postgresql关于like%xxx%的优化操作
任何一个关系型数据库关于模糊匹配（like)的优化都是一件痛苦的事，相对而言，诸如like 'abc%'之类的还好一点，可以通过创建索引来优化，但对于like 'c%'之类的，真的就没有办法了。
这里介绍一种postgresql关于like 'c%'的优化方法，是基于全文检索的特性来实现的。
测试数据准备（环境centos6.5 + postgresql 9.6.1）。
postgres=# create table ts(id int,name text);
CREATE TABLE
postgres=# \d ts
Table "public.ts"
Column | Type | Modifiers
--------+---------+-----------
id | integer |
name | text |
postgres=# insert into ts select n,n||'_pjy' from generate_series(1,2000) n;
INSERT 0 2000
postgres=# insert into ts select n,n||'_mdh' from generate_series(1,2000000) n;
INSERT 0 2000000
postgres=# insert into ts select n,n||'_lmm' from generate_series(1,2000000) n;
INSERT 0 2000000
postgres=# insert into ts select n,n||'_syf' from generate_series(1,2000000) n;
INSERT 0 2000000
postgres=# insert into ts select n,n||'_wbd' from generate_series(1,2000000) n;
INSERT 0 2000000
postgres=# insert into ts select n,n||'_hhh' from generate_series(1,2000000) n;
INSERT 0 2000000
postgres=# insert into ts select n,n||'_sjw' from generate_series(1,2000000) n;
INSERT 0 2000000
postgres=# insert into ts select n,n||'_jjs' from generate_series(1,2000000) n;
INSERT 0 2000000
postgres=# insert into ts select n,n||'_ymd' from generate_series(1,2000000) n;
INSERT 0 2000000
postgres=# insert into ts select n,n||'_biu' from generate_series(1,2000000) n;
INSERT 0 2000000
postgres=# insert into ts select n,n||'_dfl' from generate_series(1,2000000) n;
INSERT 0 2000000
postgres=# select count(*) from ts;
count
----------
20002000
(1 row)
开始测试：
postgres=# explain analyze select * from ts where name like '%pjy%';
QUERY PLAN
-----------------------------------------------------------------------------------------------------------
Seq Scan on ts (cost=0.00..358144.05 rows=2000 width=15) (actual time=0.006..1877.087 rows=2000 loops=1)
Filter: (name ~~ '%pjy%'::text)
Rows Removed by Filter: 20000000
Planning time: 0.031 ms
Execution time: 1877.178 ms
(5 rows)
关键一步：
postgres=# create index idx_name on ts using gin (to_tsvector('english',name));
CREATE INDEX
postgres=# vacuum analyze ts;
VACUUM
postgres=# \d ts
Table "public.ts"
Column | Type | Modifiers
--------+---------+-----------
id | integer |
name | text |
Indexes:
"idx_name" gin (to_tsvector('english'::regconfig, name))
postgres=# explain analyze select * from ts where to_tsvector('english',name) @@ to_tsquery('pjy');
QUERY PLAN
---------------------------------------------------------------------------------------------------------------------
Bitmap Heap Scan on ts (cost=39.75..8187.70 rows=2000 width=15) (actual time=0.016..0.016 rows=0 loops=1)
Recheck Cond: (to_tsvector('english'::regconfig, name) @@ to_tsquery('pjy'::text))
-> Bitmap Index Scan on idx_name (cost=0.00..39.25 rows=2000 width=0) (actual time=0.016..0.016 rows=0 loops=1)
Index Cond: (to_tsvector('english'::regconfig, name) @@ to_tsquery('pjy'::text))
Planning time: 0.094 ms
Execution time: 0.036 ms
(6 rows)
大家可以看到，执行时间从2秒下降到了0.04毫秒！！！
关于pg的全文检索，tsvector和tsquery，这里就不详细介绍了，大家可以自己查阅手册。
