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Nick Terrell e103d7b4a6
Fix superblock mode (#2100)
Fixes:

Enable RLE blocks for superblock mode
Fix the limitation that the literals block must shrink. Instead, when we're within 200 bytes of the next header byte size, we will just use the next one up. That way we should (almost?) always have space for the table.
Remove the limitation that the first sub-block MUST have compressed literals and be compressed. Now one sub-block MUST be compressed (otherwise we fall back to raw block which is okay, since that is streamable). If no block has compressed literals that is okay, we will fix up the next Huffman table.
Handle the case where the last sub-block is uncompressed (maybe it is very small). Before it would skip superblock in this case, now we allow the last sub-block to be uncompressed. To do this we need to regenerate the correct repcodes.
Respect disableLiteralsCompression in superblock mode
Fix superblock mode to handle a block consisting of only compressed literals
Fix a off by 1 error in superblock mode that disabled it whenever there were last literals
Fix superblock mode with long literals/matches (> 0xFFFF)
Allow superblock mode to repeat Huffman tables
Respect ZSTD_minGain().
Tests:

Simple check for the condition in #2096.
When the simple_round_trip fuzzer enables superblock mode, it checks that the compressed size isn't expanded too much.
Remaining limitations:

O(targetCBlockSize^2) because we recompute statistics every sequence
Unable to split literals of length > targetCBlockSize into multiple sequences
Refuses to generate sub-blocks that don't shrink the compressed data, so we could end up with large sub-blocks. We should emit those sections as uncompressed blocks instead.
...
Fixes #2096
2020-05-01 16:11:47 -07:00
.circleci [circleci] Run test-license.py 2020-03-26 20:13:16 -07:00
.github Add issue templates to zstd 2020-03-03 14:57:02 -08:00
build meson msvc build fix 2020-05-01 09:04:09 -05:00
contrib Fixed clash when projects are already using xxHash 2020-04-07 18:17:59 +02:00
doc Fix copyright and license lines 2020-03-26 17:02:06 -07:00
examples Fix copyright and license lines 2020-03-26 17:02:06 -07:00
lib Fix superblock mode (#2100) 2020-05-01 16:11:47 -07:00
programs fixed zstd-nolegacy target 2020-04-29 11:56:21 -07:00
tests Fix superblock mode (#2100) 2020-05-01 16:11:47 -07:00
zlibWrapper Fix copyright and license lines 2020-03-26 17:02:06 -07:00
.buckconfig Update builds to not support legacy v01-v03 2017-03-13 14:44:08 -07:00
.buckversion Add BUCK files for Nuclide support 2017-01-27 10:43:12 -08:00
.cirrus.yml [cirrus-ci] Removing pkg -y update and using 11.3-snap instead of 11.2 (#2018) 2020-02-27 13:53:03 -08:00
.gitattributes zstd.exe has FileVersion and ProductVersion 2016-09-13 13:53:43 +02:00
.gitignore added ppc64le tests on travis 2019-12-15 01:30:12 -08:00
.travis.yml added test linking user program to multi-threaded libzstd 2020-04-28 21:18:29 -07:00
appveyor.yml Add support for running more tests via CTest 2020-03-30 15:14:00 -04:00
CHANGELOG updated CHANGELOG 2020-01-24 14:12:25 -08:00
CODE_OF_CONDUCT.md added code of conduct 2018-09-06 11:20:39 -07:00
CONTRIBUTING.md Remove redundant section and typo 2020-02-18 14:21:19 -08:00
COPYING added GPLv2 license 2017-08-18 16:32:08 -07:00
LICENSE added boilerplate 2016-08-30 11:06:28 -07:00
Makefile Merge pull request #2048 from nocnokneo/ctest-support 2020-04-28 11:01:13 -07:00
README.md Update comments 2020-01-19 23:51:40 -08:00
TESTING.md Fix testing documentation typo 2020-03-23 17:48:59 -04:00

Zstandard

Zstandard, or zstd as short version, is a fast lossless compression algorithm, targeting real-time compression scenarios at zlib-level and better compression ratios. It's backed by a very fast entropy stage, provided by Huff0 and FSE library.

