PostgreSQL如何快速给指定表每个字段创建索引
小编给大家分享一下PostgreSQL如何快速给指定表每个字段创建索引,相信大部分人都还不怎么了解,因此分享这篇文章给大家参考一下,希望大家阅读完这篇文章后大有收获,下面让我们一起去了解一下吧!
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数据类型与索引类型匹配的通用选择方法
大类选择
Code | Category | 推荐 索引接口 |
---|---|---|
A | Array types | gin |
B | Boolean types | btree , 不建议加索引,选择性不好 |
C | Composite types | - |
D | Date/time types | btree |
E | Enum types | - |
G | Geometric types | gist |
I | Network address types | gist, spgist |
N | Numeric types | btree |
P | Pseudo-types | - |
R | Range types | gist, spgist |
S | String types | btree : varchar text_pattern_ops , bpchar bpchar_pattern_ops ; 模糊查询(pg_trgm) gin : varchar gin_trgm_ops |
T | Timespan types | btree |
U | User-defined types | - |
V | Bit-string types | - |
X | unknown type | - |
小类选择
select typcategory , typname from pg_type order by 1,2;
Code | Category | 推荐 索引接口 |
---|---|---|
U | aclitem | - |
U | box2d | - |
U | box2df | - |
U | box3d | - |
U | bytea | - |
U | cid | - |
U | gbtreekey16 | - |
U | gbtreekey32 | - |
U | gbtreekey4 | - |
U | gbtreekey8 | - |
U | gbtreekey_var | - |
U | geography | gist |
U | geometry | gist |
U | gidx | - |
U | gtrgm | - |
U | gtsvector | - |
U | json | gin |
U | jsonb | gin , OPS : jsonb_path_ops |
U | macaddr | - |
U | macaddr8 | - |
U | pg_lsn | - |
U | pgis_abs | - |
U | raster | - |
U | refcursor | - |
U | smgr | - |
U | spheroid | - |
U | tid | - |
U | tsquery | gin, rum |
U | tsvector | gin, rum |
U | txid_snapshot | - |
U | uuid | hash |
U | xid | btree |
U | xml | - |
依据以上规则,生成create index的SQL
写一个UDF函数,将以上规格写到UDF里面,自动生成每一列的索引SQL,自动使用合适的索引方法,OPS。
create or replace function gen_whole_index_sqls( v_nsp name, v_tbl name, v_tbs name ) returns text[] as $$ declare v_attname name; v_typid oid; v_typca "char"; v_typname name; res text[]; idxprefix text := to_char(clock_timestamp(),'yyyymmddhh34miss'); idxsuffix int := 1; sql text := 'create index IF NOT EXISTS i'||idxprefix||'_%s on '||quote_ident(v_nsp)||'.'||quote_ident(v_tbl)||' using %s (%I %s) tablespace '||quote_ident(v_tbs)||' ;'; begin for v_attname,v_typid in select attname,atttypid from pg_attribute where not attisdropped and attnum >= 1 and attrelid=(quote_ident(v_nsp)||'.'||quote_ident(v_tbl))::regclass loop select typcategory,typname into v_typca,v_typname from pg_type where oid=v_typid; case v_typca when 'A' then res := array_append(res, format(sql,idxsuffix,'gin',v_attname,'')); when 'D', 'N', 'T' then res := array_append(res, format(sql,idxsuffix,'btree',v_attname,'')); when 'S' then if v_typname='text' or v_typname='varchar' then res := array_append(res, format(sql,idxsuffix,'btree',v_attname,'text_pattern_ops')); elsif v_typname='bpchar' then res := array_append(res, format(sql,idxsuffix,'btree',v_attname,'bpchar_pattern_ops')); else res := array_append(res, format(sql,idxsuffix,'btree',v_attname,'')); end if; -- 如果字符串要支持模糊查询,使用gin索引 -- if v_typname='text' or v_typname='varchar' then -- res := array_append(res, format(sql,idxsuffix,'gin',v_attname,'gin_trgm_ops')); -- else -- res := array_append(res, format(sql,idxsuffix,'btree',v_attname,'')); -- end if; when 'G' then if v_typname not in ('line') then res := array_append(res, format(sql,idxsuffix,'gist',v_attname,'')); else continue; end if; when 'I', 'R' then res := array_append(res, format(sql,idxsuffix,'gist',v_attname,'')); -- 可选spgist -- res := array_append(res, format(sql,idxsuffix,'spgist',v_attname,'')); when 'U' then case v_typname when 'geography', 'geometry' then res := array_append(res, format(sql,idxsuffix,'gist',v_attname,'')); when 'jsonb' then res := array_append(res, format(sql,idxsuffix,'gin',v_attname,'jsonb_path_ops')); -- 可选默认gin ops -- https://www.postgresql.org/docs/11/static/datatype-json.html#JSON-INDEXING -- res := array_append(res, format(sql,idxsuffix,'gin',v_attname,'')); when 'tsvector' then res := array_append(res, format(sql,idxsuffix,'gin',v_attname,'')); when 'uuid', 'xid' then res := array_append(res, format(sql,idxsuffix,'hash',v_attname,'')); else continue; end case; else continue; end case; idxsuffix := idxsuffix+1; end loop; return res; end; $$ language plpgsql strict;
