引用
当系统中的某些表存在高度不均匀的数据分布时，使用直方图能够产生更好的选择性评估，从而产生更加优化的执行计划。
通过下面的例子来感受直方图的作用
基础数据
drop user sure cascade; create user sure identified by oracle; grant resource to sure; create table sure.tab (a number, b number);
插入1万条数据
begin for i in 1..10000 loop insert into sure.tab values (i, i); end loop; commit; end; /
制造 不均匀的情况
update sure.tab set b=5 where b between 6 and 9995; commit;
此时b列的数据分布为
select b, count(*) from sure.tab group by b order by b;
B COUNT(*)
---------- ----------
1 1
2 1
3 1
4 1
5 9991
9996 1
9997 1
9998 1
9999 1
10000 1
【1】在创建索引之前，无论是查询b=1或者是b=5，都只能走 全表扫描。
explain plan for select * from sure.tab where b=1; select * from table(dbms_xplan.display); -------------------------------------------------------------------------- | Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | -------------------------------------------------------------------------- | 0 | SELECT STATEMENT | | 1 | 26 | 6 (0)| 00:00:01 | |* 1 | TABLE ACCESS FULL| TAB | 1 | 26 | 6 (0)| 00:00:01 | --------------------------------------------------------------------------
explain plan for select * from sure.tab where b=5; select * from table(dbms_xplan.display); -------------------------------------------------------------------------- | Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | -------------------------------------------------------------------------- | 0 | SELECT STATEMENT | | 9991 | 253K| 6 (0)| 00:00:01 | |* 1 | TABLE ACCESS FULL| TAB | 9991 | 253K| 6 (0)| 00:00:01 | --------------------------------------------------------------------------
【2】在b列上创建一个索引
create index sure.ix_tab_b on sure.tab(b);
explain plan for select * from sure.tab where b=1; select * from table(dbms_xplan.display); ---------------------------------------------------------------------------------------- | Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | ---------------------------------------------------------------------------------------- | 0 | SELECT STATEMENT | | 1 | 26 | 2 (0)| 00:00:01 | | 1 | TABLE ACCESS BY INDEX ROWID| TAB | 1 | 26 | 2 (0)| 00:00:01 | |* 2 | INDEX RANGE SCAN | IX_TAB_B | 1 | | 1 (0)| 00:00:01 | ---------------------------------------------------------------------------------------- - dynamic sampling used for this statement 18 rows selected.
explain plan for select * from sure.tab where b=5; select * from table(dbms_xplan.display); -------------------------------------------------------------------------- | Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | -------------------------------------------------------------------------- | 0 | SELECT STATEMENT | | 9991 | 253K| 6 (0)| 00:00:01 | |* 1 | TABLE ACCESS FULL| TAB | 9991 | 253K| 6 (0)| 00:00:01 | -------------------------------------------------------------------------- - dynamic sampling used for this statement 17 rows selected
网上的例子说，在有了索引以后，应该都走INDEX RANGE SCAN，但是实际情况（10201）却是，b=5时，依然选择到了正确的路径-- 全表扫描。这是因为没有统计信息，Oracle进行了 动态采样，相当于临时收集了一小份统计信息，所以这时反而挺准的。
【3】收集统计信息，但不收集直方图
analyze table sure.tab compute statistics;
与统计信息相关的视图
select num_rows, blocks, empty_blocks, avg_space, chain_cnt, avg_row_len
from dba_tables where table_name = 'TAB';
NUM_ROWS BLOCKS EMPTY_BLOCKS AVG_SPACE CHAIN_CNT AVG_ROW_LEN
---------- ---------- ------------ ---------- ---------- -----------
10000 20 4 2080 0 10
col low_value format a16
col high_value format a16
col column_name format a16
select column_name, num_distinct, low_value, high_value, density, num_buckets
