课程目标

完成本课程的学习后,您应该能够:

•优化器的作用
•优化器的类型
•优化器的优化步骤
•扫描的基本类型
•表连接的执行计划
•其他运算方式的执行计划
•如何看执行计划顺序
•如何获取执行计划
 
1.优化器概述
  oracle中优化器(optimizer)是SQL分析和执行的优化工具,它负责制订SQL的执行计划,也就是负责保证SQL执行的效率最高。
优化器的类型:
基于规则的优化器(RBO,Rule-Based Optimizer)
基于成本的优化器(CBO,Cost-Based Optimizer)

1.1 RBO

  基于规则的优化器诞生于早期关系型数据库,它的原理是基于一系列规则的优先顺序来分析出执行计划,以判断最优查询路径。

  其中,排名越靠前,Oracle认为效率越高。例如:按索引访问的效率肯定高于全表扫描,多字段复合索引的效率高于单字段索引,等等。通俗地讲,RBO就是不关心被访问对象的实际数据分布情况、索引效率等,仅凭想象去决定应该如何去访问数据库。可见,RBO是一种非常粗放型的优化器。

  RBO的优缺点:

  缺点:
    通过固定的规则来判断执行计划,容易制定出恶性执行计划。
    不通过统计信息来判断,使得误差较大。
  优点:
    RBO的判断有规可循、有律可依,方便用户对优化器的选择进行正确的预测,可以按照我们所期望的方法引导优化器制定执行计划。

1.2 CBO

  基于成本的优化器是关系型数据库所追求的理想型优化器,它的原理是计算了所有查询方法所需要的成本之后,从中选择一个成本最小的查询路径。

  分析----CBO的数据来源

  a.CBO是一个数学模型
  b.需要准确的传入数据
  c,通过精确的数据计算出精确的执行计划
 

CBO在判断最优路径时,需要通过分析相关的统计信息,这些信息包括:
表中的行数
数据块数
每个数据块中的平均行数
行的平均长度
每个列常数的种类
离散程度(直方图)
列值中null的个数
聚簇因子
索引的高度
最大最小值
叶块的数量
运行系统的IO和CPU的使用情况

    select * from user_tables; select * from user_indexes;

  CBO的优缺点:

  缺点:

    a.无法提前预测执行计划。
    b.控制执行计划比较困难。
    c.少数情况存在执行计划选择错误。

  优点:

    a.即使没有理解优化器的工作原理,大多数情况下也能得到最优化的性能。
    b.通过统计信息控制优化。
  
  优化器的优化步骤:

a.通过统计信息对所要执行的sql进行解析,在可能存在的执行计划中进行选择,之后制定出临时的执行计划。
           b.优化器通过对直方图、表的存储结构特征、索引的结构、分区类型、比较运算符等信息进行分析之后计算出各个执行计划的成本。
           c.优化器对各个执行计划的成本进行比较,并从中选择一个成本最低的执行计划。

  优化器的组成

    a.查询转换器
    b.成本估算器
    c.执行计划生成器

查询转换包括:
    视图合并
    子查询解嵌套
    谓词前推
    使用物化视图进行查询重写

drop table test1 purge;
drop table test2 purge;
create table test1 as select * from dba_objects where rownum <=100;
create table test2 as select * from dba_objects where rownum <=1000;
exec dbms_stats.gather_table_stats(user,'test1');
exec dbms_stats.gather_table_stats(user,'test2'); select count(1) from test1 t1,test2 t2 where t1.object_id=t2.object_id;
select count(1) from test1 t1 where t1.object_id in
(select t2.object_id from test2 t2);
select count(1) from test1 t1
where exists (select 1 from test2 t2 where t1.object_id = t2.object_id); --查看UNPARSED QUERY IS出即是查询转换
Alter system flush shared_pool;
alter session set tracefile_identifier = '';
alter session set events '10053 trace name context forever, level 1';
select count(1) from test1 t1,test2 t2 where t1.object_id=t2.object_id;
alter session set events '10053 trace name context off' ; Alter system flush shared_pool;
alter session set tracefile_identifier = 'in';
alter session set events '10053 trace name context forever, level 1';
select count(1) from test1 t1 where t1.object_id in
(select t2.object_id from test2 t2);
alter session set events '10053 trace name context off' ; Alter system flush shared_pool;
alter session set tracefile_identifier = 'exists';
alter session set events '10053 trace name context forever, level 1';
select count(1) from test1 t1
where exists (select 1 from test2 t2 where t1.object_id = t2.object_id);
alter session set events '10053 trace name context off' ; Set autotrace traceonly
select count(1) from test1 t1,test2 t2 where t1.object_id=t2.object_id;
select count(1) from test1 t1 where t1.object_id in
(select t2.object_id from test2 t2);
select count(1) from test1 t1
where exists (select 1 from test2 t2 where t1.object_id = t2.object_id);
Set autotrace off

