The rum module provides access method to work with RUM index. It is based on the GIN access methods code.

GIN index allows to perform fast full text search using tsvector and tsquery types. But full text search with GIN index has several problems:

• Slow ranking. It is need position information about lexems to ranking. GIN index doesn't store positions of lexems. So after index scan we need additional heap scan to retreive lexems positions.
• Slow phrase search with GIN index. This problem relates with previous problem. It is need position information to perform phrase search.
• Slow ordering by timestamp. GIN index can't store some related information in index with lexemes. So it is necessary to perform additional heap scan.

RUM solves this problems by storing additional information in posting tree. For example, positional information of lexemes or timestamps. You can get an idea of RUM by the following picture:

Drawback of RUM is that it has slower build and insert time than GIN. It is because we need to store additional information besides keys and because RUM uses generic WAL.

This module available under the same license as PostgreSQL.

Before build and install rum you should ensure following:

• PostgreSQL version is 9.6+.

Typical installation procedure may look like this:

$ git clone https://github.com/postgrespro/rum
$ cd rum
$ make USE_PGXS=1
$ sudo make USE_PGXS=1 install
$ make USE_PGXS=1 installcheck
$ psql DB -c "CREATE EXTENSION rum;"

rum module provides next operators.

rum provides next operator classes.

For type: tsvector

This operator class stores tsvector lexemes with positional information. Supports ordering by <=> operator and prefix search. There is the example.

Let us assume we have the table:

CREATE TABLE test_rum(t text, a tsvector);

CREATE TRIGGER tsvectorupdate
BEFORE UPDATE OR INSERT ON test_rum
FOR EACH ROW EXECUTE PROCEDURE tsvector_update_trigger('a', 'pg_catalog.english', 't');

INSERT INTO test_rum(t) VALUES ('The situation is most beautiful');
INSERT INTO test_rum(t) VALUES ('It is a beautiful');
INSERT INTO test_rum(t) VALUES ('It looks like a beautiful place');

To create the rum index we need create an extension:

CREATE EXTENSION rum;

Then we can create new index:

CREATE INDEX rumidx ON test_rum USING rum (a rum_tsvector_ops);

And we can execute the following queries:

SELECT t, a <=> to_tsquery('english', 'beautiful | place') AS rank
    FROM test_rum
    WHERE a @@ to_tsquery('english', 'beautiful | place')
    ORDER BY a <=> to_tsquery('english', 'beautiful | place');
                t                |   rank
---------------------------------+-----------
 The situation is most beautiful | 0.0303964
 It is a beautiful               | 0.0303964
 It looks like a beautiful place | 0.0607927
(3 rows)

SELECT t, a <=> to_tsquery('english', 'place | situation') AS rank
    FROM test_rum
    WHERE a @@ to_tsquery('english', 'place | situation')
    ORDER BY a <=> to_tsquery('english', 'place | situation');
                t                |   rank
---------------------------------+-----------
 The situation is most beautiful | 0.0303964
 It looks like a beautiful place | 0.0303964
(2 rows)

For type: tsvector

This operator class stores hash of tsvector lexemes with positional information. Supports ordering by <=> operator. But doesn't support prefix search.

For type: timestamp

Operator class provides fast search and ordering by timestamp fields. Supports ordering by <=>, <=| and |=> operators. Can be used with rum_tsvector_timestamp_ops operator class.

For type: timestamptz

Operator class provides fast search and ordering by timestamptz fields. Supports ordering by <=>, <=| and |=> operators. Can be used with rum_tsvector_timestamptz_ops operator class.

For type: tsvector

This operator class stores tsvector lexems with timestamp field. There is the example.

Let us assume we have the table:

CREATE TABLE tsts (id int, t tsvector, d timestamp);

\copy tsts from 'rum/data/tsts.data'

CREATE INDEX tsts_idx ON tsts USING rum (t rum_tsvector_timestamp_ops, d)
    WITH (attach = 'd', to = 't');

Now we can execute the following queries:

EXPLAIN (costs off)
    SELECT id, d, d <=> '2016-05-16 14:21:25' FROM tsts WHERE t @@ 'wr&qh' ORDER BY d <=> '2016-05-16 14:21:25' LIMIT 5;
                                    QUERY PLAN                                     
-----------------------------------------------------------------------------------
 Limit
   ->  Index Scan using tsts_idx on tsts
         Index Cond: (t @@ '''wr'' & ''qh'''::tsquery)
         Order By: (d <=> 'Mon May 16 14:21:25 2016'::timestamp without time zone)
(4 rows)

SELECT id, d, d <=> '2016-05-16 14:21:25' FROM tsts WHERE t @@ 'wr&qh' ORDER BY d <=> '2016-05-16 14:21:25' LIMIT 5;
 id  |                d                |   ?column?    
-----+---------------------------------+---------------
 355 | Mon May 16 14:21:22.326724 2016 |      2.673276
 354 | Mon May 16 13:21:22.326724 2016 |   3602.673276
 371 | Tue May 17 06:21:22.326724 2016 |  57597.326724
 406 | Wed May 18 17:21:22.326724 2016 | 183597.326724
 415 | Thu May 19 02:21:22.326724 2016 | 215997.326724
(5 rows)

For type: tsvector

See comments for rum_tsvector_timestamp_ops operator class.

For type: tsvector

This operator class stores hash of tsvector lexems with timestamp field. Doesn't support prefix search.

For type: tsvector

This operator class stores hash of tsvector lexems with timestamptz field. Doesn't support prefix search.

For type: tsquery

Stores branches of query tree in additional information. For example we have the table:

CREATE TABLE query (q tsquery, tag text);

INSERT INTO query VALUES ('supernova & star', 'sn'),
    ('black', 'color'),
    ('big & bang & black & hole', 'bang'),
    ('spiral & galaxy', 'shape'),
    ('black & hole', 'color');

CREATE INDEX query_idx ON query USING rum(q);

Now we can execute the following fast query:

SELECT * FROM query
    WHERE to_tsvector('black holes never exists before we think about them') @@ q;
        q         |  tag  
------------------+-------
 'black'          | color
 'black' & 'hole' | color
(2 rows)

• Allow multiple additional information (lexemes positions + timestamp).
• Add support for arrays.
• Improve ranking function to support TF/IDF.
• Improve insert time.
• Improve GENERIC WAL to support shift (PostgreSQL core changes).

Alexander Korotkov [email protected] Postgres Professional Ltd., Russia

Oleg Bartunov [email protected] Postgres Professional Ltd., Russia

Teodor Sigaev [email protected] Postgres Professional Ltd., Russia