well. 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.

3. Three successive runs of stress inserting 10M keys resulted in ~3GB of data stored in leveldb.
By comparison, the same run using the tiered (default) strategy resulted in ~8GB of data.

The Meh:

Compactions do back up when setting the flush size to 64MB and the leveled SSTable size to
anywhere between 5-10MB. On the upside, if your load has peaks and quieter times this compaction
strategy will trigger a periodic check to "catch up" if all event-scheduled compactions complete.

Interestingly this extra IO has an upside. For datasets that frequently overwrite old data
that has already been flushed to disk there is the potential for substantial de-duplication
of data. Further, during reads the number of rows that would need to be merged for a single
row is bound by the number of levels + the number of un-leveled sstables.

> Redesigned Compaction
> ---------------------
>                 Key: CASSANDRA-1608
>                 URL:
>             Project: Cassandra
>          Issue Type: Improvement
>          Components: Core
>            Reporter: Chris Goffinet
>            Assignee: Benjamin Coverston
>         Attachments: 0001-leveldb-style-compaction.patch, 1608-v2.txt, 1608-v3.txt, 1608-v4.txt,
1608-v5.txt, 1608-v7.txt, 1608-v8.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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