## File: README.md __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](https://github.com/Cyan4973/FiniteStateEntropy). Zstandard's format is stable and documented in [RFC8878](https://datatracker.ietf.org/doc/html/rfc8878). Multiple independent implementations are already available. This repository represents the reference implementation, provided as an open-source dual [BSD](LICENSE) OR [GPLv2](COPYING) 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](https://facebook.github.io/zstd/#other-languages). **Development branch status:** [![Build Status][travisDevBadge]][travisLink] [![Build status][CircleDevBadge]][CircleLink] [![Build status][CirrusDevBadge]][CirrusLink] [![Fuzzing Status][OSSFuzzBadge]][OSSFuzzLink] [travisDevBadge]: https://api.travis-ci.com/facebook/zstd.svg?branch=dev "Continuous Integration test suite" [travisLink]: https://travis-ci.com/facebook/zstd [CircleDevBadge]: https://circleci.com/gh/facebook/zstd/tree/dev.svg?style=shield "Short test suite" [CircleLink]: https://circleci.com/gh/facebook/zstd [CirrusDevBadge]: https://api.cirrus-ci.com/github/facebook/zstd.svg?branch=dev [CirrusLink]: https://cirrus-ci.com/github/facebook/zstd [OSSFuzzBadge]: https://oss-fuzz-build-logs.storage.googleapis.com/badges/zstd.svg [OSSFuzzLink]: https://bugs.chromium.org/p/oss-fuzz/issues/list?sort=-opened&can=1&q=proj:zstd ## Benchmarks For reference, several fast compression algorithms were tested and compared on a desktop featuring a Core i7-9700K CPU @ 4.9GHz and running Ubuntu 24.04 (`Linux 6.8.0-53-generic`), using [lzbench], an open-source in-memory benchmark by @inikep compiled with [gcc] 14.2.0, on the [Silesia compression corpus]. [lzbench]: https://github.com/inikep/lzbench [Silesia compression corpus]: https://sun.aei.polsl.pl//~sdeor/index.php?page=silesia [gcc]: https://gcc.gnu.org/ | Compressor name | Ratio | Compression| Decompress.| | --------------- | ------| -----------| ---------- | | **zstd 1.5.7 -1** | 2.896 | 510 MB/s | 1550 MB/s | | brotli 1.1.0 -1 | 2.883 | 290 MB/s | 425 MB/s | | [zlib] 1.3.1 -1 | 2.743 | 105 MB/s | 390 MB/s | | **zstd 1.5.7 --fast=1** | 2.439 | 545 MB/s | 1850 MB/s | | quicklz 1.5.0 -1 | 2.238 | 520 MB/s | 750 MB/s | | **zstd 1.5.7 --fast=4** | 2.146 | 665 MB/s | 2050 MB/s | | lzo1x 2.10 -1 | 2.106 | 650 MB/s | 780 MB/s | | [lz4] 1.10.0 | 2.101 | 675 MB/s | 3850 MB/s | | snappy 1.2.1 | 2.089 | 520 MB/s | 1500 MB/s | | lzf 3.6 -1 | 2.077 | 410 MB/s | 820 MB/s | [zlib]: https://www.zlib.net/ [lz4]: https://lz4.github.io/lz4/ The negative compression levels, specified with `--fast=#`, offer faster compression and decompression speed at the cost of compression ratio. 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 ---------------------------|-------------------- | 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](doc/images/DCspeed5.png). ## 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](https://github.com/facebook/zstd/releases/tag/v1.1.3), created from [github public API](https://developer.github.com/v3/users/#get-all-users). It consists of roughly 10K records weighing about 1KB each. 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 `make` is the main build system of this project. It is the reference, and other build systems are periodically updated to stay compatible. However, small drifts and feature differences can be present, since perfect synchronization is difficult. For this reason, when your build system allows it, prefer employing `make`. ### Makefile Assuming your system supports standard `make` (or `gmake`), just invoking `make` in root directory generates `zstd` cli at root, and also generates `libzstd` into `lib/`. Other standard targets include: - `make install` : install zstd cli, library and man pages - `make check` : run `zstd`, test its essential behavior on local platform The `Makefile` follows the [GNU Standard Makefile conventions](https://www.gnu.org/prep/standards/html_node/Makefile-Conventions.html), allowing staged install, standard compilation flags, directory variables and command variables. For advanced use cases, specialized flags which control binary generation and installation paths are documented in [`lib/README.md`](lib/README.md#modular-build) for the `libzstd` library and in [`programs/README.md`](programs/README.md#compilation-variables) for the `zstd` CLI. ### cmake A `cmake` project generator is available for generating Makefiles or other build scripts to create the `zstd` binary as well as `libzstd` dynamic and static libraries. The repository root now contains a minimal `CMakeLists.txt` that forwards to `build/cmake`, so you can configure the project with a standard `cmake -S .