源码-数据库调优（tuning）初接触

数据库调优对我而言一直是比较高深的内容，今晚看了慕课网的一节视频课程后，有点领悟了。

问题：使用分组子句的情况下，如果要过滤查询结果，而where/having都能使用（即，过滤条件不含分组函数），请问用where好还是having好？

答案：使用where子句可以获得更好的性能，因为where是“先过滤，再分组”，而having是“先分组，再过滤”。

口说无凭，以下源码为证：

scott_pd@ORCL> ed
已写入 file afiedt.buf

1* select deptno, avg(sal) from emp where deptno=10group by deptno
scott_pd@ORCL> /

DEPTNO AVG(SAL)
---------- ----------
10 5000

执行计划
----------------------------------------------------------
Plan hash value: 2854459865

-----------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time |
-----------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 1 | 6 | 3 (0)| 00:00:01 |
| 1 | SORT GROUP BY NOSORT| | 1 | 6 | 3 (0)| 00:00:01 |
|* 2 | TABLE ACCESS FULL | EMP | 9 | 54 | 3 (0)| 00:00:01 |
-----------------------------------------------------------------------------

Predicate Information (identified by operation id):
---------------------------------------------------

2 - filter("DEPTNO"=10)

统计信息
----------------------------------------------------------
0 recursive calls
0 db block gets
7 consistent gets
0 physical reads
0 redo size
605 bytes sent via SQL*Net to client
524 bytes received via SQL*Net from client
2 SQL*Net roundtrips to/from client
0 sorts (memory)
0 sorts (disk)
1 rows processed

scott_pd@ORCL> ed
已写入 file afiedt.buf

1* select deptno, avg(sal) from emp group by deptno having deptno=10
scott_pd@ORCL> /

DEPTNO AVG(SAL)
---------- ----------
10 5000

执行计划
----------------------------------------------------------
Plan hash value: 2138686577

----------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time |
----------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 1 | 6 | 4 (25)| 00:00:01 |
|* 1 | FILTER | | | | | |
| 2 | HASH GROUP BY | | 1 | 6 | 4 (25)| 00:00:01 |
| 3 | TABLE ACCESS FULL| EMP | 38 | 228 | 3 (0)| 00:00:01 |
----------------------------------------------------------------------------

Predicate Information (identified by operation id):
---------------------------------------------------

1 - filter("DEPTNO"=10)

统计信息
----------------------------------------------------------
1 recursive calls
0 db block gets
7 consistent gets
0 physical reads
0 redo size
605 bytes sent via SQL*Net to client
524 bytes received via SQL*Net from client
2 SQL*Net roundtrips to/from client
0 sorts (memory)
0 sorts (disk)
1 rows processed

scott_pd@ORCL> spool
当前正假脱机至 d:/20161010_group_by_tuning.txt
scott_pd@ORCL> spool out


在源码（SQL运行记录）中，我们能看到，使用where子句，共占用了9（3+3+3）个CPU单位，而having子句占用了共11（4+4+3）个CPU单位。
在数据量很庞大的情况下，两者的差距想必也很大。

懂得了这个道理，以后，在写SQL语句的时候，就可以优先使用where了。姑且将本次学习经验称之为数据库调优初接触吧。