测试
1、创建测试表,包含各种数据类型
create table "你好t12" ( c1 int, "-_c2&a-b" int8, c3 text, c4 varchar(1000), c5 char(1000), c6 "char", c7 timestamp, c8 interval, c9 int[], c10 tsvector, c11 tsquery, c12 time, c13 date, c14 numeric, c15 float, c16 point, c17 box, c18 line, c19 circle, c20 inet, c21 cidr, c22 int8range, c23 tsrange, c24 geometry, c25 geography, c26 uuid, c27 xid, c28 json, c29 jsonb );
2、使用本文提供的UDF,生成CREATE INDEX SQL
select * from unnest(gen_whole_index_sqls('public','你好t12','pg_default')); unnest ------------------------------------------------------------------------------------------------------------------------------ create index IF NOT EXISTS i20180903171836_1 on public."你好t12" using btree (c1 ) tablespace pg_default ; create index IF NOT EXISTS i20180903171836_2 on public."你好t12" using btree ("-_c2&a-b" ) tablespace pg_default ; create index IF NOT EXISTS i20180903171836_3 on public."你好t12" using btree (c3 text_pattern_ops) tablespace pg_default ; create index IF NOT EXISTS i20180903171836_4 on public."你好t12" using btree (c4 text_pattern_ops) tablespace pg_default ; create index IF NOT EXISTS i20180903171836_5 on public."你好t12" using btree (c5 bpchar_pattern_ops) tablespace pg_default ; create index IF NOT EXISTS i20180903171836_6 on public."你好t12" using btree (c6 ) tablespace pg_default ; create index IF NOT EXISTS i20180903171836_7 on public."你好t12" using btree (c7 ) tablespace pg_default ; create index IF NOT EXISTS i20180903171836_8 on public."你好t12" using btree (c8 ) tablespace pg_default ; create index IF NOT EXISTS i20180903171836_9 on public."你好t12" using gin (c9 ) tablespace pg_default ; create index IF NOT EXISTS i20180903171836_10 on public."你好t12" using gin (c10 ) tablespace pg_default ; create index IF NOT EXISTS i20180903171836_11 on public."你好t12" using btree (c12 ) tablespace pg_default ; create index IF NOT EXISTS i20180903171836_12 on public."你好t12" using btree (c13 ) tablespace pg_default ; create index IF NOT EXISTS i20180903171836_13 on public."你好t12" using btree (c14 ) tablespace pg_default ; create index IF NOT EXISTS i20180903171836_14 on public."你好t12" using btree (c15 ) tablespace pg_default ; create index IF NOT EXISTS i20180903171836_15 on public."你好t12" using gist (c16 ) tablespace pg_default ; create index IF NOT EXISTS i20180903171836_16 on public."你好t12" using gist (c17 ) tablespace pg_default ; create index IF NOT EXISTS i20180903171836_17 on public."你好t12" using gist (c19 ) tablespace pg_default ; create index IF NOT EXISTS i20180903171836_18 on public."你好t12" using gist (c20 ) tablespace pg_default ; create index IF NOT EXISTS i20180903171836_19 on public."你好t12" using gist (c21 ) tablespace pg_default ; create index IF NOT EXISTS i20180903171836_20 on public."你好t12" using gist (c22 ) tablespace pg_default ; create index IF NOT EXISTS i20180903171836_21 on public."你好t12" using gist (c23 ) tablespace pg_default ; create index IF NOT EXISTS i20180903171836_22 on public."你好t12" using gist (c24 ) tablespace pg_default ; create index IF NOT EXISTS i20180903171836_23 on public."你好t12" using gist (c25 ) tablespace pg_default ; create index IF NOT EXISTS i20180903171836_24 on public."你好t12" using hash (c26 ) tablespace pg_default ; create index IF NOT EXISTS i20180903171836_25 on public."你好t12" using hash (c27 ) tablespace pg_default ; create index IF NOT EXISTS i20180903171836_26 on public."你好t12" using gin (c29 jsonb_path_ops) tablespace pg_default ; (26 rows)
3、创建索引测试
使用之前提到的并行跑后台任务的方法,并行创建多个索引,充分利用硬件资源加速。
《PostgreSQL dblink异步调用实践,跑并行多任务 - 例如开N个并行后台任务创建索引, 开N个后台任务跑若干SQL》