补充：postgresql子查询优化(提升子查询)
问题背景
在开发项目过程中，客户要求使用gbase8s数据库(基于informix)，简单的分页页面响应很慢。排查发现分页sql是先查询出数据在外面套一层后再取多少条，如果去掉嵌套的一层，直接获取则很快。日常使用中postgresql并没有这样的操作也很快，这是为什么呢？
说明
在数据库实现早期，查询优化器对子查询一般采用嵌套执行的方式，即父查询中的每一行，都要执行一次子查询，这样子查询会执行很多次，效率非常低。
本篇主要讲postgresql针对子查询的优化。
项目中使用子查询的地方非常多，如何写出高效的sql，掌握子查询的优化是非常有必要的。
执行计划对比（gbase8s vs postgresql）:
gbase8s慢sql执行计划：
--gbase8s执行计划
SET EXPLAIN ON ;
SET EXPLAIN FILE TO '/home/gbasedbt/sqexplain.out' ;
select skip 0 first 15 * from ( select * from T_SZGL_JDRY order by T_SZGL_JDRY.updatetime desc ) Estimated Cost: 3207 Estimated # of Rows Returned: 6172 1) gbasedbt.t_szgl_jdry: INDEX PATH (1) Index Name: gbasedbt.i_t_szgl_jdry_updatetime Index Keys: updatetime (Reverse) (Serial, fragments: ALL) QUERY: (OPTIMIZATION TIMESTAMP: 12-21-2017 03:20:43) ------ select skip 0 first 15 * from ( select * from T_SZGL_JDRY order by T_SZGL_JDRY.updatetime desc ) Estimated Cost: 232 Estimated # of Rows Returned: 6172 1) (Temp Table For Collection Subquery): SEQUENTIAL SCAN Query statistics: ----------------- The final cost of the plan is reduced because of the FIRST n specification in the query. Table map : ---------------------------- Internal name Table name ---------------------------- t1 t_szgl_jdry t2 (Temp Table For Collection Subquery) type table rows_prod est_rows rows_scan time est_cost ------------------------------------------------------------------- scan t1 6173 6172 6173 00:00.05 3207 --查询执行用 222 ms,15行受影响
gbase8s修改后执行计划
select skip 0 first 15 * from T_SZGL_JDRY order by T_SZGL_JDRY.updatetime desc Estimated Cost: 7 Estimated # of Rows Returned: 6172 1) gbasedbt.t_szgl_jdry: INDEX PATH (1) Index Name: gbasedbt.i_t_szgl_jdry_updatetime Index Keys: updatetime (Reverse) (Serial, fragments: ALL) Query statistics: ----------------- The final cost of the plan is reduced because of the FIRST n specification in the query. Table map : ---------------------------- Internal name Table name ---------------------------- t1 t_szgl_jdry type table rows_prod est_rows rows_scan time est_cost ------------------------------------------------------------------- scan t1 15 6172 15 00:00.00 8 QUERY: (OPTIMIZATION TIMESTAMP: 12-21-2017 03:23:25) ------ select 1 from sysusers Estimated Cost: 2 Estimated # of Rows Returned: 1 1) gbasedbt.sysusers: SEQUENTIAL SCAN ... --查询执行用 18 ms,15行受影响
第一个执行计划中 (1) (Temp Table For Collection Subquery): SEQUENTIAL SCAN)可以看出是将子查询的结果查询出来后，在这个基础上获取了15条记录
对比postgresql执行计划
--分页执行计划-不嵌套
db_jcxxzypt=# explain select * from db_jcxx.t_jcxxzy_tjaj order by d_slrq limit 15 offset 0; QUERY PLAN ------------------------------------------------------------------------- Limit (cost=0.44..28.17 rows=15 width=879) -> Index Scan using idx_ttjaj_dslrq on t_jcxxzy_tjaj (cost=0.44..32374439.85 rows=17507700 width=879) (2 rows) --子查询执行计划-嵌套一层 db_jcxxzypt=# explain db_jcxxzypt-# select * from ( db_jcxxzypt(# select * from db_jcxx.t_jcxxzy_tjaj order by d_slrq db_jcxxzypt(# )tab1 limit 15 offset 0; QUERY PLAN ------------------------------------------------------------------------- Limit (cost=0.44..28.32 rows=15 width=879) -> Index Scan using idx_ttjaj_dslrq on t_jcxxzy_tjaj (cost=0.44..32374439.85 rows=17507700 width=879) (2 rows) --子查询执行计划-嵌套两层 db_jcxxzypt=# explain db_jcxxzypt-# select * from ( db_jcxxzypt(# select * from ( db_jcxxzypt(# select * from db_jcxx.t_jcxxzy_tjaj order by d_slrq db_jcxxzypt(# )tab1 )tab2 limit 15 offset 0; QUERY PLAN ------------------------------------------------------------------------- Limit (cost=0.44..28.32 rows=15 width=879) -> Index Scan using idx_ttjaj_dslrq on t_jcxxzy_tjaj (cost=0.44..32374439.85 rows=17507700 width=879) (2 rows)
postgresql的子查询即使嵌套多层，执行计划还是和未嵌套一样。原因就是postgresql在重写sql的阶段上拉子查询（提升子查询），把子查询合并到父查询中。
postgresql子查询优化
子查询可分为三类:一、([not]in/all/any/some),二、([not]exists),三、其他子查询(sjp子查询 选择、投影、连接)
子查询可以出现在目标列、form子句、where子句、join/on子句、group by子句、having子句、orderby子句等位置。
db_jcxxzypt=# explain select * from t_jcxxzy_tjaj aj ,(select * from t_jcxxzy_ajdsr) dsr where dsr.c_ajbm = '1301020400000120090101'; QUERY PLAN ------------------------------------------------------------------------- Nested Loop (cost=0.56..1252119.58 rows=17507700 width=1098) -> Index Scan using idx_tajdsr_cajbm on t_jcxxzy_ajdsr (cost=0.56..8.57 rows=1 width=219) Index Cond: (c_ajbm = '1301020400000120090101'::bpchar) -> Seq Scan on t_jcxxzy_tjaj aj (cost=0.00..1077034.00 rows=17507700 width=879) (4 rows) Time: 1.101 ms
postgresql子链接([not]in,[not]exists,all,some,any)
子查询和子链接区别：子查询是不在表达式中的子句，子链接在表达式中的子句
--in子链接
(1).
db_jcxxzypt=# explain select * from t_jcxxzy_tjaj aj where aj.c_ajbm in (select dsr.c_ajbm from t_jcxxzy_ajdsr dsr); 转化为： select * from t_jcxxzy_tjaj aj join t_jcxxzy_ajdsr dsr aj.c_ajbm = dsr.c_ajbm; QUERY PLAN ------------------------------------------------------------------------- Hash Semi Join (cost=362618.61..5537768.07 rows=7957409 width=879) Hash Cond: (t_jcxxzy_tjaj.c_ajbm = t_jcxxzy_ajdsr.c_ajbm) -> Seq Scan on t_jcxxzy_tjaj (cost=0.00..1077034.00 rows=17507700 width=879) -> Hash (cost=237458.59..237458.59 rows=6817202 width=23) -> Index Only Scan using idx_tajdsr_cajbm on t_jcxxzy_ajdsr (cost=0.56..237458.59 rows=6817202 wi dth=23) (5 rows) --in等价于=any hash semi join表示执行的是两张表的hash半连接， 原始sql中没有(t_jcxxzy_tjaj.c_ajbm = t_jcxxzy_ajdsr.c_ajbm),表明此in子查询被优化，优化后采用hash semi join算法。 (2).相关子查询 --当加入条件where aj.d_slrq='2001-06-14'后不能提升子链接，如果把where aj.d_slrq ='2001-06-14'放到父查询 是支持子链接优化的 db_jcxxzypt=# explain db_jcxxzypt-# select * from t_jcxxzy_tjaj aj where c_ajbm in (select c_ajbm from t_jcxxzy_ajdsr dsr where aj.d_slrq='2001-06-14') ; QUERY PLAN ------------------------------------------------------------------------- Seq Scan on t_jcxxzy_tjaj aj (cost=0.00..2227874766580.75 rows=8753850 width=879) Filter: (SubPlan 1) SubPlan 1 -> Result (cost=0.56..237458.59 rows=6817202 width=23) One-Time Filter: (aj.d_slrq = '2001-06-14'::date) -> Index Only Scan using idx_tajdsr_cajbm on t_jcxxzy_ajdsr dsr (cost=0.56..237458.59 rows=6817 202 width=23) (6 