11 Indexes

时间:2023-03-09 08:20:12
11 Indexes

本章提要
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索引会影响 DML 与 select 操作, 要找到平衡点
最好从一开始就创建好索引
索引概述
B*索引
其他一些索引
索引使用中的一些基本问题
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索引概述
    oracle提供的索引种类:
        B*树索引, 我们所说的"传统"索引, 并不是二叉树, 这里的"B" 代表平衡, B*树索引的子类型:
            索引组织表
            B*树聚簇索引
            降序索引, 允许索引结构中按"从大到小"顺序排序
            反向键索引, 键中的字节会"反转"
    位图索引:
        在B*树中, 通常索引条目和行之间存在一种一对一的关系, 一个索引条目就指向一行, 而对于位图索引, 一个索引条目则使用一个位图
        同时指向多行, 位图索引适用于高度重复而且通常只读的数据, 在一个OLTP数据库中, 由于存在并发性相关的问题, 所以不能考虑使用
    位图索引:
        位图联结索引, 在多表联结时, 可能被使用, 但是, 同样, OLTP中不能使用.
    基于函数的索引:
        这些就是 B* 树索引或位图索引, 它将一个函数计算得到的结果存储在行的列中, 而不是存储列数据本身, 可以把基于函数的索引看做
        一个虚拟列(或派生列)上的索引, 换句话说, 这个列并不物理地存储在表中, 基于函数的索引可以用于加快形如 select * from t
        where function(database_column) = some_value这样的查询, 因为值 function(database_column)已经提前计算并存储在索引中.
    应用域索引:
B* 树索引
    我们所说的"传统"索引, 数据库最常用的一类索引结构, 其实现与二叉查找树很相似,    如图:
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" alt="" />
        B*树索引不存在非唯一条目, (索引也是一个存储结构, 在这个存储结构中不存在两行完全相同的数据), 在一个非唯一的索引中, oracle会
        把rowid作为一个额外的列追加到键上, 使得键唯一, 例如 create index i on t(x,y)索引, 从概念上讲, 它就是create unique index i
        on t(x, y, rowid). 在一个唯一索引中, 根据你定义的唯一性, oracle 不会再向索引键增加rowid.
        B*树特点之一是, 所有叶子块都应该在树的同一个层上, 这一层也称为索引的高度, 这说明所有索引的根块到叶子块的遍历都会访问同样
        数目的块, 大多数B*树索引的高度都是2或3, 即使索引中有数百万行记录也是如此, 这说明, 一般来讲, 在索引中找到一个键值只需要执行
        2或3次I/O. (blevel统计的是分支数, 即比高度少1)
        select index_name, blevel, num_rows from user_indexes where table_name = 'BIG_TABLE';
        B*树是一个绝佳的通用索引机制, 无论是大表还是小表都适用, 随着底层表大小的增长, 获取数据的性能只稍有恶化(或根本不恶化)
    索引键压缩(个人感觉用处不大)
        索引键条目分解为两部分, 前缀和后缀, 前缀有重复, 后缀没有重复(唯一区域)
        实验,

create table t
as
select * from all_objects
where rownum <= 50000; create index t_idx on
t(owner,object_type,object_name); analyze index t_idx validate structure; create table idx_stats
as
select 'noncompressed' what, a.*
from index_stats a; drop index t_idx;
create index t_idx on
t(owner,object_type,object_name)
compress &1; -- 分别用1,2,3来代替
analyze index t_idx validate structure;
insert into idx_stats
select 'compress &1', a.* -- 分别用1,2,3来代替
from index_stats a; select what, height, lf_blks, br_blks,
btree_space, opt_cmpr_count, opt_cmpr_pctsave
from idx_stats
/

11-1

对现在来说, 这种压缩并不是免费的, 现在压缩索引比原来更复杂了, oracle会花更多时间来处理这个索引结构中的数据, 不光在修改期间
        维护索引更耗时, 查询期间搜索索引也更花时间.    
    反向键索引(还比较重要, 分情况使用)
        反向键索引只是将索引键中各个列的字节反转, 如果考虑 90101, 90102, 和90103, 如果使用 oracle dump函数查看其内部表示, 可以看到
        这几个数表示如下:
        select 90101, dump(90101,16) from dual
         union all
        select 90102, dump(90102,16) from dual
         union all
         select 90103, dump(90103,16) from dual
         /
        结果是:
         90101 DUMP(90101,16)       
        ---------- ---------------------
         90101 Typ=2 Len=4: c3,a,2,2
         90102 Typ=2 Len=4: c3,a,2,3
         90103 Typ=2 Len=4: c3,a,2,4

