我有一个datavalue表，行数约为200M左右，site_id和paramter_id都有索引。我需要执行诸如“使用数据返回所有站点”和“使用数据返回所有参数”之类的查询。 site表只有200行左右，而parameter表只有100行左右。
site查询速度很快，并使用索引：
EXPLAIN ANALYZE
select *
from site
where exists (
select 1 from datavalue
where datavalue.site_id = site.id limit 1
);
Seq Scan on site (cost=0.00..64.47 rows=64 width=113) (actual time=0.046..1.106 rows=89 loops=1)
Filter: (SubPlan 1)
Rows Removed by Filter: 39
SubPlan 1
-> Limit (cost=0.44..0.47 rows=1 width=0) (actual time=0.008..0.008 rows=1 loops=128)
-> Index Only Scan using ix_datavalue_site_id on datavalue (cost=0.44..8142.71 rows=248930 width=0) (actual time=0.008..0.008 rows=1 loops=128)
Index Cond: (site_id = site.id)
Heap Fetches: 0
Planning time: 0.361 ms
Execution time: 1.149 ms
对参数的相同查询相当慢，并且不使用索引：
EXPLAIN ANALYZE
select *
from parameter
where exists (
select 1 from datavalue
where datavalue.parameter_id = parameter.id limit 1
);
Seq Scan on parameter (cost=0.00..20.50 rows=15 width=2648) (actual time=2895.972..21331.701 rows=15 loops=1)
Filter: (SubPlan 1)
Rows Removed by Filter: 6
SubPlan 1
-> Limit (cost=0.00..0.34 rows=1 width=0) (actual time=1015.790..1015.790 rows=1 loops=21)
-> Seq Scan on datavalue (cost=0.00..502127.10 rows=1476987 width=0) (actual time=1015.786..1015.786 rows=1 loops=21)
Filter: (parameter_id = parameter.id)
Rows Removed by Filter: 7739355
Planning time: 0.123 ms
Execution time: 21331.736 ms
这里的平局是什么？或者，这是一个很好的方法吗？
一些表格描述：
id BIGINT DEFAULT nextval('datavalue_id_seq'::regclass) NOT NULL,
value DOUBLE PRECISION NOT NULL,
site_id INTEGER NOT NULL,
parameter_id INTEGER NOT NULL,
deployment_id INTEGER,
instrument_id INTEGER,
invalid BOOLEAN,
Indexes:
"datavalue_pkey" PRIMARY KEY, btree (id)
"datavalue_datetime_utc_site_id_parameter_id_instrument_id_key" UNIQUE CONSTRAINT, btree (datetime_utc, site_id, parameter_id, instrument_id)
"ix_datavalue_instrument_id" btree (instrument_id)
"ix_datavalue_parameter_id" btree (parameter_id)
"ix_datavalue_site_id" btree (site_id)
"tmp_idx" btree (site_id, datetime_utc)
Foreign-key constraints:
"datavalue_instrument_id_fkey" FOREIGN KEY (instrument_id) REFERENCES instrument(id) ON UPDATE CASCADE ON DELETE CASCADE
"datavalue_parameter_id_fkey" FOREIGN KEY (parameter_id) REFERENCES parameter(id) ON UPDATE CASCADE ON DELETE CASCADE
"datavalue_site_id_fkey" FOREIGN KEY (site_id) REFERENCES coastal.site(id) ON UPDATE CASCADE ON DELETE CASCADE
"datavalue_statistic_type_id_fkey"
编辑：这是计数分布
select count(parameter_id), parameter_id from datavalue group by parameter_id
88169 14
2889171 8
15805 17
8570 12
4257262 21
3947049 15
1225902 2
4091090 3
103877 10
633764 11
994442 18
49232 20
14935 4
563638 13
2955919 7
答案 0 :(得分：3)
更新：如a_horse_with_no_name所述，您可以删除LIMIT 1，查询将使用索引。
显然PostgreSQL错误地认为如果你做一个子查询而忽略了LIMIT 1，它会触及整个数据库。（事实证明这是不必要的。）
我在笔记本电脑上生成了相同的发行版：
create table testtbl (id integer, par_id integer);
insert into testtbl (id, par_id) values (0,0 );
insert into testtbl (id, par_id) select "generate_series", 4 from generate_series((select max(id) from testtbl), (select max(id) from testtbl)+14935);
insert into testtbl (id, par_id) select "generate_series", 12 from generate_series((select max(id) from testtbl), (select max(id) from testtbl)+8570);
insert into testtbl (id, par_id) select "generate_series", 17 from generate_series((select max(id) from testtbl), (select max(id) from testtbl)+15805);
insert into testtbl (id, par_id) select "generate_series", 20 from generate_series((select max(id) from testtbl), (select max(id) from testtbl)+49232);
insert into testtbl (id, par_id) select "generate_series", 14 from generate_series((select max(id) from testtbl), (select max(id) from testtbl)+88169);
insert into testtbl (id, par_id) select "generate_series", 10 from generate_series((select max(id) from testtbl), (select max(id) from testtbl)+103877);
insert into testtbl (id, par_id) select "generate_series", 2 from generate_series((select max(id) from testtbl), (select max(id) from testtbl)+1225902);