rows (3). -- not in不能提升子链接 db_jcxxzypt=# explain select * from db_jcxx.t_jcxxzy_tjaj where c_ajbm not in (select c_ajbm from db_jcxx.t_jcxxzy_ajdsr); QUERY PLAN ------------------------------------------------------------------------- Seq Scan on t_jcxxzy_tjaj (cost=0.56..2875921362927.06 rows=8753850 width=879) Filter: (NOT (SubPlan 1)) SubPlan 1 -> Materialize (cost=0.56..311489.60 rows=6817202 width=23) -> Index Only Scan using idx_tajdsr_cajbm on t_jcxxzy_ajdsr (cost=0.56..237458.59 rows=6817202 width=23) (5 rows) --not in与<>all含义相同
in子句存在不被优化的可能、当in子句中包含了主查询的表字段，和主查询有相关性时不能提升子链接。
exists子链接
--exists子链接
db_jcxxzypt=# explain
db_jcxxzypt-# select * from t_jcxxzy_tjaj aj where exists (select c_ajbm from t_jcxxzy_ajdsr dsr where aj.c_ajbm = dsr.c_ajbm); QUERY PLAN ------------------------------------------------------------------------- Hash Semi Join (cost=362618.61..5537768.07 rows=7957409 width=879) Hash Cond: (aj.c_ajbm = dsr.c_ajbm) -> Seq Scan on t_jcxxzy_tjaj aj (cost=0.00..1077034.00 rows=17507700 width=879) -> Hash (cost=237458.59..237458.59 rows=6817202 width=23) -> Index Only Scan using idx_tajdsr_cajbm on t_jcxxzy_ajdsr dsr (cost=0.56..237458.59 rows=681720 2 width=23) (5 rows) -- 当加入where aj.c_xzdm = '150622'条件在子链接时，仍然支持上拉 db_jcxxzypt=# explain db_jcxxzypt-# select * from t_jcxxzy_tjaj aj where exists (select c_ajbm from t_jcxxzy_ajdsr dsr where aj.c_xzdm = '150622'); QUERY PLAN ------------------------------------------------------------------------- Nested Loop Semi Join (cost=0.56..1361779.20 rows=5436 width=879) -> Seq Scan on t_jcxxzy_tjaj aj (cost=0.00..1120803.25 rows=5436 width=879) Filter: ((c_xzdm)::text = '150622'::text) -> Index Only Scan using idx_tajdsr_cajbm on t_jcxxzy_ajdsr dsr (cost=0.56..237458.59 rows=6817202 widt h=0) (4 rows) --exists子链接 db_jcxxzypt=# explain db_jcxxzypt-# select * from t_jcxxzy_tjaj aj where exists (select c_ajbm from t_jcxxzy_ajdsr dsr where dsr.c_ajbm='1101120300000120030101') db_jcxxzypt-# ; QUERY PLAN ------------------------------------------------------------------------- Result (cost=4.58..1077038.57 rows=17507700 width=879) One-Time Filter: $0 InitPlan 1 (returns $0) -> Index Only Scan using idx_tajdsr_cajbm on t_jcxxzy_ajdsr dsr (cost=0.56..4.58 rows=1 width=0) Index Cond: (c_ajbm = '1101120300000120030101'::bpchar) -> Seq Scan on t_jcxxzy_tjaj aj (cost=0.00..1077034.00 rows=17507700 width=879) (6 rows)
子查询只执行了一次，作为aj表的参数。
--not exists子链接 db_jcxxzypt=# explain db_jcxxzypt-# select * from t_jcxxzy_tjaj aj where not exists (select c_ajbm from t_jcxxzy_ajdsr dsr); QUERY PLAN ------------------------------------------------------------------------- Result (cost=0.04..1077034.04 rows=17507700 width=879) One-Time Filter: (NOT $0) InitPlan 1 (returns $0) -> Seq Scan on t_jcxxzy_ajdsr dsr (cost=0.00..281210.02 rows=6817202 width=0) -> Seq Scan on t_jcxxzy_tjaj aj (cost=0.00..1077034.00 rows=17507700 width=879) (5 rows)
从执行计划上看，not exists子查询并没有被消除，子查询只是执行了一次，将结果作为aj表的参数。
