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136 lines
5.6 KiB
136 lines
5.6 KiB
12 years ago
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Snappy, a fast compressor/decompressor.
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Introduction
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============
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Snappy is a compression/decompression library. It does not aim for maximum
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compression, or compatibility with any other compression library; instead,
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it aims for very high speeds and reasonable compression. For instance,
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compared to the fastest mode of zlib, Snappy is an order of magnitude faster
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for most inputs, but the resulting compressed files are anywhere from 20% to
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100% bigger. (For more information, see "Performance", below.)
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Snappy has the following properties:
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* Fast: Compression speeds at 250 MB/sec and beyond, with no assembler code.
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See "Performance" below.
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* Stable: Over the last few years, Snappy has compressed and decompressed
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petabytes of data in Google's production environment. The Snappy bitstream
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format is stable and will not change between versions.
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* Robust: The Snappy decompressor is designed not to crash in the face of
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corrupted or malicious input.
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* Free and open source software: Snappy is licensed under a BSD-type license.
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For more information, see the included COPYING file.
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Snappy has previously been called "Zippy" in some Google presentations
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and the like.
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Performance
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===========
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Snappy is intended to be fast. On a single core of a Core i7 processor
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in 64-bit mode, it compresses at about 250 MB/sec or more and decompresses at
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about 500 MB/sec or more. (These numbers are for the slowest inputs in our
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benchmark suite; others are much faster.) In our tests, Snappy usually
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is faster than algorithms in the same class (e.g. LZO, LZF, FastLZ, QuickLZ,
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etc.) while achieving comparable compression ratios.
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Typical compression ratios (based on the benchmark suite) are about 1.5-1.7x
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for plain text, about 2-4x for HTML, and of course 1.0x for JPEGs, PNGs and
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other already-compressed data. Similar numbers for zlib in its fastest mode
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are 2.6-2.8x, 3-7x and 1.0x, respectively. More sophisticated algorithms are
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capable of achieving yet higher compression rates, although usually at the
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expense of speed. Of course, compression ratio will vary significantly with
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the input.
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Although Snappy should be fairly portable, it is primarily optimized
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for 64-bit x86-compatible processors, and may run slower in other environments.
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In particular:
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- Snappy uses 64-bit operations in several places to process more data at
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once than would otherwise be possible.
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- Snappy assumes unaligned 32- and 64-bit loads and stores are cheap.
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On some platforms, these must be emulated with single-byte loads
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and stores, which is much slower.
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- Snappy assumes little-endian throughout, and needs to byte-swap data in
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several places if running on a big-endian platform.
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Experience has shown that even heavily tuned code can be improved.
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Performance optimizations, whether for 64-bit x86 or other platforms,
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are of course most welcome; see "Contact", below.
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Usage
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=====
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Note that Snappy, both the implementation and the main interface,
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is written in C++. However, several third-party bindings to other languages
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are available; see the Google Code page at http://code.google.com/p/snappy/
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for more information. Also, if you want to use Snappy from C code, you can
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use the included C bindings in snappy-c.h.
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To use Snappy from your own C++ program, include the file "snappy.h" from
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your calling file, and link against the compiled library.
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There are many ways to call Snappy, but the simplest possible is
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snappy::Compress(input.data(), input.size(), &output);
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and similarly
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snappy::Uncompress(input.data(), input.size(), &output);
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where "input" and "output" are both instances of std::string.
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There are other interfaces that are more flexible in various ways, including
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support for custom (non-array) input sources. See the header file for more
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information.
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Tests and benchmarks
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====================
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When you compile Snappy, snappy_unittest is compiled in addition to the
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library itself. You do not need it to use the compressor from your own library,
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but it contains several useful components for Snappy development.
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First of all, it contains unit tests, verifying correctness on your machine in
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various scenarios. If you want to change or optimize Snappy, please run the
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tests to verify you have not broken anything. Note that if you have the
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Google Test library installed, unit test behavior (especially failures) will be
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significantly more user-friendly. You can find Google Test at
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http://code.google.com/p/googletest/
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You probably also want the gflags library for handling of command-line flags;
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you can find it at
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http://code.google.com/p/google-gflags/
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In addition to the unit tests, snappy contains microbenchmarks used to
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tune compression and decompression performance. These are automatically run
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before the unit tests, but you can disable them using the flag
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--run_microbenchmarks=false if you have gflags installed (otherwise you will
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need to edit the source).
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Finally, snappy can benchmark Snappy against a few other compression libraries
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(zlib, LZO, LZF, FastLZ and QuickLZ), if they were detected at configure time.
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To benchmark using a given file, give the compression algorithm you want to test
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Snappy against (e.g. --zlib) and then a list of one or more file names on the
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command line. The testdata/ directory contains the files used by the
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microbenchmark, which should provide a reasonably balanced starting point for
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benchmarking. (Note that baddata[1-3].snappy are not intended as benchmarks; they
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are used to verify correctness in the presence of corrupted data in the unit
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test.)
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Contact
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=======
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Snappy is distributed through Google Code. For the latest version, a bug tracker,
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and other information, see
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http://code.google.com/p/snappy/
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