Yes you can index an array, but you have to use the array operators and the GIN-index type.
Example:
CREATE TABLE "Test"("Column1" int[]);
INSERT INTO "Test" VALUES ('{10, 15, 20}');
INSERT INTO "Test" VALUES ('{10, 20, 30}');
CREATE INDEX idx_test on "Test" USING GIN ("Column1");
-- To enforce index usage because we have only 2 records for this test...
SET enable_seqscan TO off;
EXPLAIN ANALYZE
SELECT * FROM "Test" WHERE "Column1" @> ARRAY[20];
Result:
Bitmap Heap Scan on "Test" (cost=4.26..8.27 rows=1 width=32) (actual time=0.014..0.015 rows=2 loops=1)
Recheck Cond: ("Column1" @> '{20}'::integer[])
-> Bitmap Index Scan on idx_test (cost=0.00..4.26 rows=1 width=0) (actual time=0.009..0.009 rows=2 loops=1)
Index Cond: ("Column1" @> '{20}'::integer[])
Total runtime: 0.062 ms
Note
it appears that in many cases the gin__int_ops option is required
create index <index_name> on <table_name> using GIN (<column> gin__int_ops)
I have not yet seen a case where it would work with the && and @> operator without the gin__int_ops options
@Tregoreg raised a question in the comment to his offered bounty:
I didn't find the current answers working. Using GIN index on array-typed column does not increase the performance of ANY() operator. Is there really no solution?
@Frank's accepted answer tells you to use array operators, which is still correct for Postgres 11. The manual:
... the standard distribution of PostgreSQL includes a GIN operator class for arrays, which supports indexed queries using these operators:
<@ @> = &&
The complete list of built-in operator classes for GIN indexes in the standard distribution is here.
In Postgres indexes are bound to operators (which are implemented for certain types), not data types alone or functions or anything else. That's a heritage from the original Berkeley design of Postgres and very hard to change now. And it's generally working just fine. Here is a thread on pgsql-bugs with Tom Lane commenting on this.
Some PostGis functions (like ST_DWithin()
) seem to violate this principal, but that is not so. Those functions are rewritten internally to use respective operators.
The indexed expression must be to the left of the operator. For most operators (including all of the above) the query planner can achieve this by flipping operands if you place the indexed expression to the right - given that a COMMUTATOR
has been defined. The ANY
construct can be used in combination with various operators and is not an operator itself. When used as constant = ANY (array_expression)
only indexes supporting the =
operator on array elements would qualify and we would need a commutator for = ANY()
. GIN indexes are out.
Postgres is not currently smart enough to derive a GIN-indexable expression from it. For starters, constant = ANY (array_expression)
is not completely equivalent to array_expression @> ARRAY[constant]
. Array operators return an error if any NULL elements are involved, while the ANY
construct can deal with NULL on either side. And there are different results for data type mismatches.
Related answers:
Check if value exists in Postgres array
Index for finding an element in a JSON array
SQLAlchemy: how to filter on PgArray column types?
Can IS DISTINCT FROM be combined with ANY or ALL somehow?
While working with integer
arrays (int4
, not int2
or int8
) without NULL
values (like your example implies) consider the additional module intarray
, that provides specialized, faster operators and index support. See:
As for the UNIQUE
constraint in your question that went unanswered: That's implemented with a btree index on the whole array value (like you suspected) and does not help with the search for elements at all. Details:
It's now possible to index the individual array elements. For example:
CREATE TABLE test (foo int[]);
INSERT INTO test VALUES ('{1,2,3}');
INSERT INTO test VALUES ('{4,5,6}');
CREATE INDEX test_index on test ((foo[1]));
SET enable_seqscan TO off;
EXPLAIN ANALYZE SELECT * from test WHERE foo[1]=1;
QUERY PLAN
------------------------------------------------------------------------------------------------------------------
Index Scan using test_index on test (cost=0.00..8.27 rows=1 width=32) (actual time=0.070..0.071 rows=1 loops=1)
Index Cond: (foo[1] = 1)
Total runtime: 0.112 ms
(3 rows)
This works on at least Postgres 9.2.1. Note that you need to build a separate index for each array index, in my example I only indexed the first element.
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