performance - insensitive - Operador PostgreSQL IN con subconsulta de bajo rendimiento

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Question

¿Por qué el operador "IN" es tan lento cuando se usa con la subconsulta?

select *
from view1
where id in (1,2,3,4,5,6,7,8,9,10)
order by somedata;

Se ejecuta en 9ms.

select *
from view1
where id in (select ext_id
from aggregate_table
order by somedata limit 10)
order by somedata;

se ejecuta en 25000ms y parece que usa el escaneo secuencial en la vista ( view1 ) en lugar del escaneo de índice en las claves primarias devueltas por la subconsulta como en la primera consulta.

La subconsulta select ext_id from aggregate_table order by somedata limit 10 ejecuta en 0.1ms

por lo tanto, la lentitud de la segunda consulta es causada por el escaneo secuencial en la view1 que es una vista que contiene tres UNIONES y aproximadamente tres UNIONES en cada UNIÓN. La primera UNION contiene aproximadamente 1M filas, otras mucho menos. Se une a tablas con algunas filas de 100K. Sin embargo, eso no es tan relevante, solo quería entender el comportamiento del operador IN.

Lo que estoy tratando de lograr es tomar el resultado de la subconsulta (un conjunto de claves primarias) y seleccionar los datos desde una vista compleja ( view1 ) usando solo ellos.

Tampoco puedo usar

select v1.*
from view1 v1,
aggregate_table at
where v1.id = at.ext_id
order by at.somedata
limit 10

Porque no quiero ordenar la gran unión por somedata . Solo quiero seleccionar 10 resultados de la vista por claves primarias y luego ordenar solo estos.

La pregunta es ¿por qué el operador IN se desempeña rápido cuando enumero explícitamente estas claves y tan lento cuando uso una subconsulta rápida que devuelve exactamente el mismo conjunto de claves?

EXPLICAR EL ANÁLISIS según lo solicitado

primera consulta: 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

segunda consulta: 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

Answer 1

Parece que finalmente he encontrado una solución:

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;

Después de elaborar la idea de @Dukeling:

Sospecho que la identificación en (1,2,3,4,5,6,7,8,9,9,10) puede optimizarse y la identificación en (seleccionar ...) no puede, la razón es que (1, 2,3,4,5,6,7,8,9,10) es una expresión constante, mientras que la selección no lo es.

y ubicarlos en un plan de consulta más rápido

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[]))

esto funciona incluso más rápido que la primera consulta de la pregunta, aproximadamente 1,2 ms, y ahora usa

Recheck Cond: (id = ANY ($1))
Index Cond: (id = ANY ($1))

y las exploraciones de mapa de bits en el plan.

Answer 2

Sospecho where id in (1,2,3,4,5,6,7,8,9,10) puede optimizarse y la where id in (select ...) no puede, la razón es que (1,2,3,4,5,6,7,8,9,10) es una expresión constante, mientras que la select no lo es.

Qué tal si:

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