anchor.diff:  See <<brand.new.compressor,brand.new.compressor>>).
   
   [[lzo.compression]]
  -.Install LZO Support
  -
  -HBase cannot ship with LZO because of incompatibility between HBase, which uses an Apache Software License (ASL) and LZO, which uses a GPL license.
  +.Install Hadoop Native LZO Support
  +
  +HBase cannot ship with the Hadoop native LZO codc because of incompatibility between HBase, which uses an Apache Software License (ASL) and LZO, which uses a GPL license.
   See the link:https://github.com/twitter/hadoop-lzo/blob/master/README.md[Hadoop-LZO at Twitter] for information on configuring LZO support for HBase.
   
  -If you depend upon LZO compression, consider configuring your RegionServers to fail to start if LZO is not available.
  +If you depend upon LZO compression, consider using the pure Java and ASL licensed
  +AirCompressor LZO codec option instead of the Hadoop native default, or configure your
  +RegionServers to fail to start if native LZO support is not available.
   See <<hbase.regionserver.codecs,hbase.regionserver.codecs>>.
   
   [[lz4.compression]]
  -.Configure LZ4 Support
  -
  -LZ4 support is bundled with Hadoop.
  -Make sure the hadoop shared library (libhadoop.so) is accessible when you start HBase.
  -After configuring your platform (see <<hadoop.native.lib,hadoop.native.lib>>), you can make a symbolic link from HBase to the native Hadoop libraries.
  -This assumes the two software installs are colocated.
  -For example, if my 'platform' is Linux-amd64-64:
  +.Configure Hadoop Native LZ4 Support
  +
  +LZ4 support is bundled with Hadoop and is the default LZ4 codec implementation.
  +It is not required that you make use of the Hadoop LZ4 codec. Our LZ4 codec implemented
  +with lz4-java offers superior performance, and the AirCompressor LZ4 codec offers a
  +pure Java option for use where native support is not available.
  +
  +That said, if you prefer the Hadoop option, make sure the hadoop shared library
  +(libhadoop.so) is accessible when you start HBase.
  +After configuring your platform (see <<hadoop.native.lib,hadoop.native.lib>>), you can
  +make a symbolic link from HBase to the native Hadoop libraries. This assumes the two
  +software installs are colocated. For example, if my 'platform' is Linux-amd64-64:
   [source,bourne]
   ----
   $ cd $HBASE_HOME
  
positive.code: ----
  
  [[snappy.compression.installation]]
  .Install Snappy Support
  
  HBase does not ship with Snappy support because of licensing issues.
  You can install Snappy binaries (for instance, by using +yum install snappy+ on CentOS) or build Snappy from source.
  After installing Snappy, search for the shared library, which will be called _libsnappy.so.X_ where X is a number.
  If you built from source, copy the shared library to a known location on your system, such as _/opt/snappy/lib/_.
  
  
negative.code: To enable data block encoding for a ColumnFamily, see <<data.block.encoding.enable,data.block.encoding.enable>>.
  
  .Block Compressors
  * NONE
  +
  This compression type constant selects no compression, and is the default.
  * BROTLI
  +
  https://en.wikipedia.org/wiki/Brotli[Brotli] is a generic-purpose lossless compression algorithm
  that compresses data using a combination of a modern variant of the LZ77 algorithm, Huffman
  coding, and 2nd order context modeling, with a compression ratio comparable to the best currently
  available general-purpose compression methods. It is similar in speed with GZ but offers more
  dense compression.
  * BZIP2
  +
  https://en.wikipedia.org/wiki/Bzip2[Bzip2] compresses files using the Burrows-Wheeler block
  sorting text compression algorithm and Huffman coding. Compression is generally considerably
  better than that achieved by the dictionary- (LZ-) based compressors, but both compression and
  decompression can be slow in comparison to other options.
  * GZ
  +
  gzip is based on the https://en.wikipedia.org/wiki/Deflate[DEFLATE] algorithm, which is a
  combination of LZ77 and Huffman coding. It is universally available in the Java Runtime
  Environment so is a good lowest common denominator option. However in comparison to more modern
  algorithms like Zstandard it is quite slow.
  * LZ4
  +
  https://en.wikipedia.org/wiki/LZ4_(compression_algorithm)[LZ4] is a lossless data compression
  algorithm that is focused on compression and decompression speed. It belongs to the LZ77 family
  of compression algorithms, like Brotli, DEFLATE, Zstandard, and others. In our microbenchmarks
  LZ4 is the fastest option for both compression and decompression in that family, and is our
  universally recommended option.
  * LZMA
  +
  https://en.wikipedia.org/wiki/Lempel%E2%80%93Ziv%E2%80%93Markov_chain_algorithm[LZMA] is a
  dictionary compression scheme somewhat similar to the LZ77 algorithm that achieves very high
  compression ratios with a computationally expensive predictive model and variable size
  compression dictionary, while still maintaining decompression speed similar to other commonly used
  compression algorithms. LZMA is superior to all other options in general compression ratio but as
  a compressor it can be extremely slow, especially when configured to operate at higher levels of
  compression.
  * LZO
  +
  https://en.wikipedia.org/wiki/Lempel%E2%80%93Ziv%E2%80%93Oberhumer[LZO] is another LZ-variant
  data compression algorithm, with an implementation focused on decompression speed. It is almost
  but not quite as fast as LZ4.
  * SNAPPY
  +
  https://en.wikipedia.org/wiki/Snappy_(compression)[Snappy] is based on ideas from LZ77 but is
  optimized for very high compression speed, achieving only a "reasonable" compression in trade.
  It is as fast as LZ4 but does not compress quite as well. We offer a pure Java Snappy codec
  that can be used instead of GZ as the universally available option for any Java runtime on any
  hardware architecture.
  * ZSTD
  +
  https://en.wikipedia.org/wiki/Zstd[Zstandard] combines a dictionary-matching stage (LZ77) with
  a large search window and a fast entropy coding stage, using both Finite State Entropy and
  Huffman coding. Compression speed can vary by a factor of 20 or more between the fastest and
  slowest levels, while decompression is uniformly fast, varying by less than 20% between the
  fastest and slowest levels.
  +
  ZStandard is the most flexible of the available compression codec options, offering a compression
  ratio similar to LZ4 at level 1 (but with slightly less performance), compression ratios
  comparable to DEFLATE at mid levels (but with better performance), and LZMA-alike dense
  compression (and LZMA-alike compression speeds) at high levels; while providing universally fast
  decompression.
  
  .Data Block Encoding Types
  Prefix::
  