I have a very simple SQL query:
SELECT COUNT(DISTINCT x) FROM table;
My table has about 1.5 million rows. This query is running pretty slowly; it takes about 7.5s, compared to
SELECT COUNT(x) FROM table;
which takes about 435ms. Is there any way to change my query to improve performance? I've tried grouping and doing a regular count, as well as putting an index on x; both have the same 7.5s execution time.
This question is related to
performance
postgresql
count
distinct
-- My default settings (this is basically a single-session machine, so work_mem is pretty high)
SET effective_cache_size='2048MB';
SET work_mem='16MB';
\echo original
EXPLAIN ANALYZE
SELECT
COUNT (distinct val) as aantal
FROM one
;
\echo group by+count(*)
EXPLAIN ANALYZE
SELECT
distinct val
-- , COUNT(*)
FROM one
GROUP BY val;
\echo with CTE
EXPLAIN ANALYZE
WITH agg AS (
SELECT distinct val
FROM one
GROUP BY val
)
SELECT COUNT (*) as aantal
FROM agg
;
Results:
original QUERY PLAN
----------------------------------------------------------------------------------------------------------------------
Aggregate (cost=36448.06..36448.07 rows=1 width=4) (actual time=1766.472..1766.472 rows=1 loops=1)
-> Seq Scan on one (cost=0.00..32698.45 rows=1499845 width=4) (actual time=31.371..185.914 rows=1499845 loops=1)
Total runtime: 1766.642 ms
(3 rows)
group by+count(*)
QUERY PLAN
----------------------------------------------------------------------------------------------------------------------------
HashAggregate (cost=36464.31..36477.31 rows=1300 width=4) (actual time=412.470..412.598 rows=1300 loops=1)
-> HashAggregate (cost=36448.06..36461.06 rows=1300 width=4) (actual time=412.066..412.203 rows=1300 loops=1)
-> Seq Scan on one (cost=0.00..32698.45 rows=1499845 width=4) (actual time=26.134..166.846 rows=1499845 loops=1)
Total runtime: 412.686 ms
(4 rows)
with CTE
QUERY PLAN
------------------------------------------------------------------------------------------------------------------------------------
Aggregate (cost=36506.56..36506.57 rows=1 width=0) (actual time=408.239..408.239 rows=1 loops=1)
CTE agg
-> HashAggregate (cost=36464.31..36477.31 rows=1300 width=4) (actual time=407.704..407.847 rows=1300 loops=1)
-> HashAggregate (cost=36448.06..36461.06 rows=1300 width=4) (actual time=407.320..407.467 rows=1300 loops=1)
-> Seq Scan on one (cost=0.00..32698.45 rows=1499845 width=4) (actual time=24.321..165.256 rows=1499845 loops=1)
-> CTE Scan on agg (cost=0.00..26.00 rows=1300 width=0) (actual time=407.707..408.154 rows=1300 loops=1)
Total runtime: 408.300 ms
(7 rows)
The same plan as for the CTE could probably also be produced by other methods (window functions)
You can use this:
SELECT COUNT(*) FROM (SELECT DISTINCT column_name FROM table_name) AS temp;
This is much faster than:
COUNT(DISTINCT column_name)
If your count(distinct(x))
is significantly slower than count(x)
then you can speed up this query by maintaining x value counts in different table, for example table_name_x_counts (x integer not null, x_count int not null)
, using triggers. But your write performance will suffer and if you update multiple x
values in single transaction then you'd need to do this in some explicit order to avoid possible deadlock.
I was also searching same answer, because at some point of time I needed total_count with distinct values along with limit/offset.
Because it's little tricky to do- To get total count with distinct values along with limit/offset. Usually it's hard to get total count with limit/offset. Finally I got the way to do -
SELECT DISTINCT COUNT(*) OVER() as total_count, * FROM table_name limit 2 offset 0;
Query performance is also high.
Source: Stackoverflow.com