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https://github.com/rspamd/rspamd.git
synchronizováno 2024-07-29 08:17:22 +02:00
68 řádky
2.4 KiB
Markdown
68 řádky
2.4 KiB
Markdown
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aho-corasick
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==
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Aho-Corasick parallel string search, using interleaved arrays.
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Mischa Sandberg mischasan@gmail.com
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ACISM is an implementation of Aho-Corasick parallel string search,
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using an Interleaved State-transition Matrix.
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It combines the fastest possible Aho-Corasick implementation,
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with the smallest possible data structure (!).
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FEATURES
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--------
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* Fast. No hashing, no tree traversal; just a straight look-up equivalent to
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matrix[state, input-byte] per input character.
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* Tiny. On average, the whole data structure (mostly the array) takes about 2-3 bytes per
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input pattern byte. The original set of pattern strings can be reverse-generated from the machine.
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* Shareable. The state machine contains no pointers, so it can be compiled once,
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then memory-mapped by many processes.
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* Searches byte vectors, not null-terminated strings.
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Suitable for searching machine code as much as searching text.
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* DOS-proof. Well, that's an attribute of Aho-Corasick,
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so no real points for that.
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* Stream-ready. The state can be saved between calls to search data.
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DOCUMENTATION
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-------------
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The GoogleDocs description is at http://goo.gl/lE6zG
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I originally called it "psearch", but found that name was overused by other authors.
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LICENSE
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-------
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Though I've had strong suggestions to go with BSD license, I'm going with GPL2 until I figure out
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how to keep in touch with people who download and use the code. Hence the "CONTACT ME IF..." line in the license.
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GETTING STARTED
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---------------
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Download the source, type "gmake".
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"gmake install" exports lib/libacism.a, include/acism.h and bin/acism_x.
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"acism_x.c" is a good example of calling acism_create and acism_scan/acism_more.
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(If you're interested in the GNUmakefile and rules.mk,
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check my blog posts on non-recursive make, at mischasan.wordpress.com.)
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HISTORY
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-------
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The interleaved-array approach was tried and discarded in the late 70's, because the compile time was O(n^2).
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acism_create beats the problem with a "hint" array that tracks the restart points for searches.
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That, plus discarding the original idea of how to get maximal density, resulted in the tiny-fast win-win.
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ACKNOWLEDGEMENTS
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----------------
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I'd like to thank Mike Shannon, who wanted to see a machine built to make best use of L1/L2 cache.
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The change to do that doubled performance on hardware with a much larger cache than the matrix.
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Go figure.
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