insert into testtbl (id, par_id) select "generate_series", 8 from generate_series((select max(id) from testtbl), (select max(id) from testtbl)+2889171);
insert into testtbl (id, par_id) select "generate_series", 7 from generate_series((select max(id) from testtbl), (select max(id) from testtbl)+2955919);
insert into testtbl (id, par_id) select "generate_series", 3 from generate_series((select max(id) from testtbl), (select max(id) from testtbl)+4091090);
insert into testtbl (id, par_id) select "generate_series", 13 from generate_series((select max(id) from testtbl), (select max(id) from testtbl)+563638);
insert into testtbl (id, par_id) select "generate_series", 11 from generate_series((select max(id) from testtbl), (select max(id) from testtbl)+633764);
insert into testtbl (id, par_id) select "generate_series", 18 from generate_series((select max(id) from testtbl), (select max(id) from testtbl)+994442);
insert into testtbl (id, par_id) select "generate_series", 15 from generate_series((select max(id) from testtbl), (select max(id) from testtbl)+3947049);
insert into testtbl (id, par_id) select "generate_series", 21 from generate_series((select max(id) from testtbl), (select max(id) from testtbl)+4257262);
delete from testtbl where id = 0 and par_id = 0;
create index testtbl_paridx on testtbl (par_id);
create table parameter (id integer);
insert into parameter select * from generate_series (1, 28);
analyze testtbl;
然后，如果我运行查询：
testdb=# explain analyze select * from parameter where exists (select 1 from testtbl where testtbl.par_id = parameter.id limit 1);
QUERY PLAN
---------------------------------------------------------------------------------------------------------------------------------
Seq Scan on parameter (cost=0.00..643.29 rows=1200 width=4) (actual time=4083.514..54216.575 rows=15 loops=1)
Filter: (SubPlan 1)
Rows Removed by Filter: 13
SubPlan 1
-> Limit (cost=0.00..0.25 rows=1 width=0) (actual time=1936.299..1936.299 rows=1 loops=28)
-> Seq Scan on testtbl (cost=0.00..369619.35 rows=1455927 width=0) (actual time=1936.294..1936.294 rows=1 loops=28)
Filter: (par_id = parameter.id)
Rows Removed by Filter: 14870626
Planning time: 0.151 ms
Execution time: 54216.620 ms
(10 rows)
如果我禁用顺序扫描：
testdb=# set local enable_seqscan = off;
SET
testdb=# explain analyze select * from parameter where exists (select 1 from testtbl where testtbl.par_id = parameter.id limit 1);
QUERY PLAN
-------------------------------------------------------------------------------------------------------------------------------------------------------
Seq Scan on parameter (cost=10000000000.00..10000001395.02 rows=1200 width=4) (actual time=0.077..0.563 rows=15 loops=1)
Filter: (SubPlan 1)
Rows Removed by Filter: 13
SubPlan 1
-> Limit (cost=0.44..0.57 rows=1 width=0) (actual time=0.019..0.019 rows=1 loops=28)
-> Index Only Scan using ix_testtbl_par on testtbl (cost=0.44..188678.87 rows=1455927 width=0) (actual time=0.018..0.018 rows=1 loops=28)
Index Cond: (par_id = parameter.id)
Heap Fetches: 15
Planning time: 0.169 ms
Execution time: 0.605 ms
(10 rows)
速度快，但有点黑客。您希望使用SET LOCAL，以便不对所有查询禁用顺序扫描。 SET LOCAL在事务提交之前有效。
更新：更好的选择是按照a_horse_with_no_name的建议完全删除LIMIT 1。
testdb=# explain analyze select * from parameter where exists (select 1 from testtbl where testtbl.par_id = parameter.id );
QUERY PLAN
----------------------------------------------------------------------------------------------------------------------------------------------
Nested Loop Semi Join (cost=0.44..1591.08 rows=1200 width=4) (actual time=0.070..0.492 rows=15 loops=1)
-> Seq Scan on parameter (cost=0.00..34.00 rows=2400 width=4) (actual time=0.010..0.018 rows=28 loops=1)
-> Index Only Scan using testtbl_paridx on testtbl (cost=0.44..29379.76 rows=1455923 width=4) (actual time=0.016..0.016 rows=1 loops=28)
Index Cond: (par_id = parameter.id)
Heap Fetches: 15
Planning time: 0.216 ms
Execution time: 0.532 ms
(7 rows)