MSQL优化基础(无直方图选择率)
2015-07-01 15:43
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案例一 无直方图 range 内 = 的选择率
选择率=1/NDV×非空率非空率=(表行数-NUM_NULLS)/表行数
col column_name format a10;
col NUM_DISTINCT format 999;
col low_value format a10;
col high_value format a10;
col num_nulls format 999;
col HISTOGRAM format a10;
drop table test;
create table test(n1 number, c1 varchar2(20));
begin
for i in 1..100 loop
if mod(i,9)=0 then
insert into test values(null,null);
else
insert into test(n1,c1) values(i,i);
end if;
end loop;
commit;
end;
/
exec dbms_stats.gather_table_stats(null,'test');
select column_name,num_distinct,low_value,high_value,num_nulls,HISTOGRAM from user_tab_columns where table_name='TEST' and COLUMN_NAME='N1';
COLUMN_NAM NUM_DISTINCT LOW_VALUE HIGH_VALUE NUM_NULLS HISTOGRAM
---------- ------------ ---------- ---------- --------- ----------
N1 89 C102 C202 11 NONE
--以下SQL转换oracle内部结构看最大最小值
SQL> var b1 number;
SQL> exec dbms_stats.convert_raw_value(hextoraw('&1'),:b1);
Enter value for 1: C102
PL/SQL procedure successfully completed.
SQL> print b1;
B1
----------
1
SQL> exec dbms_stats.convert_raw_value(hextoraw('&1'),:b1);
Enter value for 1: C202
PL/SQL procedure successfully completed.
SQL> print b1;
B1
----------
100
COLUMN_NAM NUM_DISTINCT LOW_VALUE HIGH_VALUE NUM_NULLS HISTOGRAM
---------- ------------ ---------- ---------- --------- ----------
N1 89 C102(1) C202(100) 11 NONE
表里边的总数：
SQL> select num_rows from user_tables where table_name='TEST';
NUM_ROWS
----------
100
select * from test where n1=80;
--------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time |
--------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 1 | 5 | 2 (0)| 00:00:01 |
|* 1 | TABLE ACCESS FULL| TEST | 1 | 5 | 2 (0)| 00:00:01 |
--------------------------------------------------------------------------
选择率=1/NDV×非空率
非空率=(表行数-NUM_NULLS)/表行数
选择率= 1/89*(100-11)/100 = 0.01
基数：总行数*选择率=100×0.01=1
结论 基数和Rows都一样案例二 无直方图 range 外 = 的选择率
selectivity(range内[=])/(2High-low-high)=x/(2high-low-绑定直)select * from test where N1=102; -------------------------------------------------------------------------- | Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | -------------------------------------------------------------------------- | 0 | SELECT STATEMENT | | 1 | 5 | 2 (0)| 00:00:01 | |* 1 | TABLE ACCESS FULL| TEST | 1 | 5 | 2 (0)| 00:00:01 | -------------------------------------------------------------------------- selectivity(range内=)/(2High-low-high)=x/(2high-low-绑定直) x=0.01*(2*100-1-102)/(2*100-1-100)=.00979798 基数=.00979798*100=.979798 =1 和rows一样
如果 给定的值 >2high-low 或者 <2low-high 则给一个非常小的值
准备数据：
drop table t1;
create table t1(n1 number, c1 varchar2(20));
begin
for i in 1..2134 loop
if mod(i,9)=0 then
insert into t1 values(null,null);
else
insert into t1(n1,c1) values(trunc(dbms_random.value(1,98),0),dbms_random.string('U',20));
end if;
end loop
commit;
end;
/收集数据 exec dbms_stats.gather_table_stats(null,'t1');
//查看数据分布 SQL> select column_name,num_distinct,low_value,high_value,num_nulls,HISTOGRAM from user_tab_columns where table_name='T1' and COLUMN_NAME='N1'; COLUMN_NAM NUM_DISTINCT LOW_VALUE HIGH_VALUE NUM_NULLS HISTOGRAM ---------- ------------ ---------- ---------- --------- ---------- N1 97 C102(1) C162(97) 237 NONE //总行数 SQL> select num_rows from user_tables where table_name='T1'; NUM_ROWS ---------- 2134
案例三 无直方图 range 内 > 的选择率
Selectivity=((high_value-当前绑定值)/(high_value-low_value))*非空率select * from t1 where n1>60; 非空率=(2134-237)/2134 = .888940956 Selectivity=(97-60)/(97-1)*.888940956 = .34261266 基数：总行数*选择率=2134*.34261266 = 731.135416 -------------------------------------------------------------------------- | Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | -------------------------------------------------------------------------- | 0 | SELECT STATEMENT | | 731 | 15351 | 4 (0)| 00:00:01 | |* 1 | TABLE ACCESS FULL| T1 | 731 | 15351 | 4 (0)| 00:00:01 | --------------------------------------------------------------------------
案例四 无直方图 range 内 < 的选择率
Selectivity=((当前绑定值-low_value)/(high_value-low_value))*非空率select * from t1 where n1<20; 非空率=(2134-237)/2134 = .888940956 Selectivity=(20-1)/(97-1)*.888940956 = .175936231 基数：总行数*选择率=2134*.175936231 = 375.447917 -------------------------------------------------------------------------- | Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | -------------------------------------------------------------------------- | 0 | SELECT STATEMENT | | 375 | 7875 | 15 (0)| 00:00:01 | |* 1 | TABLE ACCESS FULL| T1 | 375 | 7875 | 15 (0)| 00:00:01 | --------------------------------------------------------------------------
案例五 无直方图 >= (in-Range) 选择率
