261 lines
11 KiB
Groff
261 lines
11 KiB
Groff
.TH PCRE2PERFORM 3 "27 July 2022" "PCRE2 10.41"
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.SH NAME
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PCRE2 - Perl-compatible regular expressions (revised API)
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.SH "PCRE2 PERFORMANCE"
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.rs
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.sp
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Two aspects of performance are discussed below: memory usage and processing
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time. The way you express your pattern as a regular expression can affect both
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of them.
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.
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.SH "COMPILED PATTERN MEMORY USAGE"
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.rs
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.sp
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Patterns are compiled by PCRE2 into a reasonably efficient interpretive code,
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so that most simple patterns do not use much memory for storing the compiled
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version. However, there is one case where the memory usage of a compiled
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pattern can be unexpectedly large. If a parenthesized group has a quantifier
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with a minimum greater than 1 and/or a limited maximum, the whole group is
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repeated in the compiled code. For example, the pattern
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.sp
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(abc|def){2,4}
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.sp
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is compiled as if it were
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.sp
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(abc|def)(abc|def)((abc|def)(abc|def)?)?
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.sp
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(Technical aside: It is done this way so that backtrack points within each of
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the repetitions can be independently maintained.)
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.P
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For regular expressions whose quantifiers use only small numbers, this is not
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usually a problem. However, if the numbers are large, and particularly if such
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repetitions are nested, the memory usage can become an embarrassment. For
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example, the very simple pattern
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.sp
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((ab){1,1000}c){1,3}
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.sp
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uses over 50KiB when compiled using the 8-bit library. When PCRE2 is
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compiled with its default internal pointer size of two bytes, the size limit on
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a compiled pattern is 65535 code units in the 8-bit and 16-bit libraries, and
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this is reached with the above pattern if the outer repetition is increased
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from 3 to 4. PCRE2 can be compiled to use larger internal pointers and thus
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handle larger compiled patterns, but it is better to try to rewrite your
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pattern to use less memory if you can.
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.P
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One way of reducing the memory usage for such patterns is to make use of
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PCRE2's
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.\" HTML <a href="pcre2pattern.html#subpatternsassubroutines">
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.\" </a>
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"subroutine"
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.\"
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facility. Re-writing the above pattern as
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.sp
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((ab)(?2){0,999}c)(?1){0,2}
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.sp
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reduces the memory requirements to around 16KiB, and indeed it remains under
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20KiB even with the outer repetition increased to 100. However, this kind of
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pattern is not always exactly equivalent, because any captures within
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subroutine calls are lost when the subroutine completes. If this is not a
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problem, this kind of rewriting will allow you to process patterns that PCRE2
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cannot otherwise handle. The matching performance of the two different versions
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of the pattern are roughly the same. (This applies from release 10.30 - things
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were different in earlier releases.)
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.
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.
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.SH "STACK AND HEAP USAGE AT RUN TIME"
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.rs
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.sp
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From release 10.30, the interpretive (non-JIT) version of \fBpcre2_match()\fP
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uses very little system stack at run time. In earlier releases recursive
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function calls could use a great deal of stack, and this could cause problems,
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but this usage has been eliminated. Backtracking positions are now explicitly
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remembered in memory frames controlled by the code.
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.P
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The size of each frame depends on the size of pointer variables and the number
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of capturing parenthesized groups in the pattern being matched. On a 64-bit
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system the frame size for a pattern with no captures is 128 bytes. For each
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capturing group the size increases by 16 bytes.
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.P
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Until release 10.41, an initial 20KiB frames vector was allocated on the system
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stack, but this still caused some issues for multi-thread applications where
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each thread has a very small stack. From release 10.41 backtracking memory
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frames are always held in heap memory. An initial heap allocation is obtained
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the first time any match data block is passed to \fBpcre2_match()\fP. This is
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remembered with the match data block and re-used if that block is used for
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another match. It is freed when the match data block itself is freed.
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.P
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The size of the initial block is the larger of 20KiB or ten times the pattern's
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frame size, unless the heap limit is less than this, in which case the heap
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limit is used. If the initial block proves to be too small during matching, it
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is replaced by a larger block, subject to the heap limit. The heap limit is
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checked only when a new block is to be allocated. Reducing the heap limit
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between calls to \fBpcre2_match()\fP with the same match data block does not
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affect the saved block.
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.P
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In contrast to \fBpcre2_match()\fP, \fBpcre2_dfa_match()\fP does use recursive
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function calls, but only for processing atomic groups, lookaround assertions,
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and recursion within the pattern. The original version of the code used to
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allocate quite large internal workspace vectors on the stack, which caused some
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problems for some patterns in environments with small stacks. From release
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10.32 the code for \fBpcre2_dfa_match()\fP has been re-factored to use heap
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memory when necessary for internal workspace when recursing, though recursive
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function calls are still used.
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.P
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The "match depth" parameter can be used to limit the depth of function
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recursion, and the "match heap" parameter to limit heap memory in
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\fBpcre2_dfa_match()\fP.
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.
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.
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.SH "PROCESSING TIME"
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.rs
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.sp
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Certain items in regular expression patterns are processed more efficiently
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than others. It is more efficient to use a character class like [aeiou] than a
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set of single-character alternatives such as (a|e|i|o|u). In general, the
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simplest construction that provides the required behaviour is usually the most
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efficient. Jeffrey Friedl's book contains a lot of useful general discussion
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about optimizing regular expressions for efficient performance. This document
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contains a few observations about PCRE2.
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.P
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Using Unicode character properties (the \ep, \eP, and \eX escapes) is slow,
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because PCRE2 has to use a multi-stage table lookup whenever it needs a
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character's property. If you can find an alternative pattern that does not use
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character properties, it will probably be faster.
