改进连接查询 postgresql/postgis

Improving join query postgresql/postgis

我相信 postgresql 可以更快地处理我的查询,但每次尝试修改它都会使它变慢!

我有 2 个 table:

我在 :

上创建了索引

这里是查询

EXPLAIN ANALYZE SELECT 
statistics.*,
st_x(st_centroid(st_transform(geometry.geom, 2154))) AS x,
st_y(st_centroid(st_transform(geometry.geom, 2154))) AS y

FROM statistics
 JOIN geometry ON statistics.id = geometry.id 

WHERE statistics.id not like '97%';

这是结果

Hash Join  (cost=1294.66..5158.10 rows=36593 width=342) (actual time=20.788..1085.257 rows=36552 loops=1)
Hash Cond: (geometry.id = (statistics.id)::text)
->  Seq Scan on geometry  (cost=0.00..2445.46 rows=36593 width=279) (actual time=0.010..25.271 rows=36597 loops=1)
    Filter: (id !~~ '97%'::text)
->  Hash  (cost=835.96..835.96 rows=36696 width=69) (actual time=19.892..19.892 rows=36696 loops=1)
    Buckets: 4096  Batches: 1  Memory Usage: 3780kB
    ->  Seq Scan on statistics  (cost=0.00..835.96 rows=36696 width=69) (actual time=0.005..6.871 rows=36696 loops=1)
Planning time: 0.401 ms
Execution time: 1088.612 ms

最昂贵的操作是哈希连接。您将如何重组那里的查询以获得更好的结果?

下面是 tables

的架构
CREATE TABLE "statistics" (
    "REG" integer,
    "DEP" character varying(10),
    "COM" character varying(50),
    "D03" integer,
    "D04" integer,
    "D05" integer,
    "D06" integer,
    "D07" integer,
    "D08" integer,
    "D09" integer,
    "D10" integer,
    "D11" integer,
    "D12" integer,
    "D13" integer,
    "id" text
);

CREATE TABLE geometry (  
    id text NOT NULL,
    id_geo numeric(10,0),
    cm_code character varying(3),
    name character varying(50),
    status character varying(20),
    lat integer,
    long integer,
    lat_centroid integer,
    long_centroid integer,
    z_ smallint,
    area numeric(10,0),
    population double precision,
    code_ct character varying(2),
    code_r character varying(1),
    code_dp character varying(2),
    name_dp character varying(30),
    code_rg character varying(2),
    geom geometry(MultiPolygon,4326),
    x real,
    y real
);

每个 table

中大约有 40 000 行

索引已创建如下

CREATE INDEX statistics_id_idx ON public.statistics USING btree (id COLLATE pg_catalog."default");
CREATE INDEX geometry_geom_idx ON public.geometry USING gist (geom);
CREATE INDEX geometry_id_gin2 ON public.geometry  USING gin (id COLLATE pg_catalog."default" gin_trgm_ops);

为了获得信息,我在 geometry_id 和 statistics_id 上尝试了不同的索引(btree 和 gin)。

我没有发现您的查询有任何问题。

要检查的事情

  • (geometry.id = (statistics.id)::text) 两个字段的数据类型相同吗?
  • WHERE statistics.id not like '97%';LIKE '%me' 永远不会使用索引,但 LIKE 'me%' 可能会使用索引。 Why doesnt use index?
  • st_x(st_centroid(st_transform(geometry.geom, 2154))) AS x,是一个函数,需要时间。需要转换坐标,然后提取一个值。如果计算该值并将其存储在一个字段中,你会更好。
  • 您的几何索引对此查询没有任何影响,因为您正在计算一个值而不是搜索某些内容。
  • 如果您想要执行索引不正确的地理搜索。不过我们可以稍后再谈

值得尝试的事情

首先是where like.

SELECT *
FROM statistics
WHERE statistics.id not like '97%';

然后 join

SELECT statistics.*,
       geometry.geom
FROM statistics
JOIN geometry ON statistics.id = geometry.id 

然后加入 + st_x

SELECT statistics.*,
       st_x(st_centroid(st_transform(geometry.geom, 2154))) AS x,
       st_y(st_centroid(st_transform(geometry.geom, 2154))) AS y
FROM statistics
JOIN geometry ON statistics.id = geometry.id 

然后在 geometry table

中创建预计算 x, y
SELECT statistics.*,
       geometry.x,
       geometry.y,
FROM statistics
JOIN geometry ON statistics.id = geometry.id 

然后加入+st_x+where like然后加入+geometry.xy+where like

比较每个步骤之间的时间以检查哪个步骤花费的时间最多。