Xabriel J Collazo Mojica created HADOOP-11644:
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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 indexes.
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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