基本信息
-
基本情况
表共800W数据，从260W的结果集中计算出不同的案件数量(130万)，需要执行20多秒 -
原SQL内容
select count(distinct c_bh_aj) as ajcount
from db_znspgl.t_zlglpt_wt
where d_cjrq between '20160913' and '20170909';
- 表信息和数据量
znspgl=# \d+ db_znspgl.t_zlglpt_wt
Table "db_znspgl.t_zlglpt_wt"
Column | Type | Modifiers | Storage | Stats target | Description
---------+------------------------+-----------+----------+--------------+-------------
c_bh | character(32) | not null | extended | | 编号
c_bh_aj | character(32) | | extended | | 案件编号
n_ajbs | numeric(15,0) | | main | | 案件标识
c_zjgz | character varying(600) | | extended | | 质检规则
c_zjxm | character varying(300) | | extended | | 质检项目
d_cjrq | date | | plain | | 创建日期
Indexes:
"pk_zlglpt_wt" PRIMARY KEY, btree (c_bh)
"i_t_zlglpt_wt_ajbs" btree (n_ajbs)
"i_t_zlglpt_wt_bh_aj" btree (c_bh_aj)
"i_t_zlglpt_wt_cjrq" btree (d_cjrq)
znspgl=# select count(*) from db_znspgl.t_zlglpt_wt
znspgl-# ;
count
---------
8000000
(1 row)
- 数据库版本信息
znspgl=# select version();
version
--------------------------------------------------------------------------------------------
PostgreSQL 9.5.5 (ArteryBase 3.5.3, Thunisoft). on x86_64-pc-linux-gnu, compiled by gcc (GCC) 4.4.7 20120313 (Red Hat 4.4.7-1
7), 64-bit
(1 row)
- 执行计划
znspgl=# explain analyze select count(distinct c_bh_aj) as ajcount from db_znspgl.t_zlglpt_wt where d_cjrq between '20160913' and '20170909';
QUERY PLAN
------------------------------------------------------------------------------------------------------------------------------
Aggregate (cost=313357.40..313357.41 rows=1 width=33) (actual time=23478.562..23478.563 rows=1 loops=1)
-> Bitmap Heap Scan on t_zlglpt_wt (cost=55811.21..306782.09 rows=2630125 width=33) (actual time=366.909..3946.452 rows=2
644330 loops=1)
Recheck Cond: ((d_cjrq >= '2016-09-13'::date) AND (d_cjrq <= '2017-09-09'::date))
Rows Removed by Index Recheck: 2670504
Heap Blocks: exact=105741 lossy=105694
-> Bitmap Index Scan on i_t_zlglpt_wt_cjrq (cost=0.00..55153.68 rows=2630125 width=0) (actual time=341.468..341.468
rows=2644330 loops=1)
Index Cond: ((d_cjrq >= '2016-09-13'::date) AND (d_cjrq <= '2017-09-09'::date))
Planning time: 0.143 ms
Execution time: 23478.624 ms
尝试增加覆盖索引
- 增加索引
create index i_zlglpt_wt_zh01 on db_znspgl.t_zlglpt_wt (d_cjrq,c_bh_aj);
- 再次查看执行计划
znspgl=# explain analyze select count(distinct c_bh_aj) as ajcount from db_znspgl.t_zlglpt_wt where d_cjrq between '20160913' and '20170909';
QUERY PLAN
------------------------------------------------------------------------------------------------------------------------------
--------------------------------
Aggregate (cost=134006.11..134006.12 rows=1 width=33) (actual time=21696.556..21696.557 rows=1 loops=1)
-> Index Only Scan using i_zlglpt_wt_zh01 on t_zlglpt_wt (cost=0.56..127480.16 rows=2610380 width=33) (actual time=0.055.
.2684.807 rows=2644330 loops=1)
Index Cond: ((d_cjrq >= '2016-09-13'::date) AND (d_cjrq <= '2017-09-09'::date))
Heap Fetches: 0
Planning time: 0.318 ms
Execution time: 21696.604 ms
- 思考
1、SQL速度提升很少！
2、时间主要话费在Aggregate上了，时间从2648一下子升级到21696。
3、理论上200W的count(distinct) 不应该花费19秒那么长时间，而且c_bh_aj还是有序的（建立索引了）
伪loose index scan
从网上看到一片帖子《分析MySQL中优化distinct的技巧》，count distinct 慢的原因是因为扫描编号时会扫描到很多重复的项，可以通过loose index scan避免这些重复的扫描（前提distinct项是有序的！），mysql 和 abase虽然不支持原生的loose index scan（oracle支持），但是可以通过改写SQL达到！
- 重新建立索引
drop index db_znspgl.i_zlglpt_wt_zh01;
create index i_zlglpt_wt_zh01 on db_znspgl.t_zlglpt_wt (c_bh_aj,d_cjrq);
- 改写SQL
select count(*) from (
select distinct(c_bh_aj)
from db_znspgl.t_zlglpt_wt
where d_cjrq between '20160913' and '20170909'
) t;
- 查看执行计划
znspgl=# explain analyze select count(*) from (select distinct(c_bh_aj) from db_znspgl.t_zlglpt_wt where d_cjrq between '20160913' and '20170909' ) t;
QUERY PLAN
------------------------------------------------------------------------------------------------------------------------------
Aggregate (cost=347567.23..347567.24 rows=1 width=0) (actual time=6954.845..6954.846 rows=1 loops=1)
-> Unique (cost=0.56..343310.31 rows=340554 width=33) (actual time=0.034..5969.209 rows=1322165 loops=1)
-> Index Only Scan using i_zlglpt_wt_zh01 on t_zlglpt_wt (cost=0.56..336784.36 rows=2610380 width=33) (actual time=
0.031..2840.502 rows=2644330 loops=1)
Index Cond: ((d_cjrq >= '2016-09-13'::date) AND (d_cjrq <= '2017-09-09'::date))
Heap Fetches: 0
Planning time: 0.172 ms
Execution time: 6954.890 ms
(7 rows)
- 通过timing 计算SQL执行时间
znspgl=# \timing on
Timing is on.
znspgl=# select count(*) from (select distinct(c_bh_aj) from db_znspgl.t_zlglpt_wt where d_cjrq between '20160913' and '20170909' ) t;
count
---------
1322165
(1 row)
Time: 1322.715 ms
总结
通过伪loose index scan的SQL处理可以有效提高count(distinct)的执行速度！