` invocation, while the historical `cmake -S build/cmake` entry point remains fully supported. ```bash cmake -S . -B build-cmake cmake --build build-cmake ``` By default, `CMAKE_BUILD_TYPE` is set to `Release`. #### Support for Fat (Universal2) Output `zstd` can be built and installed with support for both Apple Silicon (M1/M2) as well as Intel by using CMake's Universal2 support. To perform a Fat/Universal2 build and install use the following commands: ```bash cmake -S . -B build-cmake-debug -G Ninja -DCMAKE_OSX_ARCHITECTURES="x86_64;x86_64h;arm64" cd build-cmake-debug ninja sudo ninja install ``` ### Meson A Meson project is provided within [`build/meson`](build/meson). Follow build instructions in that directory. You can also take a look at [`.travis.yml`](.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](https://github.com/Microsoft/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](https://github.com/Microsoft/vcpkg) on the vcpkg repository. ### Conan You can install pre-built binaries for zstd or build it from source using [Conan](https://conan.io/). Use the following command: ```bash conan install --requires="zstd/[*]" --build=missing ``` The zstd Conan recipe is kept up to date by Conan maintainers and community contributors. If the version is out of date, please [create an issue or pull request](https://github.com/conan-io/conan-center-index) on the ConanCenterIndex repository. ### Visual Studio (Windows) Going into `build` directory, you will find additional possibilities: - Projects for Visual Studio 2008 and 2010. + VS2010 project is compatible with VS2012, VS2013, VS2015 and VS2017. - Automated build scripts for Visual compiler by [@KrzysFR](https://github.com/KrzysFR), in `build/VS_scripts`, which will build `zstd` cli and `libzstd` library without any need to open Visual Studio solution. - It is now recommended to generate Visual Studio solutions from `cmake` ### 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/`. ### Bazel You can integrate zstd into your Bazel project by using the module hosted on the [Bazel Central Repository](https://registry.bazel.build/modules/zstd). ## Testing You can run quick local smoke tests by running `make check`. If you can't use `make`, execute the `playTest.sh` script from the `src/tests` directory. Two env variables `$ZSTD_BIN` and `$DATAGEN_BIN` are needed for the test script to locate the `zstd` and `datagen` binary. For information on CI testing, please refer to `TESTING.md`. ## Status Zstandard is deployed within Meta and many other large cloud infrastructures, to compress humongous amounts of data in various formats and use cases. It is also continuously fuzzed for security issues by Google's [oss-fuzz](https://github.com/google/oss-fuzz/tree/master/projects/zstd) program. ## License Zstandard is dual-licensed under [BSD](LICENSE) OR [GPLv2](COPYING). ## Contributing The `dev` branch is the one where all contributions are merged before reaching `release`. Direct commit to `release` are not permitted. For more information, please read [CONTRIBUTING](CONTRIBUTING.md). --- ## File: contrib/docker/README.md ## Requirement The `Dockerfile` script requires a version of `docker` >= 17.05 ## Installing docker The official docker install docs use a ppa with a modern version available: https://docs.docker.com/install/linux/docker-ce/ubuntu/ ## How to run `docker build -t zstd .