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A lookbehind constraint is like a lookahead constraint in that it consumes
no text; but it checks for existence (or nonexistence) of a match *ending*
at the current point in the string, rather than one *starting* at the
current point. This is a long-requested feature since it exists in many
other regex libraries, but Henry Spencer had never got around to
implementing it in the code we use.
Just making it work is actually pretty trivial; but naive copying of the
logic for lookahead constraints leads to code that often spends O(N^2) time
to scan an N-character string, because we have to run the match engine
from string start to the current probe point each time the constraint is
checked. In typical use-cases a lookbehind constraint will be written at
the start of the regex and hence will need to be checked at every character
--- so O(N^2) work overall. To fix that, I introduced a third copy of the
core DFA matching loop, paralleling the existing longest() and shortest()
loops. This version, matchuntil(), can suspend and resume matching given
a couple of pointers' worth of storage space. So we need only run it
across the string once, stopping at each interesting probe point and then
resuming to advance to the next one.
I also put in an optimization that simplifies one-character lookahead and
lookbehind constraints, such as "(?=x)" or "(?<!\w)", into AHEAD and BEHIND
constraints, which already existed in the engine. This avoids the overhead
of the LACON machinery entirely for these rather common cases.
The net result is that lookbehind constraints run a factor of three or so
slower than Perl's for multi-character constraints, but faster than Perl's
for one-character constraints ... and they work fine for variable-length
constraints, which Perl gives up on entirely. So that's not bad from a
competitive perspective, and there's room for further optimization if
anyone cares. (In reality, raw scan rate across a large input string is
probably not that big a deal for Postgres usage anyway; so I'm happy if
it's linear.)
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This works by extracting trigrams from the given regular expression,
in generally the same spirit as the previously-existing support for
LIKE searches, though of course the details are far more complicated.
Currently, only GIN indexes are supported. We might be able to make
it work with GiST indexes later.
The implementation includes adding API functions to backend/regex/
to provide a view of the search NFA created from a regular expression.
These functions are meant to be generic enough to be supportable in
a standalone version of the regex library, should that ever happen.
Alexander Korotkov, reviewed by Heikki Linnakangas and Tom Lane
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