Why is the "IN" operator so slow when used with subquery?
select * from view1 where id in (1,2,3,4,5,6,7,8,9,10) order by somedata;
executes in 9ms.
select * from view1 where id in (select ext_id from aggregate_table order by somedata limit 10) order by somedata;
executes in 25000ms and seems to use sequential scan on the view (view1
) instead of index scan on primary keys returned by subquery as in does in first query.
The subquery select ext_id from aggregate_table order by somedata limit 10
executes in 0.1ms
so the slowness of the second query is caused by sequential scan on view1
which is a view containing three UNIONS and about three JOINS in each UNION. The first UNION contains about a 1M rows, others much less. Joins with tables with some 100K rows. That's not so relevant, though, I just wanted to understand the IN operator behaviour.
What I'm trying to accomplish is to take the result of subquery (a set of primary keys) and select the data from a complex view (view1
) using just them.
I also cannot use
select v1.* from view1 v1, aggregate_table at where v1.id = at.ext_id order by at.somedata limit 10
because I do not want to sort the big join by somedata
. I just want to select 10 results from the view by primary keys and then sort only these.
The question is why does IN operator perform fast when I explicitly list these keys and so slow when I use a fast subquery that returns the exact same set of keys?
EXPLAIN ANALYZE as requested
first query - select * from view1 where id in (1,2,3,4,5,6,7,8,9,10) order by somedata;
Sort (cost=348.480..348.550 rows=30 width=943) (actual time=14.385..14.399 rows=10 loops=1) Sort Key: "india".three Sort Method: quicksort Memory: 30kB -> Append (cost=47.650..347.440 rows=30 width=334) (actual time=11.528..14.275 rows=10 loops=1) -> Subquery Scan "*SELECT* 1" (cost=47.650..172.110 rows=10 width=496) (actual time=11.526..12.301 rows=10 loops=1) -> Nested Loop (cost=47.650..172.010 rows=10 width=496) (actual time=11.520..12.268 rows=10 loops=1) -> Hash Join (cost=47.650..87.710 rows=10 width=371) (actual time=11.054..11.461 rows=10 loops=1) Hash Cond: (hotel.alpha_five = juliet_xray.alpha_five) -> Bitmap Heap Scan on sierra hotel (cost=42.890..82.800 rows=10 width=345) (actual time=10.835..11.203 rows=10 loops=1) Recheck Cond: (four = ANY ('quebec'::integer[])) -> Bitmap Index Scan on seven (cost=0.000..42.890 rows=10 width=0) (actual time=0.194..0.194 rows=10 loops=1) Index Cond: (four = ANY ('quebec'::integer[])) -> Hash (cost=4.340..4.340 rows=34 width=30) (actual time=0.184..0.184 rows=34 loops=1) -> Seq Scan on six juliet_xray (cost=0.000..4.340 rows=34 width=30) (actual time=0.029..0.124 rows=34 loops=1) -> Index Scan using charlie on juliet_two zulu (cost=0.000..8.390 rows=1 width=129) (actual time=0.065..0.067 rows=1 loops=10) Index Cond: (zulu.four = hotel.victor_whiskey) -> Subquery Scan "*SELECT* 2" (cost=4.760..97.420 rows=10 width=366) (actual time=0.168..0.168 rows=0 loops=1) -> Hash Join (cost=4.760..97.320 rows=10 width=366) (actual time=0.165..0.165 rows=0 loops=1) Hash Cond: (alpha_xray.alpha_five = juliet_xray2.alpha_five) -> Nested Loop (cost=0.000..92.390 rows=10 width=340) (actual time=0.162..0.162 rows=0 loops=1) -> Seq Scan on lima_echo