` ## test ``` echo foo | docker run -i --rm zstd | docker run -i --rm zstd zstdcat foo ``` --- ## File: contrib/externalSequenceProducer/README.md externalSequenceProducer ===================== `externalSequenceProducer` is a test tool for the Block-Level Sequence Producer API. It demonstrates how to use the API to perform a simple round-trip test. A sample sequence producer is provided in sequence_producer.c, but the user can swap this out with a different one if desired. The sample sequence producer implements LZ parsing with a 1KB hashtable. Dictionary-based parsing is not currently supported. Command line : ``` externalSequenceProducer filename ``` --- ## File: contrib/gen_html/README.md gen_html - a program for automatic generation of zstd manual ============================================================ #### Introduction This simple C++ program generates a single-page HTML manual from `zstd.h`. The format of recognized comment blocks is following: - comments of type `/*!` mean: this is a function declaration; switch comments with declarations - comments of type `/**` and `/*-` mean: this is a comment; use a `

` header for the first line - comments of type `/*=` and `/**=` mean: use a `

` header and show also all functions until first empty line - comments of type `/*X` where `X` is different from above-mentioned are ignored Moreover: - `ZSTDLIB_API` is removed to improve readability - `typedef` are detected and included even if uncommented - comments of type `/**<` and `/*!<` are detected and only function declaration is highlighted (bold) #### Usage The program requires 3 parameters: ``` gen_html [zstd_version] [input_file] [output_html] ``` To compile program and generate zstd manual we have used: ``` make ./gen_html.exe 1.1.1 ../../lib/zstd.h zstd_manual.html ``` --- ## File: contrib/largeNbDicts/README.md largeNbDicts ===================== `largeNbDicts` is a benchmark test tool dedicated to the specific scenario of dictionary decompression using a very large number of dictionaries. When dictionaries are constantly changing, they are always "cold", suffering from increased latency due to cache misses. The tool is created in a bid to investigate performance for this scenario, and experiment mitigation techniques. Command line : ``` largeNbDicts [Options] filename(s) Options : -z : benchmark compression (default) -d : benchmark decompression -r : recursively load all files in subdirectories (default: off) -B# : split input into blocks of size # (default: no split) -# : use compression level # (default: 3) -D # : use # as a dictionary (default: create one) -i# : nb benchmark rounds (default: 6) --nbBlocks=#: use # blocks for bench (default: one per file) --nbDicts=# : create # dictionaries for bench (default: one per block) -h : help (this text) Advanced Options (see zstd.h for documentation) : --dedicated-dict-search --dict-content-type=# --dict-attach-pref=# ``` --- ## File: contrib/linux-kernel/README.md # Zstd in the Linux Kernel This directory contains the scripts needed to transform upstream zstd into the version imported into the kernel. All the transforms are automated and tested by our continuous integration. ## Upgrading Zstd in the Linux Kernel 1. `cd` into this directory. 2. Run `make libzstd` and read the output. Make sure that all the diffs printed and changes made by the script are correct. 3. Run `make test` and ensure that it passes. 4. Import zstd into the Linux Kernel `make import LINUX=/path/to/linux/repo` 5. Inspect the diff for sanity. 6. Check the Linux Kernel history for zstd. If any patches were made to the kernel version of zstd, but not to upstream zstd, then port them upstream if necessary. 7. Test the diff. Benchmark if necessary. Make sure to test multiple architectures: At least x86, i386, and arm. 8. Submit the patch to the LKML. --- ## File: contrib/match_finders/README.md ## Edit Distance Match Finder ``` /* Detailed source-code truncated for AI context efficiency. */ ``` --- ## File: contrib/pzstd/README.md # Parallel Zstandard (PZstandard) Parallel Zstandard is a Pigz-like tool for Zstandard. It provides Zstandard format compatible compression and decompression that is able to utilize multiple cores. It breaks the input up into equal sized chunks and compresses each chunk independently into a Zstandard frame. It then concatenates the frames together to produce the final compressed output. Pzstandard will write a 12 byte header for each frame that is a skippable frame in the Zstandard format, which tells PZstandard the size of the next