PostgreSQL 8.4.22 Documentation | ||||
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The intarray module provides a number of useful functions and operators for manipulating one-dimensional arrays of integers. There is also support for indexed searches using some of the operators.
Table F-7. intarray Functions
Function | Return Type | Description | Example | Result |
---|---|---|---|---|
icount(int[]) |
int | number of elements in array | icount('{1,2,3}'::int[]) | 3 |
sort(int[], text
dir) |
int[] | sort array — dir must be asc or desc | sort('{1,2,3}'::int[], 'desc') | {3,2,1} |
sort(int[]) |
int[] | sort in ascending order | sort(array[11,77,44]) | {11,44,77} |
sort_asc(int[]) |
int[] | sort in ascending order | ||
sort_desc(int[]) |
int[] | sort in descending order | ||
uniq(int[]) |
int[] | remove adjacent duplicates | uniq(sort('{1,2,3,2,1}'::int[])) | {1,2,3} |
idx(int[], int
item) |
int | index of first element matching item (0 if none) | idx(array[11,22,33,22,11], 22) | 2 |
subarray(int[], int start,
int len) |
int[] | portion of array starting at position start, len elements | subarray('{1,2,3,2,1}'::int[], 2, 3) | {2,3,2} |
subarray(int[], int
start) |
int[] | portion of array starting at position start | subarray('{1,2,3,2,1}'::int[], 2) | {2,3,2,1} |
intset(int) |
int[] | make single-element array | intset(42) | {42} |
Table F-8. intarray Operators
Operator | Returns | Description |
---|---|---|
int[] && int[] | boolean | overlap — true if arrays have at least one common element |
int[] @> int[] | boolean | contains — true if left array contains right array |
int[] <@ int[] | boolean | contained — true if left array is contained in right array |
# int[] | int | number of elements in array |
int[] # int | int | index (same as idx
function) |
int[] + int | int[] | push element onto array (add it to end of array) |
int[] + int[] | int[] | array concatenation (right array added to the end of left one) |
int[] - int | int[] | remove entries matching right argument from array |
int[] - int[] | int[] | remove elements of right array from left |
int[] | int | int[] | union of arguments |
int[] | int[] | int[] | union of arrays |
int[] & int[] | int[] | intersection of arrays |
int[] @@ query_int | boolean | true if array satisfies query (see below) |
query_int ~~ int[] | boolean | true if array satisfies query (commutator of @@) |
(Before PostgreSQL 8.2, the containment operators @> and <@ were respectively called @ and ~. These names are still available, but are deprecated and will eventually be retired. Notice that the old names are reversed from the convention formerly followed by the core geometric datatypes!)
The containment operators @> and <@ are approximately equivalent to PostgreSQL's built-in operators of the same names, except that they work only on integer arrays while the built-in operators work for any array type. An important difference is that intarray's operators do not consider an empty array to be contained in anything else. This is consistent with the behavior of GIN-indexed queries, but not with the usual mathematical definition of containment.
The @@ and ~~ operators test whether an array satisfies a query, which is expressed as a value of a specialized data type query_int. A query consists of integer values that are checked against the elements of the array, possibly combined using the operators & (AND), | (OR), and ! (NOT). Parentheses can be used as needed. For example, the query 1&(2|3) matches arrays that contain 1 and also contain either 2 or 3.
intarray provides index support for the &&, @>, <@, and @@ operators, as well as regular array equality.
Two GiST index operator classes are provided: gist__int_ops (used by default) is suitable for small- to medium-size data sets, while gist__intbig_ops uses a larger signature and is more suitable for indexing large data sets (i.e., columns containing a large number of distinct array values). The implementation uses an RD-tree data structure with built-in lossy compression.
There is also a non-default GIN operator class gin__int_ops supporting the same operators.
The choice between GiST and GIN indexing depends on the relative performance characteristics of GiST and GIN, which are discussed elsewhere. As a rule of thumb, a GIN index is faster to search than a GiST index, but slower to build or update; so GIN is better suited for static data and GiST for often-updated data.
-- a message can be in one or more "sections"
CREATE TABLE message (mid INT PRIMARY KEY, sections INT[], ...);
-- create specialized index
CREATE INDEX message_rdtree_idx ON message USING GIST (sections gist__int_ops);
-- select messages in section 1 OR 2 - OVERLAP operator
SELECT message.mid FROM message WHERE message.sections && '{1,2}';
-- select messages in sections 1 AND 2 - CONTAINS operator
SELECT message.mid FROM message WHERE message.sections @> '{1,2}';
-- the same, using QUERY operator
SELECT message.mid FROM message WHERE message.sections @@ '1&2'::query_int;
The source directory contrib/intarray/bench contains a benchmark test suite. To run:
cd .../bench createdb TEST psql TEST < ../_int.sql ./create_test.pl | psql TEST ./bench.pl
The bench.pl script has numerous options, which are displayed when it is run without any arguments.
All work was done by Teodor Sigaev (<teodor@sigaev.ru>
) and
Oleg Bartunov (<oleg@sai.msu.su>
). See
http://www.sai.msu.su/~megera/postgres/gist for
additional information. Andrey Oktyabrski did a great work on
adding new functions and operations.