wildspeed

WildSpeed - fast wildcard search for LIKE operator

Wildspeed extension provides GIN index support for wildcard search for LIKE operator.

Online version of this document is available http://www.sai.msu.su/~megera/wiki/wildspeed

Authors

  • Oleg Bartunov <oleg@sai.msu.su>, Moscow, Moscow University, Russia
  • Teodor Sigaev <teodor@sigaev.ru>, Moscow, Moscow University,Russia

License

Stable version, included into PostgreSQL distribution, released under BSD license. Development version, available from this site, released under the GNU General Public License, version 2 (June 1991)

Downloads

Latest version of wildspeed is available from git clone git://sigaev.ru/wildspeed

Installation

% cd PGSQLSRC/contrib
% tar xzvf wildspeed.tar.gz
% make
% make install
% make installcheck
% psql regression < wildspeed.sql

Wildspeed provides opclass (wildcard_ops) and uses partial match feature of GIN, available since 8.4. Also, it supports full index scan.

The size of index can be very big, since it contains entries for all permutations of the original word, see [1] for details. For example, word hello will be indexed as well as its all permutations:

=# select permute('hello');
               permute                
--------------------------------------
 {hello$,ello$h,llo$he,lo$hel,o$hell}

Notice, symbol '$' is used only for visualization, in actual implementation null-symbol '\0' is used.

Search query rewritten as prefix search:

*X  -> X$*
X*Y -> Y$X*
*X* -> X*

For example, search for 'hel*o' will be rewritten as 'o$hel'.

Special function permute(TEXT), which returns all permutations of argument, provided for test purposes.

Performance of wildspeed depends on search pattern. Basically, wildspeed is less effective than btree index with text_pattern_ops for prefix search (the difference is greatly reduced for long prefixes) and much faster for wildcard search.

Wildspeed by default uses optimization (skip short patterns if there are long one), which can be turned off in Makefile by removing define -DOPTIMIZE_WILDCARD_QUERY.

References

1. http://www.cs.wright.edu/~tkprasad/courses/cs499/L05TolerantIR.ppt, see also, http://nlp.stanford.edu/IR-book/html/htmledition/permuterm-indexes-1.html

Examples

Table words contains 747358 records, w1 and w2 columns contains the same data in order to test performance of Btree (w1) and GIN (w2) indexes:

   Table "public.words"
 Column | Type | Modifiers
--------+------+-----------
 w1     | text |
 w2     | text |

words=# create index bt_idx on words using btree (w1 text_pattern_ops);
CREATE INDEX
Time: 1885.195 ms
words=# create index gin_idx on words using gin (w2 wildcard_ops);
vacuum analyze;
CREATE INDEX
Time: 530351.223 ms

Size:

words=# select pg_relation_size('words');
 pg_relation_size
------------------
         43253760

words=# select pg_relation_size('gin_idx');
 pg_relation_size
------------------
        417816576
(1 row)

words=# select pg_relation_size('bt_idx');
 pg_relation_size
------------------
         23437312
(1 row)

Prefix search:

words=# select count(*) from words where w1 like 'a%';
 count
-------
 15491
(1 row)

Time: 7.502 ms
words=# select count(*) from words where w2 like 'a%';
 count
-------
 15491
(1 row)

Time: 31.152 ms

Wildcard search:

words=# select count(*) from words where w1 like '%asd%';
 count
-------
    26
(1 row)

Time: 147.308 ms
words=# select count(*) from words where w2 like '%asd%';
 count
-------
    26
(1 row)

Time: 0.339 ms

Full index scan:

words=# set enable_seqscan to off;
words=# explain analyze select count(*) from words where w2 like '%';
                                                                QUERY PLAN

--------------------------------------------------------------------------------------------------------------
-----------------------------
 Aggregate  (cost=226274.98..226274.99 rows=1 width=0) (actual time=2218.709..2218.709 rows=1 loops=1)
   ->  Bitmap Heap Scan on words  (cost=209785.73..224406.77 rows=747283 width=0) (actual time=1510.516..1913.
430 rows=747358 loops=1)
         Filter: (w2 ~~ '%'::text)
         ->  Bitmap Index Scan on gin_idx  (cost=0.00..209598.91 rows=747283 width=0) (actual time=1509.358..1
509.358 rows=747358 loops=1)
               Index Cond: (w2 ~~ '%'::text)
 Total runtime: 2218.747 ms
(6 rows)

How to combine fast prefix search and fast substring search ? The solution is to create two indexes - btree and wildspeed, optimizer will choose the most efficient index.