compressed frame. PZstandard supports parallel decompression of files compressed with PZstandard. When decompressing files compressed with Zstandard, PZstandard does IO in one thread, and decompression in another. ## Usage PZstandard supports the same command line interface as Zstandard, but also provides the `-p` option to specify the number of threads. Dictionary mode is not currently supported. Basic usage pzstd input-file -o output-file -p num-threads -# # Compression pzstd -d input-file -o output-file -p num-threads # Decompression PZstandard also supports piping and fifo pipes cat input-file | pzstd -p num-threads -# -c > /dev/null For more options pzstd --help PZstandard tries to pick a smart default number of threads if not specified (displayed in `pzstd --help`). If this number is not suitable, during compilation you can define `PZSTD_NUM_THREADS` to the number of threads you prefer. ## Benchmarks As a reference, PZstandard and Pigz were compared on an Intel Core i7 @ 3.1 GHz, each using 4 threads, with the [Silesia compression corpus](https://sun.aei.polsl.pl//~sdeor/index.php?page=silesia). Compression Speed vs Ratio with 4 Threads | Decompression Speed with 4 Threads ------------------------------------------|----------------------------------- | The test procedure was to run each of the following commands 2 times for each compression level, and take the minimum time. time pzstd -# -p 4 -c silesia.tar > silesia.tar.zst time pzstd -d -p 4 -c silesia.tar.zst > /dev/null time pigz -# -p 4 -k -c silesia.tar > silesia.tar.gz time pigz -d -p 4 -k -c silesia.tar.gz > /dev/null PZstandard was tested using compression levels 1-19, and Pigz was tested using compression levels 1-9. Pigz cannot do parallel decompression, it simply does each of reading, decompression, and writing on separate threads. ## Tests Tests require that you have [gtest](https://github.com/google/googletest) installed. Set `GTEST_INC` and `GTEST_LIB` in `Makefile` to specify the location of the gtest headers and libraries. Alternatively, run `make googletest`, which will clone googletest and build it. Run `make tests && make check` to run tests. --- ## File: contrib/seekable_format/README.md # Zstandard Seekable Format The seekable format splits compressed data into a series of independent "frames", each compressed individually, so that decompression of a section in the middle of an archive only requires zstd to decompress at most a frame's worth of extra data, instead of the entire archive. The frames are appended, so that the decompression of the entire payload still regenerates the original content, using any compliant zstd decoder. On top of that, the seekable format generates a jump table, which makes it possible to jump directly to the position of the relevant frame when requesting only a segment of the data. The jump table is simply ignored by zstd decoders unaware of the seekable format. The format is delivered with an API to create seekable archives and to retrieve arbitrary segments inside the archive. ### Maximum Frame Size parameter When creating a seekable archive, the main parameter is the maximum frame size. At compression time, user can manually select the boundaries between segments, but they don't have to: long segments will be automatically split when larger than selected maximum frame size. Small frame sizes reduce decompression cost when requesting small segments, because the decoder will nonetheless have to decompress an entire frame to recover just a single byte from it. A good rule of thumb is to select a maximum frame size roughly equivalent to the access pattern when it's known. For example, if the application tends to request 4KB blocks, then it's a good idea to set a maximum frame size in the vicinity of 4 KB. But small frame sizes also reduce compression ratio, and increase the cost for the jump table, so there is a balance to find. In general, try to avoid really tiny frame sizes (<1 KB), which would have a large negative impact on compression ratio. --- ## File: contrib/VS2005/README.md ## Project Support Notice The VS2005 Project directory has been moved to the contrib directory in order to indicate that it will no longer be supported.