The project is provided as an open-source dual BSD and GPLv2 licensed C library, and a command line utility producing and decoding .zst, .gz, .xz and .lz4 files. Should your project require another programming language, a list of known ports and bindings is provided on Zstandard homepage.

Development branch status:

Build Status Build status Build status Build status Fuzzing Status

Benchmarks

For reference, several fast compression algorithms were tested and compared on a server running Arch Linux (Linux version 5.0.5-arch1-1), with a Core i9-9900K CPU @ 5.0GHz, using lzbench, an open-source in-memory benchmark by @inikep compiled with gcc 8.2.1, on the Silesia compression corpus.

Compressor name Ratio Compression Decompress.
zstd 1.4.4 -1 2.884 520 MB/s 1600 MB/s
zlib 1.2.11 -1 2.743 110 MB/s 440 MB/s
brotli 1.0.7 -0 2.701 430 MB/s 470 MB/s
quicklz 1.5.0 -1 2.238 600 MB/s 800 MB/s
lzo1x 2.09 -1 2.106 680 MB/s 950 MB/s
lz4 1.8.3 2.101 800 MB/s 4220 MB/s
snappy 1.1.4 2.073 580 MB/s 2020 MB/s
lzf 3.6 -1 2.077 440 MB/s 930 MB/s

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 server running Linux Debian (Linux version 4.14.0-3-amd64) with a Core i7-6700K CPU @ 4.0GHz, using lzbench, an open-source in-memory benchmark by @inikep compiled with gcc 7.3.0, on the Silesia compression corpus.

Compression Speed vs Ratio Decompression Speed
Compression Speed vs Ratio Decompression Speed

A few other algorithms can produce higher compression ratios at slower speeds, falling outside of the graph. For a larger picture including 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 compress. This problem is common to all compression algorithms, and reason is, compression algorithms learn from past data how to compress future data. But at the beginning of a new data set, 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. Training Zstandard is achieved by providing it with a few samples (one file per sample). The result of this training is stored in a file called "dictionary", which must be loaded before compression and decompression. Using this dictionary, the compression ratio achievable on small data improves dramatically.

The following example uses the github-users sample set, created from github public API. It consists of roughly 10K records weighing about 1KB each.

Compression Ratio Compression Speed Decompression Speed
Compression Ratio Compression Speed Decompression Speed

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

Training works if there is some correlation in a family of small data samples. The more data-specific a dictionary is, the more efficient it is (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 gradually use previously decoded content to better compress the rest of the file.

Dictionary compression How To:

  1. Create the dictionary

    zstd --train FullPathToTrainingSet/* -o dictionaryName

  2. Compress with dictionary

    zstd -D dictionaryName FILE

  3. Decompress with dictionary

    zstd -D dictionaryName --decompress FILE.zst

Build instructions

Makefile

If your system is compatible with standard make (or gmake), invoking make in root directory will generate zstd cli in root directory.

Other available options include:

  • make install : create and install zstd cli, library and man pages
  • make check : create and run zstd, tests its behavior 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.

By default, CMAKE_BUILD_TYPE is set to Release.

Meson

A Meson project is provided within build/meson. Follow build instructions in that directory.

You can also take a look at .travis.yml file for an example about how Meson is used to build this project.

Note that default build type is release.

VCPKG

You can build and install zstd vcpkg dependency manager:

git clone https://github.com/Microsoft/vcpkg.git
cd vcpkg
./bootstrap-vcpkg.sh
./vcpkg integrate install
./vcpkg install zstd

The zstd port in vcpkg is kept up to date by Microsoft team members and community contributors. If the version is out of date, please create an issue or pull request on the vcpkg repository.

Visual Studio (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, VS2015 and VS2017.
  • 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.

Buck

You can build the zstd binary via buck by executing: buck build programs:zstd from the root of the repo. The output binary will be in buck-out/gen/programs/.

Status

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

License

Zstandard is dual-licensed under BSD and GPLv2.

Contributing

The "dev" branch is the one where all contributions are 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.