mirror of https://github.com/google/snappy.git
b2312c4c25
Uncompress(source, sink) to get the same performance as the different variants of Uncompress to Cord/DataBuffer/String/FlatBuffer. Changes to efficiently support Uncompress(source, sink) -------- a) For strings - we add support to StringByteSink to do GetAppendBuffer so we can write to it without copying. b) For flat array buffers, we do GetAppendBuffer and see if we can get a full buffer. With the above changes we get performance with ByteSource/ByteSink that is very close to directly using flat arrays and strings. We add various benchmark cases to demonstrate that. Orthogonal change ------------------ Add support for TryFastAppend() for SnappyScatteredWriter. Benchmark results are below CPU: Intel Core2 dL1:32KB dL2:4096KB Benchmark Time(ns) CPU(ns) Iterations ----------------------------------------------------- BM_UFlat/0 109065 108996 6410 896.0MB/s html BM_UFlat/1 1012175 1012343 691 661.4MB/s urls BM_UFlat/2 26775 26771 26149 4.4GB/s jpg BM_UFlat/3 48947 48940 14363 1.8GB/s pdf BM_UFlat/4 441029 440835 1589 886.1MB/s html4 BM_UFlat/5 39861 39880 17823 588.3MB/s cp BM_UFlat/6 18315 18300 38126 581.1MB/s c BM_UFlat/7 5254 5254 100000 675.4MB/s lsp BM_UFlat/8 1568060 1567376 447 626.6MB/s xls BM_UFlat/9 337512 337734 2073 429.5MB/s txt1 BM_UFlat/10 287269 287054 2434 415.9MB/s txt2 BM_UFlat/11 890098 890219 787 457.2MB/s txt3 BM_UFlat/12 1186593 1186863 590 387.2MB/s txt4 BM_UFlat/13 573927 573318 1000 853.7MB/s bin BM_UFlat/14 64250 64294 10000 567.2MB/s sum BM_UFlat/15 7301 7300 96153 552.2MB/s man BM_UFlat/16 109617 109636 6375 1031.5MB/s pb BM_UFlat/17 364438 364497 1921 482.3MB/s gaviota BM_UFlatSink/0 108518 108465 6450 900.4MB/s html BM_UFlatSink/1 991952 991997 705 675.0MB/s urls BM_UFlatSink/2 26815 26798 26065 4.4GB/s jpg BM_UFlatSink/3 49127 49122 14255 1.8GB/s pdf BM_UFlatSink/4 436674 436731 1604 894.4MB/s html4 BM_UFlatSink/5 39738 39733 17345 590.5MB/s cp BM_UFlatSink/6 18413 18416 37962 577.4MB/s c BM_UFlatSink/7 5677 5676 100000 625.2MB/s lsp BM_UFlatSink/8 1552175 1551026 451 633.2MB/s xls BM_UFlatSink/9 338526 338489 2065 428.5MB/s txt1 BM_UFlatSink/10 289387 289307 2420 412.6MB/s txt2 BM_UFlatSink/11 893803 893706 783 455.4MB/s txt3 BM_UFlatSink/12 1195919 1195459 586 384.4MB/s txt4 BM_UFlatSink/13 559637 559779 1000 874.3MB/s bin BM_UFlatSink/14 65073 65094 10000 560.2MB/s sum BM_UFlatSink/15 7618 7614 92823 529.5MB/s man BM_UFlatSink/16 110085 110121 6352 1027.0MB/s pb BM_UFlatSink/17 369196 368915 1896 476.5MB/s gaviota BM_UValidate/0 46954 46957 14899 2.0GB/s html BM_UValidate/1 500621 500868 1000 1.3GB/s urls BM_UValidate/2 283 283 2481447 417.2GB/s jpg BM_UValidate/3 16230 16228 43137 5.4GB/s pdf BM_UValidate/4 189129 189193 3701 2.0GB/s html4 A=uday R=sanjay |
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m4 | ||
testdata | ||
AUTHORS | ||
COPYING | ||
ChangeLog | ||
Makefile.am | ||
NEWS | ||
README | ||
autogen.sh | ||
configure.ac | ||
format_description.txt | ||
framing_format.txt | ||
snappy-c.cc | ||
snappy-c.h | ||
snappy-internal.h | ||
snappy-sinksource.cc | ||
snappy-sinksource.h | ||
snappy-stubs-internal.cc | ||
snappy-stubs-internal.h | ||
snappy-stubs-public.h.in | ||
snappy-test.cc | ||
snappy-test.h | ||
snappy.cc | ||
snappy.h | ||
snappy_unittest.cc |
README
Snappy, a fast compressor/decompressor. Introduction ============ Snappy is a compression/decompression library. It does not aim for maximum compression, or compatibility with any other compression library; instead, it aims for very high speeds and reasonable compression. For instance, compared to the fastest mode of zlib, Snappy is an order of magnitude faster for most inputs, but the resulting compressed files are anywhere from 20% to 100% bigger. (For more information, see "Performance", below.) Snappy has the following properties: * Fast: Compression speeds at 250 MB/sec and beyond, with no assembler code. See "Performance" below. * Stable: Over the last few years, Snappy has compressed and decompressed petabytes of data in Google's production environment. The Snappy bitstream format is stable and will not change between versions. * Robust: The Snappy decompressor is designed not to crash in the face of corrupted or malicious input. * Free and open source software: Snappy is licensed under a BSD-type license. For more information, see the included COPYING file. Snappy has previously been called "Zippy" in some Google presentations and