绑定变量窥探和直方图

  一、绑定变量的窥探(peek)
1、Oracle在处理带有绑定变量的SQL时候，只会在硬解析的时候才会“窥探”一下SQL中绑定变量的值，然后会根据窥探到的值来决定整个SQL的执行计划。参数：

_optim_peek_user_binds


2、绑定变量窥探的案例

create table t8(id int ,name varchar2(100));

begin
  for i in 1 .. 1000 loop
    insert into t8 values (i, 'a' || i);
  end loop;
end;


   create index t_idx on t8(id);


   exec dbms_stats.gather_table_stats(user,'T8',cascade=>true);

　select id,count(*) from t8 group by id;

   variable n number;
   exec :n := 1;
   select count(*) from t8  where id = :n;
   select * from table(dbms_xplan.display_cursor);

PLAN_TABLE_OUTPUT
--------------------------------------------------------------------------------
SQL_ID	7zy48bjbwdjff, child number 0
-------------------------------------
select count(*) from t8  where id = :n

Plan hash value: 293504097

---------------------------------------------------------------------------
| Id  | Operation	  | Name  | Rows  | Bytes | Cost (%CPU)| Time	  |
---------------------------------------------------------------------------
|   0 | SELECT STATEMENT  |	  |	  |	  |	1 (100)|	  |
|   1 |  SORT AGGREGATE   |	  |	1 |	4 |	       |	  |

PLAN_TABLE_OUTPUT
--------------------------------------------------------------------------------
|*  2 |   INDEX RANGE SCAN| T_IDX |	1 |	4 |	1   (0)| 00:00:01 |
---------------------------------------------------------------------------

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

   2 - access("ID"=:N)


19 rows selected.
   --再插入值
begin
for i in 1 .. 10000 loop
  insert into t8 values(1,'a'||i);
  end loop;
  commit;
end;
exec dbms_stats.gather_table_stats(user,'T8',cascade=>true);


variable n number;
exec :n := 1;
select count(*) from t8  where id = :n;
SQL> select * from table(dbms_xplan.display_cursor);

PLAN_TABLE_OUTPUT
--------------------------------------------------------------------------------
SQL_ID	7zy48bjbwdjff, child number 0
-------------------------------------
select count(*) from t8  where id = :n

Plan hash value: 293504097

---------------------------------------------------------------------------
| Id  | Operation	  | Name  | Rows  | Bytes | Cost (%CPU)| Time	  |
---------------------------------------------------------------------------
|   0 | SELECT STATEMENT  |	  |	  |	  |	1 (100)|	  |
|   1 |  SORT AGGREGATE   |	  |	1 |	4 |	       |	  |

PLAN_TABLE_OUTPUT
--------------------------------------------------------------------------------
|*  2 |   INDEX RANGE SCAN| T_IDX |	1 |	4 |	1   (0)| 00:00:01 |
---------------------------------------------------------------------------

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

   2 - access("ID"=:N)


19 rows selected.


不管以后数据量是什么情况,只按第一次硬解析的执行计划run SQL


二、直方图
1、作用：当某列数据分布不均衡，为了让CBO能生成最佳的执行计划，我们可能需要对表收集直方图，直方图最大的桶数(Bucket)是254。

2、两种直方图

　（1）频率直方图，当列中Distinct_keys小于254，Oracle就会自动的创建频率直方图，并且桶数(BUCKET)等于Distinct_Keys

   （2）高度平衡直方图，当列中Distinct_keys大于254，Oracle就会自动的创建高度平衡直方图

   （3）生成直方图

BEGIN
  DBMS_STATS.GATHER_TABLE_STATS(ownname=> 'HR',
  tabname          => 'T8',
  estimate_percent => 100,
  method_opt       => 'for all columns size skewonly',
  no_invalidate    => FALSE,
  degree           => 1,
  cascade          => TRUE);
END;


method_opt       => 'for all columns size skewonly',---正式的生产环境中，最好别用allcolumns方式收集直方图，因为all columns 几乎会对所有列都收集直方图信息，但

是有些列并不会出现在where条件中，我们去收集并不会出现在where条件中的列就浪费了资源。



三、绑定变量窥视bind peek与直方图相互作用 
1、收集直方图并 不绑定变量 采用hard coding 硬编码

　　select * from v$version;
　　select id,count(*) from t8 group by id;
BEGIN
  DBMS_STATS.GATHER_TABLE_STATS(ownname=> 'GYJ',
  tabname          => 'T8',
  estimate_percent => 100,
  method_opt       => 'for all columns size skewonly',
  no_invalidate    => FALSE,
  degree           => 1,
  cascade          => TRUE);
END;
/
SQL> select count(*) from t8  where id =1;


Execution Plan
----------------------------------------------------------
Plan hash value: 2157757785

---------------------------------------------------------------------------
| Id  | Operation	   | Name | Rows  | Bytes | Cost (%CPU)| Time	  |
---------------------------------------------------------------------------
|   0 | SELECT STATEMENT   |	  |	1 |	4 |	9   (0)| 00:00:01 |
|   1 |  SORT AGGREGATE    |	  |	1 |	4 |	       |	  |
|*  2 |   TABLE ACCESS FULL| T8   | 10004 | 40016 |	9   (0)| 00:00:01 |
---------------------------------------------------------------------------

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

   2 - filter("ID"=1)


Statistics
----------------------------------------------------------
	  1  recursive calls
	  0  db block gets
	 31  consistent gets
	  0  physical reads
	  0  redo size
	424  bytes sent via SQL*Net to client
	419  bytes received via SQL*Net from client
	  2  SQL*Net roundtrips to/from client
	  0  sorts (memory)
	  0  sorts (disk)
	  1  rows processed

SQL> select count(*) from t8  where id =2;


Execution Plan
----------------------------------------------------------
Plan hash value: 293504097

---------------------------------------------------------------------------
| Id  | Operation	  | Name  | Rows  | Bytes | Cost (%CPU)| Time	  |
---------------------------------------------------------------------------
|   0 | SELECT STATEMENT  |	  |	1 |	4 |	1   (0)| 00:00:01 |
|   1 |  SORT AGGREGATE   |	  |	1 |	4 |	       |	  |
|*  2 |   INDEX RANGE SCAN| T_IDX |	1 |	4 |	1   (0)| 00:00:01 |
---------------------------------------------------------------------------

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

   2 - access("ID"=2)


Statistics
----------------------------------------------------------
	  1  recursive calls
	  0  db block gets
	  2  consistent gets
	  0  physical reads
	  0  redo size
	422  bytes sent via SQL*Net to client
	419  bytes received via SQL*Net from client
	  2  SQL*Net roundtrips to/from client
	  0  sorts (memory)
	  0  sorts (disk)
	  1  rows processed
不适用用绑定变量硬解析依据直方图可以获得很好的基数(cardinality)