in和exists都存在不被优化的可能，对于in和exists的选择，当父查询结果集小于子查询结果集则选择exists，如果父查询结果集大于子查询结果集选择in。
所有的all子链接都不支持上拉
db_jcxxzypt=# explain select * from db_jcxx.t_jcxxzy_tjaj where c_ajbm >all(select c_ajbm from db_jcxx.t_jcxxzy_ajdsr); QUERY PLAN ------------------------------------------------------------------------- Seq Scan on t_jcxxzy_tjaj (cost=0.56..2875921362927.06 rows=8753850 width=879) Filter: (SubPlan 1) SubPlan 1 -> Materialize (cost=0.56..311489.60 rows=6817202 width=23) -> Index Only Scan using idx_tajdsr_cajbm on t_jcxxzy_ajdsr (cost=0.56..237458.59 rows=6817202 width=23) (5 rows) db_jcxxzypt=# explain select * from db_jcxx.t_jcxxzy_tjaj where c_ajbm =all(select c_ajbm from db_jcxx.t_jcxxzy_ajdsr); QUERY PLAN ------------------------------------------------------------------------- Seq Scan on t_jcxxzy_tjaj (cost=0.56..2875921362927.06 rows=8753850 width=879) Filter: (SubPlan 1) SubPlan 1 -> Materialize (cost=0.56..311489.60 rows=6817202 width=23) -> Index Only Scan using idx_tajdsr_cajbm on t_jcxxzy_ajdsr (cost=0.56..237458.59 rows=6817202 width=23) (5 rows) db_jcxxzypt=# explain select * from db_jcxx.t_jcxxzy_tjaj where c_ajbm <all(select c_ajbm from db_jcxx.t_jcxxzy_ajdsr); QUERY PLAN ------------------------------------------------------------------------- Seq Scan on t_jcxxzy_tjaj (cost=0.56..2875921362927.06 rows=8753850 width=879) Filter: (SubPlan 1) SubPlan 1 -> Materialize (cost=0.56..311489.60 rows=6817202 width=23) -> Index Only Scan using idx_tajdsr_cajbm on t_jcxxzy_ajdsr (cost=0.56..237458.59 rows=6817202 width=23) (5 rows)
关于all的查询都都是以子查询的形式，不会上拉
some/any
--some和any是等效的
db_jcxxzypt=#explain select * from db_jcxx.t_jcxxzy_tjaj where c_ajbm >some(select c_ajbm from db_jcxx.t_jcxxzy_ajdsr); QUERY PLAN ------------------------------------------------------------------------- - Nested Loop Semi Join (cost=0.56..11316607.35 rows=5835900 width=879) -> Seq Scan on t_jcxxzy_tjaj (cost=0.00..1077034.00 rows=17507700 width=879) -> Index Only Scan using idx_tajdsr_cajbm on t_jcxxzy_ajdsr (cost=0.56..64266.97 rows=2272401 width=23) Index Cond: (c_ajbm < t_jcxxzy_tjaj.c_ajbm) (4 rows) db_jcxxzypt=#explain select * from db_jcxx.t_jcxxzy_tjaj where c_ajbm =some(select c_ajbm from db_jcxx.t_jcxxzy_ajdsr); QUERY PLAN ------------------------------------------------------------------------- Hash Semi Join (cost=362618.61..5537768.07 rows=7957409 width=879) Hash Cond: (t_jcxxzy_tjaj.c_ajbm = t_jcxxzy_ajdsr.c_ajbm) -> Seq Scan on t_jcxxzy_tjaj (cost=0.00..1077034.00 rows=17507700 width=879) -> Hash (cost=237458.59..237458.59 rows=6817202 width=23) -> Index Only Scan using idx_tajdsr_cajbm on t_jcxxzy_ajdsr (cost=0.56..237458.59 rows=6817202 wi dth=23) (5 rows) db_jcxxzypt=#explain select * from db_jcxx.t_jcxxzy_tjaj where c_ajbm <some(select c_ajbm from db_jcxx.t_jcxxzy_ajdsr); QUERY PLAN ------------------------------------------------------------------------- Nested Loop Semi Join (cost=0.56..11316607.35 rows=5835900 width=879) -> Seq Scan on t_jcxxzy_tjaj (cost=0.00..1077034.00 rows=17507700 width=879) -> Index Only Scan using idx_tajdsr_cajbm on t_jcxxzy_ajdsr (cost=0.56..64266.97 rows=2272401 width=23) Index Cond: (c_ajbm > t_jcxxzy_tjaj.c_ajbm) (4 rows) --some中未出现子查询，dsr表都被上拉到父查询中，与aj表进行嵌套半连接和hash半连接