Selectivity=((high_value-当前绑定值)/(high_value-low_value)+1/ndv)*非空率select * from t1 where n1<=20; 非空率=(2134-237)/2134 = .888940956 Selectivity=((20-1)/(97-1)+1/97)*.888940956 = .185100571 基数：总行数*选择率=2134*.185100571 = 395.004619 -------------------------------------------------------------------------- | Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | -------------------------------------------------------------------------- | 0 | SELECT STATEMENT | | 395 | 8295 | 15 (0)| 00:00:01 | |* 1 | TABLE ACCESS FULL| T1 | 395 | 8295 | 15 (0)| 00:00:01 | --------------------------------------------------------------------------
实例六 between (in-Range) 选择率
Selectivity=((valu1-value2)/(high_value-low_value)+2*1/ndv)*非空率select * from t1 where n1 between 20 and 50; 非空率=(2134-237)/2134 = .888940956 Selectivity=((50-20)/(97-1)+2*1/97)*.888940956 = .296122728 基数：总行数*选择率=2134*.296122728 = 631.925902 -------------------------------------------------------------------------- | Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | -------------------------------------------------------------------------- | 0 | SELECT STATEMENT | | 632 | 13272 | 4 (0)| 00:00:01 | |* 1 | TABLE ACCESS FULL| T1 | 632 | 13272 | 4 (0)| 00:00:01 | --------------------------------------------------------------------------
案例七 > (out-of-Range) 选择率
转换成 = (out-of-range) 来处理= (out-of-range) 来处理 的公式
selectivity/(2High-low-high)=x/(2high-low-绑定直)
其中 selectivity=1/div*非空率
explain plan for select * from t1 where n1>150; 这两句的结果是一样的 select * from table(dbms_xplan.display); -------------------------------------------------------------------------- | Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | -------------------------------------------------------------------------- | 0 | SELECT STATEMENT | | 9 | 189 | 4 (0)| 00:00:01 | |* 1 | TABLE ACCESS FULL| T1 | 9 | 189 | 4 (0)| 00:00:01 | -------------------------------------------------------------------------- explain plan for select * from t1 where n1=150; 这两句的结果是一样的 select * from table(dbms_xplan.display); -------------------------------------------------------------------------- | Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | -------------------------------------------------------------------------- | 0 | SELECT STATEMENT | | 9 | 189 | 4 (0)| 00:00:01 | |* 1 | TABLE ACCESS FULL| T1 | 9 | 189 | 4 (0)| 00:00:01 | -------------------------------------------------------------------------- = (out-of-range) 来处理 的公式 selectivity/(2High-low-high)=x/(2high-low-绑定直) 其中 selectivity=1/div*非空率 1/97×(2134-237)/2134/(2*97-1-97)*(2*97-1-150) =.004104861 基数=.004104861*2134= 8.75977337 特殊情况 如果 绑定值 远远大于 97(最大值) 则 rows =1
实例八 < (out-of-Range) 选择率
< (out-of-Range) 选择率 <span style="background-color: rgb(153, 255, 255);">a. 涵盖整个表 , n1< b , b>max_value </span>explain plan for select * from t1 where n1<300; select * from table(dbms_xplan.display); -------------------------------------------------------------------------- | Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | -------------------------------------------------------------------------- | 0 | SELECT STATEMENT | | 1897 | 39837 | 15 (0)| 00:00:01 | |* 1 | TABLE ACCESS FULL| T1 | 1897 | 39837 | 15 (0)| 00:00:01 | -------------------------------------------------------------------------- 返回： all_rows-nuu_rows = 2134-237 = 1897 b. 比 最小值还小 转换成 out-of-range = 的情况 <font style=""><span style=""><span style="background-color: rgb(102, 204, 204);"><span style="color:#99ffff;"> x/（绑定值 -(2low-high))= selectivity/(low-(2low-high))</span> </span></span></font> x=selectivity/(low-(2low-high))*(绑定值 -(2low-high)) =(1/97)*(2134-237)/2134/(1-(2*1-97))*(-1-(2*1-97))=0.00897341600724001 cardinality= 0.00897341600724001*2134=19.1492697594502 explain plan for select * from t1 where n1<-1; select * from table(dbms_xplan.display); -------------------------------------------------------------------------- | Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | -------------------------------------------------------------------------- | 0 | SELECT STATEMENT | | 19 | 399 | 4 (0)| 00:00:01 | |* 1 | TABLE ACCESS FULL| T1 | 19 | 399 | 4 (0)| 00:00:01 | -------------------------------------------------------------------------- <span style="background-color: rgb(102, 204, 204);">c. 比 2low -high 还小 则会给一个非常小的值 </span>select * from t1 where n1<-200; -------------------------------------------------------------------------- | Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | -------------------------------------------------------------------------- | 0 | SELECT STATEMENT | | 1 | 21 | 4 (0)| 00:00:01 | |* 1 | TABLE ACCESS FULL| T1 | 1 | 21 | 4 (0)| 00:00:01 | --------------------------------------------------------------------------
案例九扩张
between 扩展 60 到 200 一边超出了 其实 下边这两句等效 select * from t1 where n1 >=60; select * from t1 where n1 between 60 and 200; NOT A 选择率 1-A 的选择率 COL is NULL num_nulls/num_rows col is not null 1- COL is NULL
补充 10053
alter session set evnet '10053 trace name context forever , level 1' select * from t1 where n1=80; alter session set evnet '10053 trace name context off' 打开10053 搜： Best:: nestloop 的内层循环的a-row 是 外层数乘出来的
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