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https://issues.apache.org/jira/browse/HBASE-4218?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13086615#comment-13086615
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Jacek Migdal commented on HBASE-4218:
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Matt, I have already implemented a few algorithms which share common interface.
I think we can add your method as another one. For the data I tested on, it
seemed that stream compression was the best solution. However, the algorithm
should be configurable so supporting a few algorithms should not be a problem.
Basically, I need four methods:
-compress list of KeyValues (I operate on bytes)
-uncompress to list of KeyValues
-find in your structure certain key and return "position"
-materialize KeyValue on certain "position" and move to the next position
The only thing that could be challenging for you. I store all the data in
ByteBuffer and need a tiny decompression state. That make things like direct
buffers trivial to implement. However, As long as you use bunch of Java objects
you would be unable to move it off the heap.
Once we have common interface you would be able to reuse some of my tests and
benchmarks.
Since I work on it almost full time, I could integrate it with HBase. Sooner or
later you could add your algorithm. Does it sound good for you?
> Delta Encoding of KeyValues (aka prefix compression)
> -----------------------------------------------------
>
> Key: HBASE-4218
> URL: https://issues.apache.org/jira/browse/HBASE-4218
> Project: HBase
> Issue Type: Improvement
> Components: io
> Reporter: Jacek Migdal
> Labels: compression
>
> A compression for keys. Keys are sorted in HFile and they are usually very
> similar. Because of that, it is possible to design better compression than
> general purpose algorithms,
> It is an additional step designed to be used in memory. It aims to save
> memory in cache as well as speeding seeks within HFileBlocks. It should
> improve performance a lot, if key lengths are larger than value lengths. For
> example, it makes a lot of sense to use it when value is a counter.
> Initial tests on real data (key length = ~ 90 bytes , value length = 8 bytes)
> shows that I could achieve decent level of compression:
> key compression ratio: 92%
> total compression ratio: 85%
> LZO on the same data: 85%
> LZO after delta encoding: 91%
> While having much better performance (20-80% faster decompression ratio than
> LZO). Moreover, it should allow far more efficient seeking which should
> improve performance a bit.
> It seems that a simple compression algorithms are good enough. Most of the
> savings are due to prefix compression, int128 encoding, timestamp diffs and
> bitfields to avoid duplication. That way, comparisons of compressed data can
> be much faster than a byte comparator (thanks to prefix compression and
> bitfields).
> In order to implement it in HBase two important changes in design will be
> needed:
> -solidify interface to HFileBlock / HFileReader Scanner to provide seeking
> and iterating; access to uncompressed buffer in HFileBlock will have bad
> performance
> -extend comparators to support comparison assuming that N first bytes are
> equal (or some fields are equal)
> Link to a discussion about something similar:
> http://search-hadoop.com/m/5aqGXJEnaD1/hbase+windows&subj=Re+prefix+compression
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