the like. Performance =========== Snappy is intended to be fast. On a single core of a Core i7 processor in 64-bit mode, it compresses at about 250 MB/sec or more and decompresses at about 500 MB/sec or more. (These numbers are for the slowest inputs in our benchmark suite; others are much faster.) In our tests, Snappy usually is faster than algorithms in the same class (e.g. LZO, LZF, FastLZ, QuickLZ, etc.) while achieving comparable compression ratios. Typical compression ratios (based on the benchmark suite) are about 1.5-1.7x for plain text, about 2-4x for HTML, and of course 1.0x for JPEGs, PNGs and other already-compressed data. Similar numbers for zlib in its fastest mode are 2.6-2.8x, 3-7x and 1.0x, respectively. More sophisticated algorithms are capable of achieving yet higher compression rates, although usually at the expense of speed. Of course, compression ratio will vary significantly with the input. Although Snappy should be fairly portable, it is primarily optimized for 64-bit x86-compatible processors, and may run slower in other environments. In particular: - Snappy uses 64-bit operations in several places to process more data at once than would otherwise be possible. - Snappy assumes unaligned 32- and 64-bit loads and stores are cheap. On some platforms, these must be emulated with single-byte loads and stores, which is much slower. - Snappy assumes little-endian throughout, and needs to byte-swap data in several places if running on a big-endian platform. Experience has shown that even heavily tuned code can be improved. Performance optimizations, whether for 64-bit x86 or other platforms, are of course most welcome; see "Contact", below. Usage ===== Note that Snappy, both the implementation and the main interface, is written in C++. However, several third-party bindings to other languages are available; see the Google Code page at http://code.google.com/p/snappy/ for more information. Also, if you want to use Snappy from C code, you can use the included C bindings in snappy-c.h. To use Snappy from your own C++ program, include the file "snappy.h" from your calling file, and link against the compiled library. There are many ways to call Snappy, but the simplest possible is snappy::Compress(input.data(), input.size(), &output); and similarly snappy::Uncompress(input.data(), input.size(), &output); where "input" and "output" are both instances of std::string. There are other interfaces that are more flexible in various ways, including support for custom (non-array) input sources. See the header file for more information. Tests and benchmarks ==================== When you compile Snappy, snappy_unittest is compiled in addition to the library itself. You do not need it to use the compressor from your own library, but it contains several useful components for Snappy development. First of all, it contains unit tests, verifying correctness on your machine in various scenarios. If you want to change or optimize Snappy, please run the tests to verify you have not broken anything. Note that if you have the Google Test library installed, unit test behavior (especially failures) will be significantly more user-friendly. You can find Google Test at http://code.google.com/p/googletest/ You probably also want the gflags library for handling of command-line flags; you can find it at http://code.google.com/p/google-gflags/ In addition to the unit tests, snappy contains microbenchmarks used to tune compression and decompression performance. These are automatically run before the unit tests, but you can disable them using the flag --run_microbenchmarks=false if you have gflags installed (otherwise you will need to edit the source). Finally, snappy can benchmark Snappy against a few other compression libraries (zlib, LZO, LZF, FastLZ and QuickLZ), if they were detected at configure time. To benchmark using a given file, give the compression algorithm you want to test Snappy against (e.g. --zlib) and then a list of one or more file names on the command line. The testdata/ directory contains the files used by the microbenchmark, which should provide a reasonably balanced starting point for benchmarking. (Note that baddata[1-3].snappy are not intended as benchmarks; they are used to verify correctness in the presence of corrupted data in the unit test.) Contact ======= Snappy is distributed through Google Code. For the latest version, a bug tracker, and other information, see http://code.google.com/p/snappy/