I need help optimizing a Postgres query which uses the BETWEEN
clause with a timestamp
field.
I have 2 tables:
ONE(int id_one(PK), datetime cut_time, int f1 ...)
containing about 3394 rows
TWO(int id_two(PK), int id_one(FK), int f2 ...)
containing about 4000000 rows
There are btree indexes on both PKs id_one
and id_two
, on the FK id_one
and cut_time
.
I want to perform a query like:
select o.id_one, Date(o.cut_time), o.f1, t.f2 from one o inner join two t ON (o.id_one = t.id_one) where o.cut_time between '2013-01-01' and '2013-01-31';
This query retrieves about 1.700.000 rows in about 7 seconds.
Below the explain analyze report is reported:
Merge Join (cost=20000000003.53..20000197562.38 rows=1680916 width=24) (actual time=0.017..741.718 rows=1692345 loops=1)" Merge Cond: (c.coilid = hf.coilid) -> Index Scan using pk_coils on coils c (cost=10000000000.00..10000000382.13 rows=1420 width=16) (actual time=0.008..4.539 rows=1404 loops=1) Filter: ((cut_time >= '2013-01-01 00:00:00'::timestamp without time zone) AND (cut_time <= '2013-01-31 00:00:00'::timestamp without time zone)) Rows Removed by Filter: 1990 -> Index Scan using idx_fk_lf_data on hf_data hf (cost=10000000000.00..10000166145.90 rows=4017625 width=16) (actual time=0.003..392.535 rows=1963386 loops=1) Total runtime: 768.473 ms
The index on the timestamp column isn’t used. How to optimize this query?
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Answer
The query executes in less than one second. The other 6+ seconds are spent on traffic between server and client.