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.P
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By default, the escape sequences \eb, \ed, \es, and \ew, and the POSIX
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character classes such as [:alpha:] do not use Unicode properties, partly for
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backwards compatibility, and partly for performance reasons. However, you can
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set the PCRE2_UCP option or start the pattern with (*UCP) if you want Unicode
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character properties to be used. This can double the matching time for items
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such as \ed, when matched with \fBpcre2_match()\fP; the performance loss is
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less with a DFA matching function, and in both cases there is not much
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difference for \eb.
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.P
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When a pattern begins with .* not in atomic parentheses, nor in parentheses
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that are the subject of a backreference, and the PCRE2_DOTALL option is set,
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the pattern is implicitly anchored by PCRE2, since it can match only at the
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start of a subject string. If the pattern has multiple top-level branches, they
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must all be anchorable. The optimization can be disabled by the
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PCRE2_NO_DOTSTAR_ANCHOR option, and is automatically disabled if the pattern
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contains (*PRUNE) or (*SKIP).
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.P
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If PCRE2_DOTALL is not set, PCRE2 cannot make this optimization, because the
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dot metacharacter does not then match a newline, and if the subject string
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contains newlines, the pattern may match from the character immediately
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following one of them instead of from the very start. For example, the pattern
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.sp
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.*second
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.sp
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matches the subject "first\enand second" (where \en stands for a newline
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character), with the match starting at the seventh character. In order to do
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this, PCRE2 has to retry the match starting after every newline in the subject.
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.P
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If you are using such a pattern with subject strings that do not contain
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newlines, the best performance is obtained by setting PCRE2_DOTALL, or starting
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the pattern with ^.* or ^.*? to indicate explicit anchoring. That saves PCRE2
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from having to scan along the subject looking for a newline to restart at.
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.P
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Beware of patterns that contain nested indefinite repeats. These can take a
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long time to run when applied to a string that does not match. Consider the
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pattern fragment
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.sp
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^(a+)*
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.sp
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This can match "aaaa" in 16 different ways, and this number increases very
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rapidly as the string gets longer. (The * repeat can match 0, 1, 2, 3, or 4
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times, and for each of those cases other than 0 or 4, the + repeats can match
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different numbers of times.) When the remainder of the pattern is such that the
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entire match is going to fail, PCRE2 has in principle to try every possible
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variation, and this can take an extremely long time, even for relatively short
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strings.
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.P
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An optimization catches some of the more simple cases such as
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.sp
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(a+)*b
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.sp
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where a literal character follows. Before embarking on the standard matching
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procedure, PCRE2 checks that there is a "b" later in the subject string, and if
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there is not, it fails the match immediately. However, when there is no
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following literal this optimization cannot be used. You can see the difference
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by comparing the behaviour of
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.sp
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(a+)*\ed
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.sp
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with the pattern above. The former gives a failure almost instantly when
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applied to a whole line of "a" characters, whereas the latter takes an
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appreciable time with strings longer than about 20 characters.
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.P
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In many cases, the solution to this kind of performance issue is to use an
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atomic group or a possessive quantifier. This can often reduce memory
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requirements as well. As another example, consider this pattern:
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.sp
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([^<]|<(?!inet))+
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.sp
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It matches from wherever it starts until it encounters "<inet" or the end of
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the data, and is the kind of pattern that might be used when processing an XML
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file. Each iteration of the outer parentheses matches either one character that
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is not "<" or a "<" that is not followed by "inet". However, each time a
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parenthesis is processed, a backtracking position is passed, so this
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formulation uses a memory frame for each matched character. For a long string,
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a lot of memory is required. Consider now this rewritten pattern, which matches
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exactly the same strings:
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.sp
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([^<]++|<(?!inet))+
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.sp
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This runs much faster, because sequences of characters that do not contain "<"
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are "swallowed" in one item inside the parentheses, and a possessive quantifier
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is used to stop any backtracking into the runs of non-"<" characters. This
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version also uses a lot less memory because entry to a new set of parentheses
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happens only when a "<" character that is not followed by "inet" is encountered
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(and we assume this is relatively rare).
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.P
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This example shows that one way of optimizing performance when matching long
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subject strings is to write repeated parenthesized subpatterns to match more
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than one character whenever possible.
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.
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.
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.SS "SETTING RESOURCE LIMITS"
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.rs
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.sp
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You can set limits on the amount of processing that takes place when matching,
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and on the amount of heap memory that is used. The default values of the limits
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are very large, and unlikely ever to operate. They can be changed when PCRE2 is
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built, and they can also be set when \fBpcre2_match()\fP or
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\fBpcre2_dfa_match()\fP is called. For details of these interfaces, see the
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.\" HREF
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\fBpcre2build\fP
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.\"
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documentation and the section entitled
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.\" HTML <a href="pcre2api.html#matchcontext">
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.\" </a>
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"The match context"
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.\"
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in the
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.\" HREF
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\fBpcre2api\fP
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.\"
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documentation.
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.P
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The \fBpcre2test\fP test program has a modifier called "find_limits" which, if
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applied to a subject line, causes it to find the smallest limits that allow a
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pattern to match. This is done by repeatedly matching with different limits.
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.
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.
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.SH AUTHOR
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.rs
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.sp
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.nf
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Philip Hazel
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Retired from University Computing Service
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Cambridge, England.
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.fi
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.
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.
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.SH REVISION
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.rs
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.sp
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.nf
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Last updated: 27 July 2022
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Copyright (c) 1997-2022 University of Cambridge.
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.fi
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