F.57. rum

F.57.1. Introduction

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

GIN index allows you to perform fast full-text search using tsvector and tsquery types. However, full-text search with GIN index has some performance issues because positional and other additional information is not stored.

RUM solves these issues by storing additional information in a posting tree. As compared to GIN, RUM index has the following benefits:

  • Faster ranking. Ranking requires positional information. And after the index scan we do not need an additional heap scan to retrieve lexeme positions because RUM index stores them.

  • Faster phrase search. This improvement is related to the previous one as phrase search also needs positional information.

  • Faster ordering by timestamp. RUM index stores additional information together with lexemes, so it is not necessary to perform a heap scan.

  • A possibility to perform depth-first search and therefore return first results immediately.

The drawback of RUM is that it has slower build and insert time as compared to GIN because RUM stores additional information together with keys and uses generic WAL records.

F.57.2. Installation

rum is a Postgres Pro Standard extension and it has no special prerequisites.

Install extension as follows:

$ psql dbname -c "CREATE EXTENSION rum"

F.57.3. Common Operators

The operators provided by the rum module are shown in Table F.35:

Table F.35. rum Operators

OperatorReturnsDescription
tsvector <=> tsqueryfloat4Returns distance between tsvector and tsquery values.
timestamp <=> timestampfloat8Returns distance between two timestamp values.
timestamp <=| timestampfloat8Returns distance only for ascending timestamp values.
timestamp |=> timestampfloat8Returns distance only for descending timestamp values.

Note

rum introduces its own ranking function that is executed inside the <=> operator. It calculates the score (inverted distance) using the specified normalization method. This function is a combination of ts_rank and ts_rank_cd (see Section 9.13 for details). While ts_rank does not support logical operators and ts_rank_cd works poorly with OR queries, the rum-specific ranking function overcomes these drawbacks.

F.57.4. Operator Classes

The rum extension provides the following operator classes:

rum_tsvector_ops

Stores tsvector lexemes with positional information. Supports ordering by <=> operator and prefix search.

rum_tsvector_hash_ops

Stores hash of tsvector lexemes with positional information. Supports ordering by <=> operator, but does not support prefix search.

rum_tsvector_addon_ops

Stores tsvector lexemes with additional data of any type supported by RUM.

Note

To use the rum_tsvector_addon_ops operator class, when creating the RUM index with CREATE INDEX, specify the attach and to storage parameters in the WITH clause.

rum_tsvector_hash_addon_ops

Stores tsvector lexemes with additional data of any type supported by RUM. Does not support prefix search.

rum_tsquery_ops

Stores branches of query tree in additional information.

rum_anyarray_ops

Stores anyarray elements with length of the array. Supports ordering by <=> operator.

Indexable operators: && @> <@ = %

rum_anyarray_addon_ops

Stores anyarray elements with additional data of any type supported by RUM.

rum_type_ops

Stores lexemes of the corresponding type with positional information. The type placeholder in the class name must be substituted by one of the following type names: int2, int4, int8, float4, float8, money, oid, timestamp, timestamptz, time, timetz, date, interval, macaddr, inet, cidr, text, varchar, char, bytea, bit, varbit, numeric.

rum_type_ops supports ordering by <=>, <=|, and |=> operators. This operator class can be used together with rum_tsvector_addon_ops, rum_tsvector_hash_addon_ops, and rum_anyarray_addon_ops operator classes.

Supported indexable operators depend on the data type:

  • < <= = >= > <=> <=| |=> are supported for int2, int4, int8, float4, float8, money, oid, timestamp, timestamptz.

  • < <= = >= > are supported for time, timetz, date, interval, macaddr, inet, cidr, text, varchar, char, bytea, bit, varbit, numeric.

Note

The following operator classes are now deprecated: rum_tsvector_timestamp_ops, rum_tsvector_timestamptz_ops, rum_tsvector_hash_timestamp_ops, rum_tsvector_hash_timestamptz_ops.

F.57.5. Functions

The RUM index provides functions for low-level inspection of all its page types.

rum_metapage_info(rel_name text, blk_num int4) returns record

Returns information about a RUM index metapage. For example:

SELECT * FROM rum_metapage_info('rum_index', 0);
-[ RECORD 1 ]----+-----------
pending_head     | 4294967295
pending_tail     | 4294967295
tail_free_size   | 0
n_pending_pages  | 0
n_pending_tuples | 0
n_total_pages    | 87
n_entry_pages    | 80
n_data_pages     | 6
n_entries        | 1650
version          | 0xC0DE0002
rum_page_opaque_info(rel_name text, blk_num int4) returns record

Returns information about a RUM index opaque area, such as leftlink and rightlink, maxoff, and freespace. The maxoff parameter is the number of elements stored in the page, it is used differently for different types of pages. The freespace column represents the amount of free space in the page. For example:

SELECT * FROM rum_page_opaque_info('rum_index', 10);
 leftlink | rightlink | maxoff | freespace | flags
----------+-----------+--------+-----------+--------
        6 |        11 |      0 |         0 | {leaf}
(1 row)
rum_internal_entry_page_items(rel_name text, blk_num int4) returns setof record

Returns information stored in internal pages of the entry tree. This information is extracted from IndexTuple. For example:

SELECT * FROM rum_internal_entry_page_items('rum_index', 1);
               key               | attrnum |     category     | down_link
---------------------------------+---------+------------------+-----------
 3d                              |       1 | RUM_CAT_NORM_KEY |         3
 6k                              |       1 | RUM_CAT_NORM_KEY |         2
 a8                              |       1 | RUM_CAT_NORM_KEY |         4
...
 Tue May 10 21:21:22.326724 2016 |       2 | RUM_CAT_NORM_KEY |        83
 Sat May 14 19:21:22.326724 2016 |       2 | RUM_CAT_NORM_KEY |        84
 Wed May 18 17:21:22.326724 2016 |       2 | RUM_CAT_NORM_KEY |        85
 +inf                            |         |                  |        86
(79 rows)

The RUM index, just like GIN, packs downlinks and keys in pairs of the (P_n, K_{n+1}) type on internal pages of the entry tree. Note that there is no key for P_0, it is assumed to be equal to -inf. Also, there is no downlink for the last key K_{n+1}, it is assumed to be the largest key, or high key, in the subtree to which the P_n link leads. In the rightmost page of each internal level of the entry tree, the key related to P_n does not have any value and is assumed to be equal to +inf.

rum_leaf_entry_page_items(rel_name text, blk_num int4) returns setof record

Returns information that is stored in leaf pages of the entry tree. This information is extracted from compressed posting lists. For example:

SELECT * FROM rum_leaf_entry_page_items('rum_index', 10);
 key | attrnum |     category     | tuple_id | add_info_is_null | add_info | is_posting_tree  | posting_tree_root
-----+---------+------------------+----------+------------------+----------+------------------+--------------------
 ay  |       1 | RUM_CAT_NORM_KEY | (0,16)   | t                |          | f                |
 ay  |       1 | RUM_CAT_NORM_KEY | (0,23)   | t                |          | f                |
 ay  |       1 | RUM_CAT_NORM_KEY | (2,1)    | t                |          | f                |
...
 az  |       1 | RUM_CAT_NORM_KEY | (0,15)   | t                |          | f                |
 az  |       1 | RUM_CAT_NORM_KEY | (0,22)   | t                |          | f                |
 az  |       1 | RUM_CAT_NORM_KEY | (1,4)    | t                |          | f                |
...
 b9  |       1 | RUM_CAT_NORM_KEY |          |                  |          | t                |                  7
...
(1602 rows)

Each posting list is an IndexTuple that stores the key value and a compressed list of TIDs. When the rum_leaf_entry_page_items() function is called, the key value is attached to each TID for convenience, but in the page it is stored separately.

If the number of TIDs is too large, then a posting tree is used for storage rather than a posting list. In the example above, a posting tree is created for the key with the b9 value. The key in the posting tree is the TID. In this case, the magic number and the page number, which is the root of the posting tree, are stored inside IndexTuple instead of the posting list.

rum_internal_data_page_items(rel_name text, blk_num int4) returns setof record

Returns information that is stored in internal pages of the posting tree. This information is extracted from arrays of the RumPostingItem structures. For example:

SELECT * FROM rum_internal_data_page_items('rum_index', 7);
 is_high_key | block_number | tuple_id | add_info_is_null | add_info
-------------+--------------+----------+------------------+----------
 t           |              | (0,0)    | t                |
 f           |            9 | (138,79) | t                |
 f           |            8 | (0,0)    | t                |
(3 rows)

Each internal page element of the posting tree contains the high key (TID) value for the child page and a link to this child page as well as additional information if it was added when creating the index.

At the beginning of am internal page of the posting tree, the high key of this page is always stored if it has the (0,0) value, this is equivalent to +inf. This is always the case if the page is the rightmost.

At the moment, RUM does not support storing data of the varlena data types in internal pages of the posting tree. These types of data can be stored only on leaf pages. Therefore, the following output is possible:

 is_high_key | block_number | tuple_id | add_info_is_null |                    add_info
-------------+--------------+----------+------------------+------------------------------------------------
...
 f           |           23 | (39,43)  | f                | varlena types in posting tree is not supported
 f           |           22 | (74,9)   | f                | varlena types in posting tree is not supported
...
rum_leaf_data_page_items(rel_name text, blk_num int4) returns setof record

Returns information that is stored in leaf pages of the posting tree. This information is extracted from compressed posting lists. For example:

SELECT * FROM rum_leaf_data_page_items('rum_idx', 9);
 is_high_key | tuple_id  | add_info_is_null | add_info
-------------+-----------+------------------+----------
 t           | (138,79)  | t                |
 f           | (0,9)     | t                |
 f           | (1,23)    | t                |
 f           | (3,5)     | t                |
 f           | (3,22)    | t                |

Unlike leaf pages of the entry tree, compressed posting lists are not stored in IndexTuple in the posting tree leaf pages. The high key is the largest key on the page.

F.57.6. Examples

F.57.6.1.  rum_tsvector_ops Example

Let's assume we have the following 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');

Then we can create a 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)

F.57.6.2.  rum_tsvector_addon_ops Example

Let's assume we have the following 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)

F.57.6.3.  rum_tsquery_ops Example

Suppose 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);

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)

F.57.6.4.  rum_anyarray_ops Example

Let's assume we have the following 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 following 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)

F.57.7. Authors

Alexander Korotkov

Oleg Bartunov

Teodor Sigaev