alpha_xray (cost=0.000..8.340 rows=10 width=216) (actual time=0.159..0.159 rows=0 loops=1) Filter: (four = ANY ('quebec'::integer[])) -> Index Scan using charlie on juliet_two xray (cost=0.000..8.390 rows=1 width=128) (never executed) Index Cond: (zulu2.four = alpha_xray.victor_whiskey) -> Hash (cost=4.340..4.340 rows=34 width=30) (never executed) -> Seq Scan on six uniform (cost=0.000..4.340 rows=34 width=30) (never executed) -> Subquery Scan "*SELECT* 3" (cost=43.350..77.910 rows=10 width=141) (actual time=1.775..1.775 rows=0 loops=1) -> Hash Join (cost=43.350..77.810 rows=10 width=141) (actual time=1.771..1.771 rows=0 loops=1) Hash Cond: (golf.alpha_five = juliet_xray3.alpha_five) -> Bitmap Heap Scan on lima_golf golf (cost=38.590..72.910 rows=10 width=115) (actual time=0.110..0.110 rows=0 loops=1) Recheck Cond: (four = ANY ('quebec'::integer[])) -> Bitmap Index Scan on victor_hotel (cost=0.000..38.590 rows=10 width=0) (actual time=0.105..0.105 rows=0 loops=1) Index Cond: (four = ANY ('quebec'::integer[])) -> Hash (cost=4.340..4.340 rows=34 width=30) (actual time=0.118..0.118 rows=34 loops=1) -> Seq Scan on six victor_kilo (cost=0.000..4.340 rows=34 width=30) (actual time=0.007..0.063 rows=34 loops=1) Total runtime: 14.728 ms
second query - select * from view1 where id in (select ext_id from aggregate_table order by somedata limit 10) order by somedata;
Sort (cost=254515.780..254654.090 rows=55325 width=943) (actual time=24687.475..24687.488 rows=10 loops=1) Sort Key: "five".xray_alpha Sort Method: quicksort Memory: 30kB -> Hash Semi Join (cost=54300.820..250157.370 rows=55325 width=943) (actual time=11921.783..24687.308 rows=10 loops=1) Hash Cond: ("five".lima = "delta_echo".lima) -> Append (cost=54298.270..235569.720 rows=1106504 width=494) (actual time=3412.453..23091.938 rows=1106503 loops=1) -> Subquery Scan "*SELECT* 1" (cost=54298.270..234227.250 rows=1100622 width=496) (actual time=3412.450..20234.122 rows=1100622 loops=1) -> Hash Join (cost=54298.270..223221.030 rows=1100622 width=496) (actual time=3412.445..17078.021 rows=1100622 loops=1) Hash Cond: (three_victor.xray_hotel = delta_yankee.xray_hotel) -> Hash Join (cost=54293.500..180567.160 rows=1100622 width=470) (actual time=3412.251..12108.676 rows=1100622 loops=1) Hash Cond: (three_victor.tango_three = quebec_seven.lima) -> Seq Scan on india three_victor (cost=0.000..104261.220 rows=1100622 width=345) (actual time=0.015..3437.722 rows=1100622 loops=1) -> Hash (cost=44613.780..44613.780 rows=774378 width=129) (actual time=3412.031..3412.031 rows=774603 loops=1) -> Seq Scan on oscar quebec_seven (cost=0.000..44613.780 rows=774378 width=129) (actual time=4.142..1964.036 rows=774603 loops=1) -> Hash (cost=4.340..4.340 rows=34 width=30) (actual time=0.149..0.149 rows=34 loops=1) -> Seq Scan on alpha_kilo delta_yankee (cost=0.000..4.340 rows=34 width=30) (actual time=0.017..0.095 rows=34 loops=1) -> Subquery Scan "*SELECT* 2" (cost=4.760..884.690 rows=104 width=366) (actual time=7.846..10.161 rows=104 loops=1) -> Hash Join (cost=4.760..883.650 rows=104 width=366) (actual time=7.837..9.804 rows=104 loops=1) Hash Cond: (foxtrot.xray_hotel = delta_yankee2.xray_hotel) -> Nested Loop (cost=0.000..877.200 rows=104 width=340) (actual time=7.573..9.156 