Oracle索引扫描算法

SQL> create table t as select * from dba_objects;  

  

Table created.  

  

SQL> create index idx_t on t(object_id);  

  

Index created.  





SQL> BEGIN  

  2    DBMS_STATS.GATHER_TABLE_STATS(ownname          => 'TEST',  

  3                                  tabname          => 'T',  

  4                                  estimate_percent => 100,  

  5                                  method_opt       => 'for all columns size auto',  

  6                                  degree           => DBMS_STATS.AUTO_DEGREE,  

  7                                  cascade          => TRUE);  

  8  END;  

  9  /  



SQL> select leaf_blocks,blevel,clustering_factor from dba_indexes where index_name='IDX_T';  



LEAF_BLOCKS	BLEVEL CLUSTERING_FACTOR

----------- ---------- -----------------

	165	     1		    1705







LEAF_BLOCKS 叶子块 165个



BLEVEL  索引高度-1





集群因子；

CLUSTERING_FACTOR =1705





SQL> select count(distinct dbms_rowid.rowid_block_number(rowid)) from T;



COUNT(DISTINCTDBMS_ROWID.ROWID_BLOCK_NUMBER(ROWID))

---------------------------------------------------

					       1057



存储在1057个块中



SQL> set linesize 200

SQL> select b.num_rows,

       a.num_distinct,

       a.num_nulls,

       utl_raw.cast_to_number(high_value) high_value,

       utl_raw.cast_to_number(low_value) low_value,

       (b.num_rows - a.num_nulls) "NUM_ROWS-NUM_NULLS",

       utl_raw.cast_to_number(high_value) -

       utl_raw.cast_to_number(low_value) "HIGH_VALUE-LOW_VALUE"

  from dba_tab_col_statistics a, dba_tables b

 where a.owner = b.owner

   and a.table_name = b.table_name

   and a.owner = 'TEST'

   and a.table_name = upper('T')

   and a.column_name = 'OBJECT_ID';  2    3    4    5    6    7    8    9   10   11   12   13   14  



  NUM_ROWS NUM_DISTINCT  NUM_NULLS HIGH_VALUE  LOW_VALUE NUM_ROWS-NUM_NULLS HIGH_VALUE-LOW_VALUE

---------- ------------ ---------- ---------- ---------- ------------------ --------------------

     74486	  74486 	 0	77616	       2	      74486		   77614







SQL> explain plan for select owner from t where object_id<1000;



Explained.



SQL> select * from table(dbms_xplan.display());



PLAN_TABLE_OUTPUT

------------------------------------------------------------------------------------------------------------------------------------------------------------



--------------------------------------------

Plan hash value: 1594971208



-------------------------------------------------------------------------------------

| Id  | Operation		    | Name  | Rows  | Bytes | Cost (%CPU)| Time     |

-------------------------------------------------------------------------------------

|   0 | SELECT STATEMENT	    |	    |	958 | 10538 |	 26   (0)| 00:00:01 |

|   1 |  TABLE ACCESS BY INDEX ROWID| T     |	958 | 10538 |	 26   (0)| 00:00:01 |

|*  2 |   INDEX RANGE SCAN	    | IDX_T |	958 |	    |	  4   (0)| 00:00:01 |

-------------------------------------------------------------------------------------



Predicate Information (identified by operation id):



PLAN_TABLE_OUTPUT

------------------------------------------------------------------------------------------------------------------------------------------------------------



--------------------------------------------

---------------------------------------------------



   2 - access("OBJECT_ID"<1000)



14 rows selected.





索引扫描首先要定义到叶子块:





定位到叶子块 要扫描 多少个块？？？  需要高度-1个块



叶子块个数 乘以 选择性



定位到叶子块 要扫描 多少个块？？？



回表和集群因子有关:



选择性(Selectivity) 列唯一键(Distinct_Keys) 与行数(Num_Rows)的比值。





这里有个概念叫有效选择性 ，< 的有效选择性为



(limit-low_value)/(high_value-low_value)





limit 是限制

1000



low_value=2



1000-2 有可能扫到的值的范围





high_value-low_value  表示总共有多少个值:



HIGH_VALUE=77616



LOW_VALUE=2



HIGH_VALUE-LOW_VALUE=77614



LEAF_BLOCKS=165





索引扫描的计算公式如下：

cost =  

 blevel +  

 celiling(leaf_blocks *effective index selectivity) +  

 celiling(clustering_factor * effective table selectivity)





SQL> select 1+ceil(165*(1000-2)/77614)+ceil(1705*(1000-2)/77614) from dual; 



1+CEIL(165*(1000-2)/77614)+CEIL(1705*(1000-2)/77614)

----------------------------------------------------

						  26





为啥effective table selectivity和effective index selectivity一样？



表和索引都包含指定列的数据 两者当然一样