这些查询中all是完全不支持上拉子子链接的，而in和exists存在不被上拉的可能。
不可上拉的子查询
不支持带有with子句的格式，集合操作、聚集函数(aggregates、group、distinct)、cte、having、limit/offset等子句格式
db_jcxxzypt=# explain select * from t_jcxxzy_tjaj aj ,(select * from t_jcxxzy_ajdsr limit 10) dsr where dsr.c_ajbm = '1301020400000120090101'; QUERY PLAN ------------------------------------------------------------------------- Nested Loop (cost=0.00..1252111.54 rows=17507700 width=1098) -> Subquery Scan on dsr (cost=0.00..0.54 rows=1 width=219) Filter: (dsr.c_ajbm = '1301020400000120090101'::bpchar) -> Limit (cost=0.00..0.41 rows=10 width=219) -> Seq Scan on t_jcxxzy_ajdsr (cost=0.00..281210.02 rows=6817202 width=219) -> Seq Scan on t_jcxxzy_tjaj aj (cost=0.00..1077034.00 rows=17507700 width=879) (6 rows) Time: 0.958 ms
上拉子查询后，父级的多个表之间的连接顺序是怎么样的呢？会有什么变化吗？
对于被上拉的子查询，abase把子查询的关系并入主from-list中，这样关系的个数会增加，按照多表连接顺序算法就会产生更多的连接路径比如A、B、C三张表的关联就有{A,B}、{A,C}、{B,A}、{B,C}、{C,A}、{C,B}六种连接方式
join与子查询固化或rewrite
join或子查询的优化，属于优化器优化JOIN的范畴。
当用户的QUERY涉及到多个JOIN对象，或者涉及到多个子查询时，优化器可以选择是否改变当前的SQL，产生更多的plan选择更优的执行计划。
postgresql.conf文件中：
#from_collapse_limit = 8
当from列表的对象少于from_collapse_limit时，优化器可以将子查询提升到上层进行JOIN，从而可能选择到更优的执行计划。
#join_collapse_limit = 8 # 1 disables collapsing of explicit
# JOIN clauses 当使用显示的JOIN时（除了full join），例如a join b join c join d，优化器可以重排JOIN的顺序，以产生更多的PLAN选择更优的执行计划。 如果join_collapse_limit=1，则不重排，使用SQL写法提供的顺序。 如果用户要固化JOIN顺序，请使用显示的JOIN，同时将join_collapse_limit设置为1。 如果用户不打算提升子查询，同样的，将from_collapse_limit 设置为1即可。
等价改写
子查询中没有group by子句，也没有聚集函数，则可使用下面的等价转换
val>all(select...) to val>max(select...)
val<all(select...) to val<min(select...)
val>any(select...) to val>min(select...) val<any(select...) to val<max(select...) val>=all(select...) to val>=max(select...) val<=all(select...) to val<=min(select...) val>=any(select...) to val>=min(select...) val<=any(select...) to val<=max(select...)
通常，聚集函数min(),max()的执行效率要比any、all效率高
相关子查询和非相关子查询
相关子查询子查询的执行依赖于外层父查询的一些属性值。子查询因依赖于父查询的参数，当父查询的参数改变时，子查询需要根据新参数值重新执行（查询优化器对相关子查询进行优化有一定意义），如：
select * from t_jcxxzy_tjaj aj where c_ajbm in (select c_ajbm from t_jcxxzy_ajdsr dsr where dsr.c_ajbm = aj.c_ajbm)/* 子查询语句中存在父查询的列 */
非相关子查询子查询的执行，不依赖于外层父查询的任何属性值。这样子查询具有独立性，可独自求解，形成一个子查询计划先于外层的查询求解，如：
select * from t_jcxxzy_tjaj aj where c_ajbm in (select c_ajbm from t_jcxxzy_ajdsr dsr where dsr.c_xzdm = '150622')/* 子查询语句中不存在父查询的属性 */
结束语
1.postgresql子查询的优化思路，子查询不用执行多次
2.优化器可以根据统计信息来选择不同的连接方法和不同的连接顺序
3.子查询中的连接条件，过滤条件分别变成了父查询的连接条件、过滤条件、优化器可以对这些条件进行下推、提高执行效率
4.将子查询优化为表连接后，子查询只需要执行一次、而优化器可以根据统计信息来选择不同的连接方式和连接顺序、子查询的连接条件和过滤条件分别变成父查询的条件。
5.这些查询中all是完全不支持上拉子子链接的，in和exists存在不被优化的可能
6.not exists虽然没有被上拉，但是被优化为只执行一次，相对于not in稍好
7.可使用等价改写的方式优化
8.可根据配置文件，固化子查询，以及表的连接顺序
以上为个人经验，希望能给大家一个参考，也希望大家多多支持。如有错误或未考虑完全的地方，望不吝赐教。
以上是 postgresql关于like%xxx%的优化操作 的全部内容， 来源链接： utcz.com/z/343934.html