rows=104 loops=1) -> Seq Scan on four_india foxtrot (cost=0.000..7.040 rows=104 width=216) (actual time=0.081..0.311 rows=104 loops=1) -> Index Scan using three_delta on oscar alpha_victor (cost=0.000..8.350 rows=1 width=128) (actual time=0.077..0.078 rows=1 loops=104) Index Cond: (quebec_seven2.lima = foxtrot.tango_three) -> Hash (cost=4.340..4.340 rows=34 width=30) (actual time=0.216..0.216 rows=34 loops=1) -> Seq Scan on alpha_kilo quebec_foxtrot (cost=0.000..4.340 rows=34 width=30) (actual time=0.035..0.153 rows=34 loops=1) -> Subquery Scan "*SELECT* 3" (cost=4.760..457.770 rows=5778 width=141) (actual time=0.264..58.353 rows=5777 loops=1) -> Hash Join (cost=4.760..399.990 rows=5778 width=141) (actual time=0.253..39.062 rows=5777 loops=1) Hash Cond: (four_uniform.xray_hotel = delta_yankee3.xray_hotel) -> Seq Scan on whiskey four_uniform (cost=0.000..315.780 rows=5778 width=115) (actual time=0.112..15.759 rows=5778 loops=1) -> Hash (cost=4.340..4.340 rows=34 width=30) (actual time=0.117..0.117 rows=34 loops=1) -> Seq Scan on alpha_kilo golf (cost=0.000..4.340 rows=34 width=30) (actual time=0.005..0.059 rows=34 loops=1) -> Hash (cost=2.430..2.430 rows=10 width=4) (actual time=0.303..0.303 rows=10 loops=1) -> Subquery Scan "ANY_subquery" (cost=0.000..2.430 rows=10 width=4) (actual time=0.092..0.284 rows=10 loops=1) -> Limit (cost=0.000..2.330 rows=10 width=68) (actual time=0.089..0.252 rows=10 loops=1) -> Index Scan using tango_seven on zulu romeo (cost=0.000..257535.070 rows=1106504 width=68) (actual time=0.087..0.227 rows=10 loops=1) Total runtime: 24687.975 ms
In most cases JOIN s are faster than sub-queries and it is very rare for a sub-query to be faster.
For multiple-table subqueries, execution of NULL IN (SELECT ...) is particularly slow because the join optimizer does not optimize for the case where the outer expression is NULL .
Some of the tricks we used to speed up SELECT-s in PostgreSQL: LEFT JOIN with redundant conditions, VALUES, extended statistics, primary key type conversion, CLUSTER, pg_hint_plan + bonus.
Seems that I have finally found a solution:
select * from view1 where view1.id = ANY( (select array(select ext_id from aggregate_table order by somedata limit 10) )::integer[] ) order by view1.somedata;
After elaborating @Dukeling's idea:
I suspect where id in (1,2,3,4,5,6,7,8,9,10) can be optimised and where id in (select ...) can't, the reason being that (1,2,3,4,5,6,7,8,9,10) is a constant expression, while the select is not.
and locating these in faster query plan
Recheck Cond: (id = ANY ('{1,2,3,4,5,6,7,8,9,10}'::integer[])) Index Cond: (id = ANY ('{1,2,3,4,5,6,7,8,9,10}'::integer[]))
this works even faster than the first query in the question, about 1.2ms, and now it uses
Recheck Cond: (id = ANY ($1)) Index Cond: (id = ANY ($1))
and bitmap scans in the plan.
I suspect where id in (1,2,3,4,5,6,7,8,9,10)
can be optimised and where id in (select ...)
can't, the reason being that (1,2,3,4,5,6,7,8,9,10)
is a constant expression, while the select
is not.
How about:
WITH myCTE AS ( SELECT ext_id FROM aggregate_table ORDER BY somedata LIMIT 10 ) SELECT * FROM myCTE LEFT JOIN table1 ON myCTE.ext_id = table1.id ORDER BY somedata
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