实验:优化器RBO与CBO

1.2.1CBO为什么不走索引

  为什么有时明显会走索引的情况却不走索引?

  •统计信息陈旧、直方图信息有误。
  •选择其他扫描的代价更低。
Drop table tt purge;
create table tt as select * from dba_objects;
create index ind_status on tt(status);
exec dbms_stats.gather_table_stats(user,'TT',cascade=>true);
set autotrace traceonly
set timing on
set linesize 1000
update tt set status='INVALID' where object_id in (10);
Commit;
select * from tt where status='INVALID';
exec dbms_stats.gather_table_stats(user,'TT',cascade=>true);
select * from tt where status='INVALID';

实验:CBO不走索引

  RULE:基于规则的方式。
  CHOOSE (默认) :如果有统计信息,走CBO;如果没有统计信息且动态采集级别设置为0,走RBO。

  CBO优化器有两种可选的运行模式:
  FIRST_ROWS:以最低的成本返回查询的最先几行。
  ALL_ROWS:以最低的成本返回所有行。

drop table test purge;
create table test as select * from dba_objects;
insert /*+append*/ into test select * from test;
Commit;
insert /*+append*/ into test select * from test;
Commit;
insert /*+append*/ into test select * from test;
Commit;
insert /*+append*/ into test select * from test;
Commit;
insert /*+append*/ into test select * from test;
commit;
select count(*) from test;
create index idx_name on test(owner,object_name) nologging;
exec dbms_stats.gather_table_stats(user,'TEST',cascade=>true); Set timing on
Set autotrace traceonly
Set linesize 1000
SELECT /*+all_rows*/*
FROM (SELECT /*+all_rows*/
INNER_TABLE.*, ROWNUM OUTER_TABLE_ROWNUM
FROM (select /*+all_rows*/
owner, object_name, created
from test
where owner = 'SYS'
order by object_name) INNER_TABLE
WHERE rownum <= 18)
WHERE OUTER_TABLE_ROWNUM > 1; SELECT /*+first_rows(18)*/*
FROM (SELECT /*+first_rows(18)*/
INNER_TABLE.*, ROWNUM OUTER_TABLE_ROWNUM
FROM (select /*+first_rows(18)*/
owner, object_name, created
from test
where owner = 'SYS'
order by object_name) INNER_TABLE
WHERE rownum <= 18)
WHERE OUTER_TABLE_ROWNUM > 1;

优化器模式

 2.执行计划

  执行计划的重要性:当分析一条SQL语句的性能时,通常最先做的事情就是分析它的执行计划,如果连执行计划都看不懂,那SQL调优根本无从谈起。
  执行计划:从表中读出数据并且生成查询语句所要求结果的查询路径。简单点说是SQL语句访问和处理数据的方式。

  执行计划的类型:执行计划的最基本类型实际上就是查询且读取物理数据的方式,该方式被称为扫描。当需要从一个以上的表中读取数据时,必然需要将这些表进行连接,这样的执行类型被称为表连接。

  a.扫描的执行计划
  b.表连接的执行计划
  c.其他运算方式的执行计划
  
2.1扫描的执行计划-全表扫描、rowid扫描

  全表扫描(full   table   scan)扫描对象表中高水位线以下的所有数据块,包括空数据块,同时通过对where 条件中查询条件的过滤来筛选出满足所有条件的数据行的过程。

