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From "Xabriel J Collazo Mojica (JIRA)" <j...@apache.org>
Subject [jira] [Created] (HADOOP-11644) Contribute CMX compression
Date Sat, 28 Feb 2015 00:12:04 GMT
Xabriel J Collazo Mojica created HADOOP-11644:

             Summary: Contribute CMX compression
                 Key: HADOOP-11644
                 URL: https://issues.apache.org/jira/browse/HADOOP-11644
             Project: Hadoop Common
          Issue Type: Improvement
          Components: io
            Reporter: Xabriel J Collazo Mojica
            Assignee: Xabriel J Collazo Mojica

Hadoop natively supports four main compression algorithms: BZIP2, LZ4, Snappy and ZLIB.

Each one of these algorithms fills a gap:

bzip2 : Very high compression ratio, splittable
LZ4 : Very fast, non splittable
Snappy : Very fast, non splittable
zLib : good balance of compression and speed.

We think there is a gap for a compression algorithm that can perform fast compress and decompress,
while also being splittable. This can help significantly on jobs where the input file sizes
are >= 1GB.
For this, IBM has developed CMX. CMX is a dictionary-based, block-oriented, splittable, concatenable
compression algorithm developed specifically for Hadoop workloads. Many of our customers use
CMX, and we would love to be able to contribute it to hadoop-common. 

CMX is block oriented : We typically use 64k blocks. Blocks are independently decompressable.

CMX is splittable : We implement the SplittableCompressionCodec interface. All CMX files are
a multiple of 64k, so the splittability is achieved in a simple way with no need for external

CMX is concatenable : Two independent CMX files can be concatenated together. We have seen
that some projects like Apache Flume require this feature.

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