Two  aspects  of performance are discussed below: memory usage and pro-
       cessing time. The way you express your pattern as a regular  expression
       can affect both of them.


       Patterns are compiled by PCRE into a reasonably efficient byte code, so
       that most simple patterns do not use much memory. However, there is one
       case  where  the memory usage of a compiled pattern can be unexpectedly
       large. If a parenthesized subpattern has a quantifier  with  a  minimum
       greater  than  1  and/or  a  limited  maximum,  the whole subpattern is
       repeated in the compiled code. For example, the pattern


       is compiled as if it were


       (Technical aside: It is done this way so that backtrack  points  within
       each of the repetitions can be independently maintained.)

       For  regular expressions whose quantifiers use only small numbers, this
       is not usually a problem. However, if the numbers are large,  and  par-
       ticularly  if  such repetitions are nested, the memory usage can become
       an embarrassment. For example, the very simple pattern


       uses 51K bytes when compiled. When PCRE is compiled  with  its  default
       internal  pointer  size of two bytes, the size limit on a compiled pat-
       tern is 64K, and this is reached with the above pattern  if  the  outer
       repetition is increased from 3 to 4. PCRE can be compiled to use larger
       internal pointers and thus handle larger compiled patterns, but  it  is
       better to try to rewrite your pattern to use less memory if you can.

       One  way  of reducing the memory usage for such patterns is to make use
       of PCRE's "subroutine" facility. Re-writing the above pattern as


       reduces the memory requirements to 18K, and indeed it remains under 20K
       even  with the outer repetition increased to 100. However, this pattern
       is not exactly equivalent, because the "subroutine" calls  are  treated
       as  atomic groups into which there can be no backtracking if there is a
       subsequent matching failure. Therefore, PCRE cannot  do  this  kind  of
       rewriting  automatically.   Furthermore,  there is a noticeable loss of
       speed when executing the modified pattern. Nevertheless, if the  atomic
       grouping  is  not  a  problem and the loss of speed is acceptable, this
       kind of rewriting will allow you to process patterns that  PCRE  cannot
       otherwise handle.
       Certain items in regular expression patterns are processed  more  effi-
       ciently than others. It is more efficient to use a character class like
       [aeiou]  than  a  set  of   single-character   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.

       By  default,  the  escape  sequences  \b, \d, \s, and \w, and the POSIX
       character classes such as [:alpha:]  do  not  use  Unicode  properties,
       partly for backwards compatibility, and partly for performance reasons.
       However, you can set PCRE_UCP if you want Unicode character  properties
       to  be  used.  This  can double the matching time for items such as \d,
       when matched with  pcre_exec();  the  performance  loss  is  less  with
       pcre_dfa_exec(), and in both cases there is not much difference for \b.

       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  new-
       lines,  the  pattern may match from the character immediately following
       one of them instead of from the very start. For example, the pattern


       matches 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 con-
       tain newlines, the best performance is obtained by setting PCRE_DOTALL,
       or  starting  the pattern with ^.* or ^.*? to indicate explicit anchor-
       ing. 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


       This  can  match "aaaa" in 16 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 or 4, the +
       ever, when there is no following literal this  optimization  cannot  be
       used. You can see the difference by comparing the behaviour of


       with  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.


       Philip Hazel
       University Computing Service
       Cambridge CB2 3QH, England.


       Last updated: 16 May 2010
       Copyright (c) 1997-2010 University of Cambridge.

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