  谓词access和filter的区别
drop table test purge;
create table test as select * from dba_objects;
exec dbms_stats.gather_table_stats(user,'test');
set autotrace traceonly
select * from test where object_id=100;
create index ind_object_id on test(object_id) nologging;
select * from test where object_id=100;

谓词access和filter的区别

  可以看到Access Predicate和Filter Predicate的重要区别:
Access Predicate在访问数据时做判断,不满足条件的数据不会形成Row Source;
Filter Predicate对已产生的Row Source再做判断,不满足条件的则被丢弃(Throw-Away)。
而降低执行计划中的Throw-Away是我们做SQL调优的一项重要参考指标,因此,一些将Filter Predicate转为Access Predicate的方法也是我们的重要调优手段。

 
2.2扫描的执行计划-索引扫描

  索引扫描类型:

a.索引唯一扫描(index unique scan)
b.索引范围扫描(index range scan)
c.索引降序范围扫描(index range scan descending)
d.索引跳跃式扫描(index skip scan)
e.索引全扫描(index full scan)
f.索引快速全扫描(index fast full scan)
g.位图索引(bitmap index)
drop table test purge;
create table test as select * from dba_objects where object_id is not null;
alter table test modify object_id not null;
create unique index ind_object_id on test(object_id) nologging;
create index ind_object_name on test(object_name) nologging;
exec dbms_stats.gather_table_stats(user,'test',cascade => true);
set autotrace trace exp
--索引唯一扫描:
select * from test where object_id = 100;
--索引范围扫描
select * from test where object_name = 'C_COBJ#';
select * from test where object_id < 100;
--索引降序范围扫描
select * from test where object_id >100 and object_id <110 order by object_id desc;
--索引全扫描
select * from test order by object_id;
--索引快速全扫描
select object_id from test;
--索引跳跃式扫描
drop index ind_object_id;
create index ind_type_id on test(object_type,object_id);
select * from test where object_id=100;
--位图索引
create bitmap index bit_status on test(status);
select count(*) from test where status='VALID';

实验:索引扫描类型

 
2.3表连接的执行计划类型

  表连接类型:

a.嵌套循环连接(nested loops join)
b.排序合并连接(sort merge join)
c.哈希连接(hash join)
d.半连接(semi join)
e.外连接(outer join)
f.索引连接(index join)
g笛卡尔连接(cartestian join)
 
2.3.1表连接的执行计划-嵌套循环连接
 
嵌套循环连接(nested loops join):
访问次数:驱动表返回几条,被驱动表访问多少次。
驱动表是否有顺序:有。
是否要排序:否。
应用场景: 1. 关联中有一个表比较小;
            2. 被关联表的关联字段上有索引;
            3. 索引的键值不应该重复率很高。
通过实验一起来探究nested loops join的原理吧!
set linesize 1000
Set pagesize 100
drop table test1 purge;
drop table test2 purge;
create table test1 as select * from dba_objects where rownum <=100;
create table test2 as select * from dba_objects where rownum <=1000;
exec dbms_stats.gather_table_stats(user,'test1');
exec dbms_stats.gather_table_stats(user,'test2');

1.创建嵌套环连接例子

  basic的情况下,oracle关闭了所有性能数据的收集, 如果要关闭AWR收集
默认为typical的时,除了plan_executetion_statistics和OS Statistics不能收集外,其他的都可以收集
all,所有的都要收集。

alter session set statistics_level=all;
select count(*) from test1 t1, test2 t2
where t1.object_id = t2.object_id;

