NAME

       PCRE2 - Perl-compatible regular expressions (revised API)

PCRE2 PERFORMANCE

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

COMPILED PATTERN MEMORY USAGE

       Patterns are compiled by PCRE2 into a  reasonably  efficient  interpretive  code,  so  that  most  simple
       patterns  do  not  use much memory for storing the compiled version. However, there is one case where the
       memory usage of a compiled pattern can be unexpectedly large. If a parenthesized group has  a  quantifier
       with a minimum greater than 1 and/or a limited maximum, the whole group is repeated in the compiled code.
       For example, the pattern

         (abc|def){2,4}

       is compiled as if it were

         (abc|def)(abc|def)((abc|def)(abc|def)?)?

       (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 particularly if such repetitions are nested, the memory usage can become an
       embarrassment. For example, the very simple pattern

         ((ab){1,1000}c){1,3}

       uses  over  50KiB when compiled using the 8-bit library. When PCRE2 is compiled with its default internal
       pointer size of two bytes, the size limit on a compiled pattern is 65535 code  units  in  the  8-bit  and
       16-bit  libraries, and this is reached with the above pattern if the outer repetition is increased from 3
       to 4. PCRE2 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 PCRE2's "subroutine" facility.
       Re-writing the above pattern as

         ((ab)(?2){0,999}c)(?1){0,2}

       reduces the memory requirements to around 16KiB, and indeed it remains under 20KiB even  with  the  outer
       repetition  increased to 100. However, this kind of pattern is not always exactly equivalent, because any
       captures within subroutine calls are lost when the subroutine completes. If this is not a  problem,  this
       kind  of  rewriting  will  allow you to process patterns that PCRE2 cannot otherwise handle. The matching
       performance of the two different versions of the pattern are roughly the same. (This applies from release
       10.30 - things were different in earlier releases.)

STACK AND HEAP USAGE AT RUN TIME

       From  release 10.30, the interpretive (non-JIT) version of pcre2_match() uses very little system stack at
       run time. In earlier releases recursive function calls could use a great deal of stack,  and  this  could
       cause  problems, but this usage has been eliminated. Backtracking positions are now explicitly remembered
       in memory frames controlled by the code.

       The size of each frame depends on the size of pointer variables and the number of capturing parenthesized
       groups  in the pattern being matched. On a 64-bit system the frame size for a pattern with no captures is
       128 bytes. For each capturing group the size increases by 16 bytes.

       Until release 10.41, an initial 20KiB frames vector was allocated on the system  stack,  but  this  still
       caused  some  issues for multi-thread applications where each thread has a very small stack. From release
       10.41 backtracking memory frames are always held in heap memory. An initial heap allocation  is  obtained
       the  first  time  any match data block is passed to pcre2_match(). This is remembered with the match data
       block and re-used if that block is used for another match. It is freed when the match data  block  itself
       is freed.

       The  size  of  the initial block is the larger of 20KiB or ten times the pattern's frame size, unless the
       heap limit is less than this, in which case the heap limit is used. If the initial block proves to be too
       small  during  matching,  it  is replaced by a larger block, subject to the heap limit. The heap limit is
       checked only when a new block is to be allocated. Reducing the heap limit between calls to  pcre2_match()
       with the same match data block does not affect the saved block.

       In  contrast  to  pcre2_match(),  pcre2_dfa_match()  does  use  recursive  function  calls,  but only for
       processing atomic groups, lookaround assertions, and recursion within the pattern. The  original  version
       of  the  code  used  to  allocate  quite large internal workspace vectors on the stack, which caused some
       problems for some  patterns  in  environments  with  small  stacks.  From  release  10.32  the  code  for
       pcre2_dfa_match()  has  been  re-factored  to  use heap memory when necessary for internal workspace when
       recursing, though recursive function calls are still used.

       The "match depth" parameter can be used to limit the depth of function recursion, and  the  "match  heap"
       parameter to limit heap memory in pcre2_dfa_match().

PROCESSING TIME

       Certain  items  in  regular  expression  patterns  are processed more efficiently 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 PCRE2.

       Using  Unicode  character  properties  (the  \p,  \P, and \X escapes) is slow, because PCRE2 has to use a
       multi-stage table lookup 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 the PCRE2_UCP option or start the pattern with (*UCP) if you want Unicode character
       properties to be used. This can double the matching  time  for  items  such  as  \d,  when  matched  with
       pcre2_match();  the performance loss is less with a DFA matching function, and in both cases there is not
       much difference for \b.

       When a pattern begins with .* not in atomic parentheses, nor in parentheses that are  the  subject  of  a
       backreference,  and the PCRE2_DOTALL option is set, the pattern is implicitly anchored by PCRE2, since it
       can match only at the start of a subject string. If the pattern has  multiple  top-level  branches,  they
       must  all  be  anchorable. The optimization can be disabled by the PCRE2_NO_DOTSTAR_ANCHOR option, and is
       automatically disabled if the pattern contains (*PRUNE) or (*SKIP).

       If PCRE2_DOTALL is not set, PCRE2 cannot make this optimization, because the dot 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

         .*second

       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, PCRE2 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  PCRE2_DOTALL,  or  starting  the pattern with ^.* or ^.*? to indicate explicit
       anchoring. That saves PCRE2 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 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  +  repeats can match different numbers of times.) When the remainder of the pattern is such that the
       entire match is going to fail, PCRE2 has in principle to try every possible variation, and this can  take
       an extremely long time, even for relatively short strings.

       An optimization catches some of the more simple cases such as

         (a+)*b

       where a literal character follows. Before embarking on the standard matching procedure, PCRE2 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+)*\d

       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. This can often reduce memory requirements as well. As another example, consider this pattern:

         ([^<]|<(?!inet))+

       It matches from wherever it starts until it encounters "<inet" or the end of the data, and is the kind of
       pattern  that  might be used when processing an XML file. Each iteration of the outer parentheses matches
       either one character that is not "<" or a "<" that is not  followed  by  "inet".  However,  each  time  a
       parenthesis  is processed, a backtracking position is passed, so this formulation uses a memory frame for
       each matched character. For a long string, a lot of memory  is  required.  Consider  now  this  rewritten
       pattern, which matches exactly the same strings:

         ([^<]++|<(?!inet))+

       This  runs  much  faster,  because sequences of characters that do not contain "<" are "swallowed" in one
       item inside the parentheses, and a possessive quantifier is used to stop any backtracking into  the  runs
       of non-"<" characters. This version also uses a lot less memory because entry to a new set of parentheses
       happens only when a "<" character that is not followed by "inet" is encountered (and we  assume  this  is
       relatively rare).

       This  example shows that one way of optimizing performance when matching long subject strings is to write
       repeated parenthesized subpatterns to match more than one character whenever possible.

   SETTING RESOURCE LIMITS

       You can set limits on the amount of processing that takes place when matching, and on the amount of  heap
       memory  that is used. The default values of the limits are very large, and unlikely ever to operate. They
       can be changed when PCRE2 is built, and they can also be set when pcre2_match() or  pcre2_dfa_match()  is
       called.  For  details of these interfaces, see the pcre2build documentation and the section entitled "The
       match context" in the pcre2api documentation.

       The pcre2test test program has a modifier called "find_limits" which,  if  applied  to  a  subject  line,
       causes  it to find the smallest limits that allow a pattern to match. This is done by repeatedly matching
       with different limits.

AUTHOR

       Philip Hazel
       Retired from University Computing Service
       Cambridge, England.

REVISION

       Last updated: 27 July 2022
       Copyright (c) 1997-2022 University of Cambridge.