select * from run_sqls_parallel(6, gen_whole_index_sqls('public','你好t12','pg_default')) as t(a text); NOTICE: the last 3 tasks running. NOTICE: whole tasks done. run_sqls_parallel ------------------- (1 row)
4、检验
postgres=# \d 你好t12 Table "public.你好t12" Column | Type | Collation | Nullable | Default ----------+-----------------------------+-----------+----------+--------- c1 | integer | | | -_c2&a-b | bigint | | | c3 | text | | | c4 | character varying(1000) | | | c5 | character(1000) | | | c6 | "char" | | | c7 | timestamp without time zone | | | c8 | interval | | | c9 | integer[] | | | c10 | tsvector | | | c11 | tsquery | | | c12 | time without time zone | | | c13 | date | | | c14 | numeric | | | c15 | double precision | | | c16 | point | | | c17 | box | | | c18 | line | | | c19 | circle | | | c20 | inet | | | c21 | cidr | | | c22 | int8range | | | c23 | tsrange | | | c24 | geometry | | | c25 | geography | | | c26 | uuid | | | c27 | xid | | | c28 | json | | | c29 | jsonb | | | Indexes: "i20180903171855_1" btree (c1) "i20180903171855_10" gin (c10) "i20180903171855_11" btree (c12) "i20180903171855_12" btree (c13) "i20180903171855_13" btree (c14) "i20180903171855_14" btree (c15) "i20180903171855_15" gist (c16) "i20180903171855_16" gist (c17) "i20180903171855_17" gist (c19) "i20180903171855_18" gist (c20) "i20180903171855_19" gist (c21) "i20180903171855_2" btree ("-_c2&a-b") "i20180903171855_20" gist (c22) "i20180903171855_21" gist (c23) "i20180903171855_22" gist (c24) "i20180903171855_23" gist (c25) "i20180903171855_24" hash (c26) "i20180903171855_25" hash (c27) "i20180903171855_26" gin (c29 jsonb_path_ops) "i20180903171855_3" btree (c3 text_pattern_ops) "i20180903171855_4" btree (c4 text_pattern_ops) "i20180903171855_5" btree (c5 bpchar_pattern_ops) "i20180903171855_6" btree (c6) "i20180903171855_7" btree (c7) "i20180903171855_8" btree (c8) "i20180903171855_9" gin (c9)
postgres=# \di i20180903171855_* List of relations Schema | Name | Type | Owner | Table --------+--------------------+-------+----------+--------- public | i20180903171855_1 | index | postgres | 你好t12 public | i20180903171855_10 | index | postgres | 你好t12 public | i20180903171855_11 | index | postgres | 你好t12 public | i20180903171855_12 | index | postgres | 你好t12 public | i20180903171855_13 | index | postgres | 你好t12 public | i20180903171855_14 | index | postgres | 你好t12 public | i20180903171855_15 | index | postgres | 你好t12 public | i20180903171855_16 | index | postgres | 你好t12 public | i20180903171855_17 | index | postgres | 你好t12 public | i20180903171855_18 | index | postgres | 你好t12 public | i20180903171855_19 | index | postgres | 你好t12 public | i20180903171855_2 | index | postgres | 你好t12 public | i20180903171855_20 | index | postgres | 你好t12 public | i20180903171855_21 | index | postgres | 你好t12 public | i20180903171855_22 | index | postgres | 你好t12 public | i20180903171855_23 | index | postgres | 你好t12 public | i20180903171855_24 | index | postgres | 你好t12 public | i20180903171855_25 | index | postgres | 你好t12 public | i20180903171855_26 | index | postgres | 你好t12 public | i20180903171855_3 | index | postgres | 你好t12 public | i20180903171855_4 | index | postgres | 你好t12 public | i20180903171855_5 | index | postgres | 你好t12 public | i20180903171855_6 | index | postgres | 你好t12 public | i20180903171855_7 | index | postgres | 你好t12 public | i20180903171855_8 | index | postgres | 你好t12 public | i20180903171855_9 | index | postgres | 你好t12 (26 rows)
1、本文提供了一个UDF,用于生成创建索引的SQL(返回SQL数组)
gen_whole_index_sqls('name space','表名','表空间名')
2、使用之前提到的并行跑后台任务的方法,并行创建多个索引,充分利用硬件资源加速。
例如
select * from run_sqls_parallel(6, gen_whole_index_sqls('public','你好t12','pg_default')) as t(a text);
3、结合表的统计信息(analyze table后),可以把生成CREATE INDEX SQL做得更加完美。
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