【发布时间】:2016-04-19 14:09:01
【问题描述】:
我想检索另一组点的给定范围内的所有点。比方说,找到任何地铁站 500m 范围内的所有商店。
我写了这个查询,很慢,想优化一下:
SELECT DISCTINCT ON(locations.id) locations.id FROM locations, pois
WHERE pois.poi_kind = 'subway'
AND ST_DWithin(locations.coordinates, pois.coordinates, 500, false);
我正在运行最新版本的 Postgres 和 PostGis(Postgres 9.5、PostGis 2.2.1)
这是表元数据:
Table "public.locations"
Column | Type | Modifiers
--------------------+-----------------------------+--------------------------------------------------------
id | integer | not null default nextval('locations_id_seq'::regclass)
coordinates | geometry |
Indexes:
"locations_coordinates_index" gist (coordinates)
Table "public.pois"
Column | Type | Modifiers
-------------+-----------------------------+---------------------------------------------------
id | integer | not null default nextval('pois_id_seq'::regclass)
coordinates | geometry |
poi_kind_id | integer |
Indexes:
"pois_pkey" PRIMARY KEY, btree (id)
"pois_coordinates_index" gist (coordinates)
"pois_poi_kind_id_index" btree (poi_kind_id)
Foreign-key constraints:
"pois_poi_kind_id_fkey" FOREIGN KEY (poi_kind_id) REFERENCES poi_kinds(id)
这是 EXPLAIN (ANALYZE, BUFFERS) 的结果:
Unique (cost=2407390.71..2407390.72 rows=2 width=4) (actual time=3338.080..3338.252 rows=918 loops=1)
Buffers: shared hit=559
-> Sort (cost=2407390.71..2407390.72 rows=2 width=4) (actual time=3338.079..3338.145 rows=963 loops=1)
Sort Key: locations.id
Sort Method: quicksort Memory: 70kB
Buffers: shared hit=559
-> Nested Loop (cost=0.00..2407390.71 rows=2 width=4) (actual time=2.466..3337.835 rows=963 loops=1)
Join Filter: (((pois.coordinates)::geography && _st_expand((locations.coordinates)::geography, 500::double precision)) AND ((locations.coordinates)::geography && _st_expand((pois.coordinates)::geography, 500::double precision)) AND _st_dwithin((pois.coordinates)::geography, (locations.coordinates)::geography, 500::double precision, false))
Rows Removed by Join Filter: 4531356
Buffers: shared hit=559
-> Seq Scan on locations (cost=0.00..791.68 rows=24168 width=36) (actual time=0.005..3.100 rows=24237 loops=1)
Buffers: shared hit=550
-> Materialize (cost=0.00..10.47 rows=187 width=32) (actual time=0.000..0.009 rows=187 loops=24237)
Buffers: shared hit=6
-> Seq Scan on pois (cost=0.00..9.54 rows=187 width=32) (actual time=0.015..0.053 rows=187 loops=1)
Filter: (poi_kind_id = 3)
Rows Removed by Filter: 96
Buffers: shared hit=6
Planning time: 0.184 ms
Execution time: 3338.304 ms
(20 rows)
【问题讨论】:
-
它们是几何还是地理?
-
@FrancescoD'Alesio 几何
-
您使用的是公制坐标系吗?结果慢但正确吗?
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@FrancescoD'Alesio 是的,它是一个公制系统。是的,当前结果是正确的,但太慢了(大约 3 秒才能匹配 100.000 家商店和 200 个地铁站)
标签: sql postgresql postgis query-performance nearest-neighbor