设置SQL统计信息等级

Starts为该sql执行的次数。
E-Rows为执行计划预计的行数。
A-Rows为实际返回的行数。A-Rows跟E-Rows做比较,就可以确定哪一步执行计划出了问题。
A-Time为每一步实际执行的时间(HH:MM:SS.FF),根据这一行可以知道该sql耗时在了哪个地方。
Buffers为每一步实际执行的逻辑读或一致性读。
Reads为物理读。
OMem、1Mem为执行所需的内存评估值,0Mem为最优执行模式所需内存的评估值,1Mem为one-pass模式所需内存的评估值。
0/1/M 为最优/one-pass/multipass执行的次数。
Used-Mem耗的内存

select /*+leading(t1) use_nl(t2)*/count(*)
from test1 t1, test2 t2
where t1.object_id = t2.object_id;
select * from table(dbms_xplan.display_cursor(null,null,'allstats last')); select /*+leading(t1) use_nl(t2)*/count(*)
from test1 t1, test2 t2
where t1.object_id = t2.object_id
and t1.object_id in (10, 11, 12);
select * from table(dbms_xplan.display_cursor(null,null,'allstats last')); select /*+leading(t1) use_nl(t2)*/count(*)
from test1 t1, test2 t2
where t1.object_id = t2.object_id
and t1.object_id =10;
select * from table(dbms_xplan.display_cursor(null,null,'allstats last')); select /*+leading(t1) use_nl(t2)*/count(*)
from test1 t1, test2 t2
where t1.object_id = t2.object_id
and t1.object_id =99999;

嵌套循环

驱动表的顺序对性能的影响(看Buffers),大表驱动好,还是小表驱动好?
select /*+leading(t1) use_nl(t2)*/count(*)
from test1 t1, test2 t2
where t1.object_id = t2.object_id;
select * from table(dbms_xplan.display_cursor(null,null,'allstats last')); select /*+leading(t2) use_nl(t1)*/count(*)
from test1 t1, test2 t2
where t1.object_id = t2.object_id;
select * from table(dbms_xplan.display_cursor(null,null,'allstats last'));

驱动表的顺序对性能的影响

Drop table  t_xiao purge;
Drop table t_da purge;
create table t_xiao(a1 number(10));
create table t_da(a2 number(10));
begin
for i in 1 .. 10 loop
insert into t_xiao values(i);
end loop;
commit;
end;
/
begin
for i in 1 .. 100000 loop
insert into t_da values(i);
end loop;
commit;
end;
/
exec dbms_stats.gather_table_stats(user,'t_xiao');
exec dbms_stats.gather_table_stats(user,'t_da');
Set autotrace traceonly
select /*+leading(t1,t2) use_nl(t1,t2)*/ * from t_xiao t1,t_da t2 where t1.a1 = t2.a2;
select /*+leading(t2,t1) use_nl(t2,t1)*/ * from t_xiao t1,t_da t2 where t1.a1 = t2.a2;
Set autotrace off
select s.segment_name,s.blocks from user_segments s where s.segment_name in('T_XIAO','T_DA');

如果上述实验不够直观,那我们做下面的实验:

2.3.1表连接的执行计划-哈希连接

哈希连接(hash join):
访问次数:驱动表和被驱动表都只会访问0次或1次。
驱动表是否有顺序:有。
是否要排序:否。
应用场景: 1. 一个大表,一个小表的关联;
             2. 表上没有索引;
               3. 返回结果集比较大。
通过实验一起来探究hash  join的原理吧!

set linesize 1000
Set pagesize 100
drop table test1 purge;
drop table test2 purge;
create table test1 as select * from dba_objects where rownum <=100;
create table test2 as select * from dba_objects where rownum <=1000;
exec dbms_stats.gather_table_stats(user,'test1');
exec dbms_stats.gather_table_stats(user,'test2'); alter session set statistics_level=all; select /*+leading(t1) use_hash(t2)*/count(*)
from test1 t1, test2 t2
where t1.object_id = t2.object_id;
select * from table(dbms_xplan.display_cursor(null,null,'allstats last')); select /*+leading(t1) use_hash (t2)*/count(*)
from test1 t1, test2 t2
where t1.object_id = t2.object_id
and t1.object_id = 99999;
select * from table(dbms_xplan.display_cursor(null,null,'allstats last')); select /*+leading(t1) use_hash (t2)*/count(*)
from test1 t1, test2 t2
where t1.object_id = t2.object_id
and 1=2;
select * from table(dbms_xplan.display_cursor(null,null,'allstats last'));

