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PCRE PERFORMANCE
Certain items that may appear in regular expression patterns are more efficient than others. It is more efficient to use a character class like [aeiou] than a set of alternatives such as (a|e|i|o|u). In general, the simplest construction that provides the required behaviour is usually the most efficient. Jeffrey Friedl's book contains a lot of useful general discussion about optimizing regular expressions for efficient performance. This document contains a few observations about PCRE.
Using Unicode character properties (the \p, \P, and \X escapes) is slow, because PCRE has to scan a structure that contains data for over fifteen thousand characters whenever it needs a character's property. If you can find an alternative pattern that does not use character properties, it will probably be faster.
When a pattern begins with .* not in parentheses, or in parentheses that are not the subject of a backreference, and the PCRE_DOTALL option is set, the pattern is implicitly anchored by PCRE, since it can match only at the start of a subject string. However, if PCRE_DOTALL is not set, PCRE cannot make this optimization, because the . metacharacter does not then match a newline, and if the subject string contains newlines, the pattern may match from the character immediately following one of them instead of from the very start. For example, the pattern
.*secondmatches the subject "first\nand second" (where \n stands for a newline character), with the match starting at the seventh character. In order to do this, PCRE has to retry the match starting after every newline in the subject.
If you are using such a pattern with subject strings that do not contain newlines, the best performance is obtained by setting PCRE_DOTALL, or starting the pattern with ^.* to indicate explicit anchoring. That saves PCRE from having to scan along the subject looking for a newline to restart at.
Beware of patterns that contain nested indefinite repeats. These can take a long time to run when applied to a string that does not match. Consider the pattern fragment
(a+)*This can match "aaaa" in 33 different ways, and this number increases very rapidly as the string gets longer. (The * repeat can match 0, 1, 2, 3, or 4 times, and for each of those cases other than 0, the + repeats can match different numbers of times.) When the remainder of the pattern is such that the entire match is going to fail, PCRE has in principle to try every possible variation, and this can take an extremely long time.
An optimization catches some of the more simple cases such as
(a+)*bwhere a literal character follows. Before embarking on the standard matching procedure, PCRE checks that there is a "b" later in the subject string, and if there is not, it fails the match immediately. However, when there is no following literal this optimization cannot be used. You can see the difference by comparing the behaviour of
(a+)*\dwith the pattern above. The former gives a failure almost instantly when applied to a whole line of "a" characters, whereas the latter takes an appreciable time with strings longer than about 20 characters.
In many cases, the solution to this kind of performance issue is to use an atomic group or a possessive quantifier.
Last updated: 09 September 2004
Copyright © 1997-2004 University of Cambridge.
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