# pcre2perform

## 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.
    


## REVISION



    
           Last updated: 06 December 2022
           Copyright (c) 1997-2022 University of Cambridge.
    


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