Gitiles
Code Review Sign In
gerrit-public.fairphone.software / platform / external / zstd / baa152e56e5f56e8991615998b3550b0a736d5cb
commitbaa152e56e5f56e8991615998b3550b0a736d5cb[log] [tgz]
authorNick Terrell <terrelln@fb.com>Wed Oct 12 19:02:27 2016 -0700
committerNick Terrell <terrelln@fb.com>Fri Oct 14 15:26:55 2016 -0700
tree57d0144f66bfabadebc77b57140f327d405b8bda
parente9e151ce31835accd17ed5dcdf87ba18c558606d [diff]
[pzstd] Add Logger class
3 files changed
tree: 57d0144f66bfabadebc77b57140f327d405b8bda
  1. build/
  2. contrib/
  3. examples/
  4. images/
  5. lib/
  6. programs/
  7. tests/
  8. zlibWrapper/
  9. .coverity.yml
  10. .gitattributes
  11. .gitignore
  12. .travis.yml
  13. appveyor.yml
  14. CONTRIBUTING.md
  15. LICENSE
  16. LICENSE-examples
  17. Makefile
  18. NEWS
  19. PATENTS
  20. README.md
  21. zstd_compression_format.md
README.md

Zstd, short for Zstandard, is a fast lossless compression algorithm, targeting real-time compression scenarios at zlib-level and better compression ratios.

It is provided as an open-source BSD-licensed C library. For other programming languages, you can consult a list of known ports on Zstandard homepage.

BranchStatus
masterBuild Status
devBuild Status

As a reference, several fast compression algorithms were tested and compared on a Core i7-3930K CPU @ 4.5GHz, using lzbench, an open-source in-memory benchmark by @inikep compiled with GCC 5.4.0, with the Silesia compression corpus.

NameRatioC.speedD.speed
MB/sMB/s
zstd 0.8.2 -12.877330940
zlib 1.2.8 -12.73095360
brotli 0.4 -02.708320375
QuickLZ 1.52.237510605
LZO 2.092.106610870
LZ4 r1312.1016203100
Snappy 1.1.32.0914801600
LZF 3.62.077375790

Zstd can also offer stronger compression ratios at the cost of compression speed. Speed vs Compression trade-off is configurable by small increments. Decompression speed is preserved and remains roughly the same at all settings, a property shared by most LZ compression algorithms, such as zlib or lzma.

The following tests were run on a Core i7-3930K CPU @ 4.5GHz, using lzbench, an open-source in-memory benchmark by @inikep compiled with GCC 5.2.1, on the Silesia compression corpus.

Compression Speed vs RatioDecompression Speed
Compression Speed vs RatioDecompression Speed

Several algorithms can produce higher compression ratios, but at slower speeds, falling outside of the graph. For a larger picture including very slow modes, click on this link .

The case for Small Data compression

Previous charts provide results applicable to typical file and stream scenarios (several MB). Small data comes with different perspectives. The smaller the amount of data to compress, the more difficult it is to achieve any significant compression.

This problem is common to many compression algorithms. The reason is, compression algorithms learn from past data how to compress future data. But at the beginning of a new file, there is no "past" to build upon.

To solve this situation, Zstd offers a training mode, which can be used to tune the algorithm for a selected type of data, by providing it with a few samples. The result of the training is stored in a file called "dictionary", which can be loaded before compression and decompression. Using this dictionary, the compression ratio achievable on small data improves dramatically:

Compressing Small Data

These compression gains are achieved while simultaneously providing faster compression and decompression speeds.

Dictionary works if there is some correlation in a family of small data (there is no universal dictionary). Hence, deploying one dictionary per type of data will provide the greatest benefits. Dictionary gains are mostly effective in the first few KB. Then, the compression algorithm will rely more and more on previously decoded content to compress the rest of the file.

Dictionary compression How To :

  1. Create the dictionary

zstd --train FullPathToTrainingSet/* -o dictionaryName

  1. Compress with dictionary

zstd FILE -D dictionaryName

  1. Decompress with dictionary

zstd --decompress FILE.zst -D dictionaryName

Build

Once you have the repository cloned, there are multiple ways provided to build Zstandard.

Makefile

If your system is compatible with a standard make (or gmake) binary generator, you can simply run it at the root directory. It will generate zstd within root directory.

Other available options include :

  • make install : create and install zstd binary, library and man page
  • make test : create and run zstd and test tools on local platform

cmake

A cmake project generator is provided within build/cmake. It can generate Makefiles or other build scripts to create zstd binary, and libzstd dynamic and static libraries.

Visual (Windows)

Going into build directory, you will find additional possibilities :

  • Projects for Visual Studio 2005, 2008 and 2010
    • VS2010 project is compatible with VS2012, VS2013 and VS2015
  • Automated build scripts for Visual compiler by @KrzysFR , in build/VS_scripts, which will build zstd cli and libzstd library without any need to open Visual Studio solution.

Status

Zstandard is currently deployed within Facebook. It is used daily to compress and decompress very large amounts of data in multiple formats and use cases. Zstandard is considered safe for production environments.

License

Zstandard is BSD-licensed. We also provide an additional patent grant.

Contributing

The "dev" branch is the one where all contributions will be merged before reaching "master". If you plan to propose a patch, please commit into the "dev" branch or its own feature branch. Direct commit to "master" are not permitted. For more information, please read CONTRIBUTING.

Miscellaneous

Zstd entropy stage is provided by Huff0 and FSE, from Finite State Entropy library.