探究hash join的原理

select /*+leading(t1) use_hash(t2)*/count(*)
from test1 t1, test2 t2
where t1.object_id = t2.object_id;
select * from table(dbms_xplan.display_cursor(null,null,'allstats last')); select /*+leading(t2) use_hash(t1)*/count(*)
from test1 t1, test2 t2
where t1.object_id = t2.object_id;
select * from table(dbms_xplan.display_cursor(null,null,'allstats last'));

驱动表的顺序对性能的影响(看Used-Mem)

Drop table  t_xiao purge;
Drop table t_da purge;
create table t_xiao(a1 number(10));
create table t_da(a2 number(10));
begin
for i in 1 .. 10 loop
insert into t_xiao values(i);
end loop;
commit;
end;
/
begin
for i in 1 .. 100000 loop
insert into t_da values(i);
end loop;
commit;
end;
/
exec dbms_stats.gather_table_stats(user,'t_xiao');
exec dbms_stats.gather_table_stats(user,'t_da');
Set autotrace traceonly
select /*+leading(t1,t2) use_hash(t1,t2)*/ * from t_xiao t1,t_da t2 where t1.a1 = t2.a2;
select /*+leading(t2,t1) use_hash(t2,t1)*/ * from t_xiao t1,t_da t2 where t1.a1 = t2.a2;

再来做一个实验

2.3.2表连接的执行计划-排序合并连接

  排序合并连接(sort merge join):
  访问次数:两张表都只会访问0次或1次。
  驱动表是否有顺序:无。
  是否要排序:是。
  应用场景:当结果集已经排过序。
  通过实验一起来探究 sort merge  join 的原理吧!

set linesize 1000
drop table test1 purge;
drop table test2 purge;
create table test1 as select * from dba_objects where rownum <=100;
create table test2 as select * from dba_objects where rownum <=1000;
exec dbms_stats.gather_table_stats(user,'test1');
exec dbms_stats.gather_table_stats(user,'test2'); alter session set statistics_level=all; select /*+ ordered use_merge(t2)*/count(*)
from test1 t1, test2 t2
where t1.object_id = t2.object_id;
select * from table(dbms_xplan.display_cursor(null,null,'allstats last')); select /*+ ordered use_merge(t2)*/count(*)
from test1 t1, test2 t2
where t1.object_id = t2.object_id
and t1.object_id = 99999;
select * from table(dbms_xplan.display_cursor(null,null,'allstats last')); select /*+ ordered use_merge(t2)*/count(*)
from test1 t1, test2 t2
where t1.object_id = t2.object_id
and 1=2;
select * from table(dbms_xplan.display_cursor(null,null,'allstats last'));

探究sort merge join的原理

Drop table  t_xiao purge;
Drop table t_da purge;
create table t_xiao(a1 number(10));
create table t_da(a2 number(10));
begin
for i in 1 .. 10 loop
insert into t_xiao values(i);
end loop;
commit;
end;
/
begin
for i in 1 .. 100000 loop
insert into t_da values(i);
end loop;
commit;
end;
/
exec dbms_stats.gather_table_stats(user,'t_xiao');
exec dbms_stats.gather_table_stats(user,'t_da');
Set autotrace traceonly
select /*+ leading(t1) use_merge(t2)*/ * from t_xiao t1,t_da t2 where t1.a1 = t2.a2;
select /*+ leading(t2) use_merge(t1)*/ * from t_xiao t1,t_da t2 where t1.a1 = t2.a2;