from dba_tab_columns where table_name = 'TAB';
COLUMN_NAME NUM_DISTINCT LOW_VALUE HIGH_VALUE DENSITY NUM_BUCKETS
---------------- ------------ ---------------- ---------------- ---------- -----------
A 10000 C102 C302 .0001 1
B 10 C102 C302 .1 1
select table_name, column_name, endpoint_number, endpoint_value
from dba_tab_histograms where table_name = 'TAB';
TABLE_NA COLUMN_NAME ENDPOINT_NUMBER ENDPOINT_VALUE
-------- ---------------- --------------- --------------
TAB B 0 1
TAB A 0 1
TAB B 1 10000
TAB A 1 10000
观察执行计划
explain plan for select * from sure.tab where b=1; select * from table(dbms_xplan.display); ---------------------------------------------------------------------------------------- | Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | ---------------------------------------------------------------------------------------- | 0 | SELECT STATEMENT | | 1000 | 6000 | 4 (0)| 00:00:01 | | 1 | TABLE ACCESS BY INDEX ROWID| TAB | 1000 | 6000 | 4 (0)| 00:00:01 | |* 2 | INDEX RANGE SCAN | IX_TAB_B | 1000 | | 2 (0)| 00:00:01 | ----------------------------------------------------------------------------------------
explain plan for select * from sure.tab where b=5; select * from table(dbms_xplan.display); ---------------------------------------------------------------------------------------- | Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | ---------------------------------------------------------------------------------------- | 0 | SELECT STATEMENT | | 1000 | 6000 | 4 (0)| 00:00:01 | | 1 | TABLE ACCESS BY INDEX ROWID| TAB | 1000 | 6000 | 4 (0)| 00:00:01 | |* 2 | INDEX RANGE SCAN | IX_TAB_B | 1000 | | 2 (0)| 00:00:01 | ----------------------------------------------------------------------------------------
有了统计信息， b=5的查询反而跑偏了。
【4】创建tab表b列的柱状图统计信息，使得优化器能够知道该列每个值的具体分布情况。
analyze table sure.tab compute statistics for columns b size 10;
直方图中的ENDPOINT_VALUE表示列值，ENDPOINT_NUMBER表示累积的行数。
select table_name, column_name, endpoint_number, endpoint_value from dba_histograms where table_name = 'TAB'; TABLE_NA COLUMN_NAME ENDPOINT_NUMBER ENDPOINT_VALUE -------- ---------------- --------------- -------------- TAB B 1 1 TAB B 2 2 TAB B 3 3 TAB B 4 4 TAB B 9995 5 TAB B 9996 9996 TAB B 9997 9997 TAB B 9998 9998 TAB B 9999 9999 TAB B 10000 10000 TAB A 0 1 TAB A 1 10000
观察执行计划
explain plan for select * from sure.tab where b=1; select * from table(dbms_xplan.display); ---------------------------------------------------------------------------------------- | Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | ---------------------------------------------------------------------------------------- | 0 | SELECT STATEMENT | | 1 | 6 | 2 (0)| 00:00:01 | | 1 | TABLE ACCESS BY INDEX ROWID| TAB | 1 | 6 | 2 (0)| 00:00:01 | |* 2 | INDEX RANGE SCAN | IX_TAB_B | 1 | | 1 (0)| 00:00:01 | ----------------------------------------------------------------------------------------
explain plan for select * from sure.tab where b=5; select * from table(dbms_xplan.display); -------------------------------------------------------------------------- | Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | -------------------------------------------------------------------------- | 0 | SELECT STATEMENT | | 9991 | 59946 | 6 (0)| 00:00:01 | |* 1 | TABLE ACCESS FULL| TAB | 9991 | 59946 | 6 (0)| 00:00:01 | --------------------------------------------------------------------------
【总结】对于b=5的查询来说，全表扫描比之索引范围扫描更加合理，有直方图，优化器就可以做出正确的判断。（没有统计信息，因为动态采样而选对路径，属于歪打正着）