The rum module provides an access method to work with a RUM index. It is based
on the GIN access method's code.
A GIN index allows performing fast full-text search using tsvector and
tsquery types. But full-text search with a GIN index has several problems:
- Slow ranking. It needs positional information about lexemes to do ranking. A
GINindex doesn't store positions of lexemes. So after index scanning, we need an additional heap scan to retrieve lexeme positions. - Slow phrase search with a
GINindex. This problem relates to the previous problem. It needs positional information to perform phrase search. - Slow ordering by timestamp. A
GINindex can't store some related information in the index with lexemes. So it is necessary to perform an additional heap scan.
RUM solves these problems by storing additional information in a posting tree.
For example, positional information of lexemes or timestamps. You can get an
idea of RUM with the following diagram:
A drawback of RUM is that it has slower build and insert times than GIN.
This is because we need to store additional information besides keys and because
RUM uses generic Write-Ahead Log (WAL) records.
This module is available under the license similar to PostgreSQL.
Before building and installing rum, you should ensure following are installed:
- 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
$ make USE_PGXS=1 install
$ make USE_PGXS=1 installcheck
$ psql DB -c "CREATE EXTENSION rum;"
$ USE_PGXS=1 pgxn install rum
Important: Don't forget to set the
PG_CONFIGvariable in case you want to testRUMon a custom build of PostgreSQL. Read more here.
The rum module provides next operators.
| Operator | Returns | Description |
|---|---|---|
| tsvector <=> tsquery | float4 | Returns distance between tsvector and tsquery. |
| timestamp <=> timestamp | float8 | Returns distance between two timestamps. |
| timestamp <=| timestamp | float8 | Returns distance only for left timestamps. |
| timestamp |=> timestamp | float8 | Returns distance only for right timestamps. |
The last three operations also work for types timestamptz, int2, int4, int8, float4, float8, money and oid.
rum provides the following operator classes.
For type: tsvector
This operator class stores tsvector lexemes with positional information. It supports
ordering by the <=> operator and prefix search. See the example below.
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
---------------------------------+---------
It looks like a beautiful place | 8.22467
The situation is most beautiful | 16.4493
It is a beautiful | 16.4493
(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 | 16.4493
It looks like a beautiful place | 16.4493
(2 rows)For type: tsvector
This operator class stores a hash of tsvector lexemes with positional information.
It supports ordering by the <=> operator. It doesn't support prefix search.
For types: int2, int4, int8, float4, float8, money, oid, time, timetz, date, interval, macaddr, inet, cidr, text, varchar, char, bytea, bit, varbit, numeric, timestamp, timestamptz
Supported operations: <, <=, =, >=, > for all types and
<=>, <=| and |=> for int2, int4, int8, float4, float8, money, oid,
timestamp and timestamptz types.
This operator supports ordering by the <=>, <=| and |=> operators. It can be used with
rum_tsvector_addon_ops, rum_tsvector_hash_addon_ops' and rum_anyarray_addon_ops` operator classes.
For type: tsvector
This operator class stores tsvector lexemes with any supported by module
field. See the example below.
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_addon_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)Warning: Currently RUM has bogus behaviour when one creates an index using ordering over pass-by-reference additional information. This is due to the fact that posting trees have fixed length right bound and fixed length non-leaf posting items. It isn't allowed to create such indexes.
For type: tsvector
This operator class stores a hash of tsvector lexemes with any supported by module
field.
It doesn't support prefix search.
For type: tsquery
It 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)For type: anyarray
This operator class stores anyarray elements with length of the array.
It supports operators &&, @>, <@, =, % operators. It also supports ordering by <=> operator.
For example, we have the table:
CREATE TABLE test_array (i int2[]);
INSERT INTO test_array VALUES ('{}'), ('{0}'), ('{1,2,3,4}'), ('{1,2,3}'), ('{1,2}'), ('{1}');
CREATE INDEX idx_array ON test_array USING rum (i rum_anyarray_ops);Now we can execute the query using index scan:
SET enable_seqscan TO off;
EXPLAIN (COSTS OFF) SELECT * FROM test_array WHERE i && '{1}' ORDER BY i <=> '{1}' ASC;
QUERY PLAN
------------------------------------------
Index Scan using idx_array on test_array
Index Cond: (i && '{1}'::smallint[])
Order By: (i <=> '{1}'::smallint[])
(3 rows
SELECT * FROM test_array WHERE i && '{1}' ORDER BY i <=> '{1}' ASC;
i
-----------
{1}
{1,2}
{1,2,3}
{1,2,3,4}
(4 rows)For type: anyarray
This operator class stores anyarray elements with any supported by module
field.
- Allow multiple additional information (lexemes positions + timestamp).
- 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
Arthur Zakirov [email protected] Postgres Professional Ltd., Russia
Pavel Borisov [email protected] Postgres Professional Ltd., Russia
Maxim Orlov [email protected] Postgres Professional Ltd., Russia
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