驱动表顺序

2.3.3表连接的执行计划-笛卡尔连接

  笛卡尔连接(cartestian join):
  在开发要消除它,它可能由下列几种情况引起:
  SQL逻辑有问题,表之间没有关联关系;
  表统计信息没有收集,产生错误的执行计划;
  SQL过于复杂,CBO给出错误的执行计划。

drop table test1 purge;
drop table test2 purge;
create table test1 as select * from dba_objects where rownum <=8000;
create table test2 as select * from dba_objects where rownum <=8000;
exec dbms_stats.gather_table_stats(user,'test1');
exec dbms_stats.gather_table_stats(user,'test2');
Set autotrace traceonly
Select count(*) from test1,test2;

笛卡尔连接

2.3.4表连接的执行计划-半连接

  半连接(semi join):
  由各种运算所构成的子查询与主查询之间的连接。尽管子查询的种类众多,但其都是一种为实现子查询与主查询之间连接的表连接。
  in 和 exists原理及效率
  not in  和 not  exists原理及效率

drop table test1 purge;
drop table test2 purge;
create table test1 as select * from dba_objects where rownum <=1000;
create table test2 as select * from dba_objects;
exec dbms_stats.gather_table_stats(user,'test1');
exec dbms_stats.gather_table_stats(user,'test2');
Set autotrace traceonly
--in 和exist原理和效率
select count(*) from test1 where object_id in(select object_id from test2);
select count(*) from test1 t1 where exists
(select 1 from test2 t2 where t1.object_id=t2.object_id); --not in 和not exist原理和效率
select count(*) from test1 where object_id not in(select object_id from test2);
select count(*) from test1 t1 where not exists
(select 1 from test2 t2 where t1.object_id=t2.object_id); --再看not in 和not exist的效率
Set autotrace off
drop table test1 purge;
drop table test2 purge;
create table test1 as select * from dba_objects where rownum <=5;
create table test2 as select * from dba_objects;
Insert into test2 select * from dba_objects;
Insert into test2 select * from test2;
Insert into test2 select * from test2;
Commit;
exec dbms_stats.gather_table_stats(user,'test1');
exec dbms_stats.gather_table_stats(user,'test2');
Set autotrace traceonly
select count(*) from test1 where object_id not in(select object_id from test2);
select count(*) from test1 t1 where not exists
(select 1 from test2 t2 where t1.object_id=t2.object_id);

半连接

--值得注意的是:如果子查询的关联字段中存在null,not in 查出的结果是不正确的。
set autotrace off
Update test1 set object_id = null where rownum <10;
Commit;
select count(*) from test2 t2 where t2.object_id not in(select t1.object_id from test1 t1);
select count(*) from test2 t2 where not exists
(select 1 from test1 t1 where t1.object_id=t2.object_id); --not in 和 not exists等价
Oracle 10g下
select count(*) from test2 where object_id not in(select t1.object_id from test1 t1 where
T1.object_id is not null) and object_id is not null;
select count(*) from test2 t1 where not exists
(select 1 from test1 t2 where t1.object_id=t2.object_id);
Oracle 11g下在没有null的情况下就相同了
drop table test1 purge;
drop table test2 purge;
create table test1 as select * from dba_objects where rownum <=1000;
create table test2 as select * from dba_objects;
exec dbms_stats.gather_table_stats(user,'test1');
exec dbms_stats.gather_table_stats(user,'test2');
select count(*) from test2 t2 where t2.object_id not in(select t1.object_id from test1 t1);
select count(*) from test2 t2 where not exists
(select 1 from test1 t1 where t1.object_id=t2.object_id);
Set autotrace traceonly
select count(*) from test2 t2 where t2.object_id not in(select t1.object_id from test1 t1);
select count(*) from test2 t2 where not exists
(select 1 from test1 t1 where t1.object_id=t2.object_id);
Set autotrace off
Update test1 set object_id = null where rownum <10;
Commit;
select count(*) from test2 t2 where t2.object_id not in(select t1.object_id from test1 t1);
select count(*) from test2 t2 where not exists
(select 1 from test1 t1 where t1.object_id=t2.object_id);

