Use CompressionTest to verify snappy support is enabled and the libs can be loaded ON ALL NODES of your cluster:.Build and install snappy on all nodes of your cluster (see below).If snappy is installed, HBase can make use of it (courtesy of In versions since HBase 0.90.0, we should fail in a way that makes it plain what the problem is, but maybe not. Using LZO Compression wiki page for how to make LZO work with HBase.Ī common problem users run into when using LZO is that while initial setup of the cluster runs smooth, a month goes by and some sysadmin goes to add a machine to the cluster only they'll have forgotten to do the LZO fixup on the new machine. Therefore LZO install is to be done post-HBase install. Unfortunately, HBase cannot ship with LZO because of the licensing issues HBase is Apache-licensed, LZO is GPL. No matter what codec you use, be sure to test that it is installed correctly and is available on all nodes in your cluster. This articles discusses common codecs that are used and tested with HBase. Some codecs are licensed in ways that conflict with HBase's license and cannot be shipped as part of HBase. Other codecs, such as Google Snappy, need to be installed first. In this case, HBase only needs access to the appropriate shared library. Native libraries may be available as part of Hadoop, such as LZ4. Some codecs take advantage of capabilities built into Java, such as GZip compression. If you change compression or encoding for a ColumnFamily, the changes take effect during compaction. Compressors reduce the size of large, opaque byte arrays in cells, and can significantly reduce the storage space needed to store uncompressed data.Ĭompressors and data block encoding can be used together on the same ColumnFamily.Ĭhanges Take Effect Upon Compaction. Data block encoding attempts to limit duplication of information in keys, taking advantage of some of the fundamental designs and patterns of HBase, such as sorted row keys and the schema of a given table. Install snzip: If you don’t already have snzip installed on your system, you can install it using your system’s package manager.HBase supports several different compression algorithms which can be enabled on a ColumnFamily.Here are the steps to decompress a Snappy-compressed reduce output file using snzip: One such tool is snzip, which is a command-line utility for Snappy compression/decompression. To decompress a Snappy-compressed reduce output file, you need to use a command-line tool that supports the Snappy compression format. How to Decompress Snappy-Compressed Reduce Output Files When a reduce output file is compressed with Snappy, its file extension is typically. The output files generated by the reduce phase can be compressed using various compression algorithms, including Snappy. In this phase, the intermediate key-value pairs generated by the map phase are aggregated and reduced to a smaller set of key-value pairs that are written to output files. In Hadoop, the reduce phase is the second phase of a MapReduce job. Snappy is also designed to work well with various data formats, including text, binary, and multimedia data. Snappy achieves high compression/decompression speeds by using a simple and efficient algorithm that is optimized for modern CPUs. Snappy is widely used in various big data processing frameworks, including Hadoop, because of its speed and low memory usage. It was created by Google and released under the Apache license. Snappy is a compression/decompression library that is designed for speed and efficiency. We assume that you have a basic understanding of Hadoop and its ecosystem, as well as some familiarity with the Linux command line interface. In this article, we will explain how to decompress Hadoop reduce output files ending with Snappy. However, to work with these compressed files, you need to know how to decompress them. Snappy is a fast, open-source, and widely-used compression library that is supported by Hadoop and other big data processing frameworks. As a data scientist or software engineer, you might have come across Hadoop reduce output files ending with Snappy compression.
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