PostgreSQL利用递归优化求稀疏列唯一值的方法
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在数据库中经常会碰到一些表的列是稀疏列,只有很少的值,例如性别字段,一般就只有2种不同的值。
但是当我们求这些稀疏列的唯一值时,如果表的数据量很大,速度还是会很慢。
例如:
创建测试表
bill=# create table t_sex (sex char(1), otherinfo text);CREATE TABLEbill=# insert into t_sex select 'm', generate_series(1,10000000)||'this is test';INSERT 0 10000000bill=# insert into t_sex select 'w', generate_series(1,10000000)||'this is test';INSERT 0 10000000
查询:
可以看到下面的查询速度很慢。
bill=# select count(distinct sex) from t_sex;count------- 2(1 row)
Time: 8803.505 ms (00:08.804)bill=# select sex from t_sex t group by sex;sex-----mw(2 rows)
Time: 1026.464 ms (00:01.026)
那么我们对该字段加上索引又是什么情况呢?
速度依然没有明显
bill=# create index idx_sex_1 on t_sex(sex);CREATE INDEXbill=# select count(distinct sex) from t_sex;count------- 2(1 row)
Time: 8502.460 ms (00:08.502)bill=# select sex from t_sex t group by sex;sex-----mw(2 rows)
Time: 572.353 ms
的变化,可以看到执行计划已经使用Index Only Scan了。
bill=# explain select count(distinct sex) from t_sex; QUERY PLAN----------------------------------------------------------------------------------------------Aggregate (cost=371996.44..371996.45 rows=1 width=8) -> Index Only Scan using idx_sex_1 on t_sex (cost=0.44..321996.44 rows=20000000 width=2)(2 rows)
同样的SQL我们看看在Oracle中性能如何?
创建测试表:
SQL> create table t_sex (sex char(1), otherinfo varchar2(100));
Table created.
SQL> insert into t_sex select 'm', rownum||'this is test' from dual connect by level <=10000000;
10000000 rows created.
SQL> commit;
Commit complete.
SQL> insert into t_sex select 'w', rownum||'this is test' from dual connect by level <=10000000;
10000000 rows created.
SQL> commit;
Commit complete.
性能测试:
SQL> set lines 1000 pages 2000SQL> set autotrace onSQL> set timing on
SQL> select count(distinct sex) from t_sex;
COUNT(DISTINCTSEX)------------------ 2
Elapsed: 00:00:01.58
Execution Plan----------------------------------------------------------Plan hash value: 3915432945
----------------------------------------------------------------------------| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time |----------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 1 | 3 | 20132 (1)| 00:00:01 || 1 | SORT GROUP BY | | 1 | 3 | | || 2 | TABLE ACCESS FULL| T_SEX | 14M| 42M| 20132 (1)| 00:00:01 |----------------------------------------------------------------------------
Note----- - dynamic statistics used: dynamic sampling (level=2)
Statistics---------------------------------------------------------- 0 recursive calls 0 db block gets 74074 consistent gets 0 physical reads 0 redo size 552 bytes sent via SQL*Net to client 608 bytes received via SQL*Net from client 2 SQL*Net roundtrips to/from client 1 sorts (memory) 0 sorts (disk) 1 rows processed
SQL> select sex from t_sex t group by sex;
SE--mw
Elapsed: 00:00:01.08
Execution Plan----------------------------------------------------------Plan hash value: 3915432945
----------------------------------------------------------------------------| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time |----------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 14M| 42M| 20558 (3)| 00:00:01 || 1 | SORT GROUP BY | | 14M| 42M| 20558 (3)| 00:00:01 || 2 | TABLE ACCESS FULL| T_SEX | 14M| 42M| 20132 (1)| 00:00:01 |----------------------------------------------------------------------------
Note----- - dynamic statistics used: dynamic sampling (level=2)
Statistics---------------------------------------------------------- 0 recursive calls 0 db block gets 74074 consistent gets 0 physical reads 0 redo size 589 bytes sent via SQL*Net to client 608 bytes received via SQL*Net from client 2 SQL*Net roundtrips to/from client 1 sorts (memory) 0 sorts (disk) 2 rows processed
可以看到Oracle的性能即使不加索引也明显比PostgreSQL中要好。
那么我们在PostgreSQL中是不是没办法继续优化了呢?这种情况我们利用pg中的递归语句结合索引可以大幅提升性能。
SQL改写:
bill=# with recursive tmp as (bill(# (bill(# select min(t.sex) as sex from t_sex t where t.sex is not nullbill(# )bill(# union allbill(# (bill(# select (select min(t.sex) from t_sex t where t.sex > s.sex and t.sex is not null)bill(# from tmp s where s.sex is not nullbill(# )bill(# )bill-# select count(distinct sex) from tmp;count------- 2(1 row)
Time: 2.711 ms
查看执行计划:
bill=# explain with recursive tmp as (bill(# (bill(# select min(t.sex) as sex from t_sex t where t.sex is not nullbill(# )bill(# union allbill(# (bill(# select (select min(t.sex) from t_sex t where t.sex > s.sex and t.sex is not null)bill(# from tmp s where s.sex is not nullbill(# )bill(# )bill-# select count(distinct sex) from tmp; QUERY PLAN----------------------------------------------------------------------------------------------------------------------Aggregate (cost=53.62..53.63 rows=1 width=8) CTE tmp -> Recursive Union (cost=0.46..51.35 rows=101 width=32) -> Result (cost=0.46..0.47 rows=1 width=32) InitPlan 3 (returns $1) -> Limit (cost=0.44..0.46 rows=1 width=2) -> Index Only Scan using idx_sex_1 on t_sex t (cost=0.44..371996.44 rows=20000000 width=2) Index Cond: (sex IS NOT NULL) -> WorkTable Scan on tmp s (cost=0.00..4.89 rows=10 width=32) Filter: (sex IS NOT NULL) -> CTE Scan on tmp (cost=0.00..2.02 rows=101 width=32)(11 rows)
Time: 1.371 ms
可以看到执行时间从原先的8000ms降低到了2ms,提升了几千倍!
甚至对比Oracle,性能也是提升了很多。
但是需要注意的是:这种写法仅仅是针对稀疏列,换成数据分布广泛的字段,显然性能是下降的, 所以使用递归SQL不适合数据分布广泛的字段的group by或者count(distinct)操作。
文章来源:脚本之家
来源地址:https://www.jb51.net/article/204437.htm
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