半连接-查询字段为NULL

2.3.5表连接的执行计划-外连接

  外连接(outer join):
  是指以将要连接的两个表中的某个表为基准,即使连接时另一个对象表中没有找到对应的行,也同样要返回基准表中所有行的一种连接方式。

drop table test1 purge;
drop table test2 purge;
create table test1 as select * from dba_objects where rownum <=1000;
create table test2 as select * from dba_objects;
exec dbms_stats.gather_table_stats(user,'test1');
exec dbms_stats.gather_table_stats(user,'test2');
Set autotrace traceonly
select * from test1 t1,test2 t2 where t1.object_id(+) = t2.object_id;

外连接

2.3.6表连接的执行计划-索引连接

  索引连接(index join):
  在某个查询语句中所使用到的某个列存在一个以上的索引时,按照哈希连接方式将这些索引连接起来的方法。也就是说不是通过读取索引再读取表的方式,而是只通过索引连接来实现数据查询的方法。

drop table test1 purge;
drop table test2 purge;
create table test1 as select * from dba_objects;
create table test2 as select * from dba_objects where rownum <=1000;
Create index ind_t1_object_id on test1(object_id) nologging;
Create index ind_t1_object_type on test1(object_type) nologging;
Create index ind_t2_object_id on test2(object_id) nologging;
exec dbms_stats.gather_table_stats(user,'test1',cascade=>true);
exec dbms_stats.gather_table_stats(user,'test2',cascade=>true);
Set autotrace traceonly
select /*+index_join(t1)*/ object_id,object_type from test1 t1
where object_id=100 and object_type='TABLE'; select t1.object_id from test1 t1,test2 t2
where t1.object_id = t2.object_id;

索引连接

2.3.7各类连接的限制场景
   哈希连接不支持不等值<>,不支持> 、<的连接方式,也不支持like 的连接方式。
   排序合并连接不支持不等值<>,也不支持like 的连接方式,但支持> 的连接的条件。
   嵌套循环无限制。

drop table test1 purge;
drop table test2 purge;
create table test1 as select * from dba_objects where rownum<100;
create table test2 as select * from dba_objects where rownum<1000;
exec dbms_stats.gather_table_stats(user,'test1');
exec dbms_stats.gather_table_stats(user,'test2');
Set autotrace traceonly
--<>实验
select /*+leading(t1) use_hash(t2)*/count(*)
from test1 t1, test2 t2
where t1.object_id <> t2.object_id;
--like实验
select /*+leading(t1) use_hash(t2)*/count(*)
from test1 t1, test2 t2
where t1.object_type like t2.object_type;
--这种like是可以的
select /*+leading(t1) use_hash(t2)*/count(*)
from test1 t1, test2 t2
where t1.object_id = t2.object_id
and t1.object_type like '%TABLE%';
-- >实验
select /*+leading(t1) use_hash(t2)*/count(*)
from test1 t1, test2 t2
where t1.object_id > t2.object_id ;
--这种>是可以的
select /*+leading(t1) use_hash(t2)*/count(*)
from test1 t1, test2 t2
where t1.object_id = t2.object_id
and t1.object_id >100;

哈希连接限制场景实验

 select /*+leading(t1) use_merge(t2)*/count(*)
from test1 t1, test2 t2
where t1.object_id <> t2.object_id ; select /*+leading(t1) use_merge(t2)*/count(*)
from test1 t1, test2 t2
where t1.object_id like t2.object_id ; select /*+leading(t1) use_merge(t2)*/count(*)
from test1 t1, test2 t2
where t1.object_id > t2.object_id ;

排序合并连接限制场景实验

2.3.8其他运算方式的执行计划- IN-list 迭代

  IN-list 迭代执行计划(INLIST ITERATOR):
  在inlist interator 之下的查询过程被反复执行了多次,执行次数有in 中的值个数决定。

drop table test1 purge;
create table test1 as select * from dba_objects;
Create index ind_t1_object_id on test1(object_id) nologging;
exec dbms_stats.gather_table_stats(user,'test1',cascade=>true);
Set autotrace traceonly
Select * from test1 where object_id in(7,8,9,10);
Select * from test1 where object_id =7 or object_id =8 or object_id =9 or object_id =10;

