改进连接查询 postgresql/postgis

Question

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其变慢！

我有两张桌子：

• 统计信息（id、field1、[...]、field10）
• 几何（id、geom）

我创建了索引：

• statistics.id
• geometry.id
• 几何 (st_x(st_centroid(st_transform(geom, 2154))), st_y(st_centroid(st_transform(geom, 2154)))))

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？

下面是表格的架构

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
);

每个表大约有 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);

对于信息，我在geometry_id 和statistics_id 上尝试了不同的索引（btree 和gin）。

Answer 1

我认为您的查询没有任何问题。

检查事项

• (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，这需要时间。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，您会更好。
• 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。
• 如果您想要执行地理搜索，也不是正确的索引。但我们可以稍后再谈

尝试的事情

首先是where like。

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

然后就是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 表中创建预先计算的x, y 列

SELECT statistics.*,
       geometry.x,
       geometry.y,
FROM statistics
JOIN geometry ON statistics.id = geometry.id 

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

比较每个步骤之间的时间，以检查哪里花费的时间最多。