IN-list

2.3.9其他运算方式的执行计划-连锁

  连锁执行计划(CONCATENATION):
  是指在使用or连接由不同列所构成的查询条件的情况下,按照各个查询条件将整个查询分成多个独立的查询,为各个独立查询制定最优查询路径后再将其连接起来的执行计划。

drop table test1 purge;
create table test1 as select * from dba_objects;
Create index ind_t1_object_id on test1(object_id) nologging;
Create index ind_t1_object_type on test1(object_type) nologging;
exec dbms_stats.gather_table_stats(user,'test1',cascade=>true);
Set autotrace traceonly
Select * from test1 where object_id=100 or object_type='TABLE';

连锁

2.4.0其他运算方式的执行计划-排序操作

  排序操作执行计划:
  sort(unique) 是指把输出结果变为唯一集合的过程,查询中用到了distinct 。
  sort(aggregate)  是指在没有group by 的前提下,使用统计函数对全部数据进行运算时所显示的执行计划。在使用sum、count、min、max、avg等统计函数时并不执行我们所熟悉的一般排序。
  sort(group by)  该操作是将数据行向不同分组中聚集的操作,即依据查询语句中所使用的group by 而进行的相关操作,为了进行分组就只能进行排序,因此所需分组的数据量越大则代价就越高。
  sort(order by)  在查询语句中使用了order by。

drop table test1 purge;
create table test1 as select * from dba_objects;
exec dbms_stats.gather_table_stats(user,'test1');
Set autotrace traceonly
--sort(unique)
select distinct object_id from test1 order by object_id; --sort(aggregate)
select sum(object_id) from test1; --sort(group by)
select object_type,count(*) from test1 group by object_type; --sort(order by)
select * from test1 order by object_id;

排序操作

2.4.1其他运算方式的执行计划-集合操作

  集合操作执行计划:
  SQL是处理集合的语言,包含读取集合、进行集合运算、输出集合。
  并集(union 、union  all)
  交集(intersect)
  差集(minus)

drop table test1 purge;
drop table test2 purge;
create table test1 as select * from dba_objects;
create table test2 as select * from dba_objects where rownum <=1000;
exec dbms_stats.gather_table_stats(user,'test1');
exec dbms_stats.gather_table_stats(user,'test2');
Set autotrace traceonly select * from test1
union
select * from test2; select * from test1
union all
select * from test2; select * from test1
intersect
select * from test2; select * from test1
minus
select * from test2;

集合操作

2.4.2其他运算方式的执行计划-COUNT(STOPKEY)

  COUNT(STOPKEY)执行计划:
  该计划指在查询语句的查询条件中使用了rownum时所显示出来的执行计划。

drop table test1 purge;
create table test1 as select * from dba_objects;
exec dbms_stats.gather_table_stats(user,'test1');
Set autotrace traceonly
select * from test1 where rownum <10;

Count

2.4.3如何获取执行计划

  autotrace(最常用的工具)    autotrace traceonly explain 没有执行,其他都执行。
  Explain plan  for      引发硬解析,但并不会执行。
  DBMS_XPLAN.DISPLAY_CURSOR      在Shared pool中取执行计划。
  SQL_TRACE和10046(神器)

drop table test purge;
create table test as select * from dba_objects;
exec dbms_stats.gather_table_stats(user,'test1'); Autotrace
Set timing on
Set autotrace traceonly
Select * from test;
Set autotrace off 分析AWR时,可以根据SQL_ID找到真实的执行计划,绑定变量,统计信息
select hash_value, child_number, sql_text from v$sql s
where s.SQL_ID = '866n2xzvtyndu';
select * from table(dbms_xplan.display_cursor(hash_value, child_number, 'advanced')); 如果想要获得更多的信息
alter session set statistics_level=all;
Select count(*) from test;
select * from table(dbms_xplan.display_cursor(null,null,'allstats last')); explain plan for
explain plan for select * from test;
select * from table(dbms_xplan.display);

示例

 

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