3 rows selected.    
        每个数的长度都是4字节, 它们只是最后一个字节有所不同, 这些书最后可能在一个索引结构中向右一次放置(放置的比较近), 不过, 如果
        反转这些数的字节, oracle就会插入以下值:
        90101 reversed = 2,2,a,c3
        90102 reversed = 3,2,a,c3
        90103 reversed = 4,2,a,c3
        这些数之间最后可能相距很远, 这样访问同一个块(最右边的块)的RAC实例个数就能减少, 反向键索引的缺点之一是, 能用常规索引的地方
        不一定能用反向键索引, 例如: 在回答谓词时, x 上的反向键索引就没用: where x > 5
        存储之前, 数据部是按 x 在索引中派讯, 而是按 reverse(x)排序, 因此, 对 x>5的区间扫描不能使用这个索引. 另外有些谓词有可以,比如
        在(x,y)上有一个串联索引, where x = 5 就可以, 这是因为, 首先将x的字节翻转, 然后再将 y 的字节翻转, oracle并不是将(x||y)的字节
        反转, 而是会存储(reverse(x) || reverse(y)), 这说明, x = 5 的所有值会存储在一起, 所以 oracle 可以对这个索引执行区间扫描来
        找到所有这些数据.
        下面假设一个用序列填充的表上有一个代理主键,而且不需要在这个(主键)索引上使用区间扫描, 也就是说, 不需要 max(primary_key),
        where primary_key < 100 等查询(如果有这个查询条件, 那么就不能使用反向索引, 因为反向索引在这种情况下不能被使用), 在有大量插入
        操作的情况下, 即使只有一个实例, 也要使用反向索引. 下面测试:

create table t tablespace assm
as
select 0 id, a.*
from all_objects a
where 1=0; alter table t
add constraint t_pk
primary key (id)
using index (create index t_pk on t(id) &indexType tablespace assm); create sequence s cache 1000; -- 如果把 &indexType 替换为reverse, 就会创建一个反向索引, 如果不加&indexType
-- 即替换为"什么也没有", 则表示使用一个"常规"索引 -- 开始测试
create or replace procedure do_sql
as
begin
for x in ( select rownum r, all_objects.* from all_objects )
loop
insert into t
( id, OWNER, OBJECT_NAME, SUBOBJECT_NAME,
OBJECT_ID, DATA_OBJECT_ID, OBJECT_TYPE, CREATED,
LAST_DDL_TIME, TIMESTAMP, STATUS, TEMPORARY,
GENERATED, SECONDARY )
values
( s.nextval, x.OWNER, x.OBJECT_NAME, x.SUBOBJECT_NAME,
x.OBJECT_ID, x.DATA_OBJECT_ID, x.OBJECT_TYPE, x.CREATED,
x.LAST_DDL_TIME, x.TIMESTAMP, x.STATUS, x.TEMPORARY,
x.GENERATED, x.SECONDARY );
if ( mod(x.r,100) = 0 )
then
commit;
end if;
end loop;
commit;
end;
/ -- c 代码, 目前无法测试
exec sql declare c cursor for select * from all_objects;
exec sql whenever notfound do break;
for(;;)
{
exec sql
fetch c into :owner:owner_i,
:object_name:object_name_i, :subobject_name:subobject_name_i,
:object_id:object_id_i, :data_object_id:data_object_id_i,
:object_type:object_type_i, :created:created_i,
:last_ddl_time:last_ddl_time_i, :timestamp:timestamp_i,
:status:status_i, :temporary:temporary_i,
:generated:generated_i, :secondary:secondary_i;
exec sql
insert into t
( id, OWNER, OBJECT_NAME, SUBOBJECT_NAME,
OBJECT_ID, DATA_OBJECT_ID, OBJECT_TYPE, CREATED,
LAST_DDL_TIME, TIMESTAMP, STATUS, TEMPORARY,
GENERATED, SECONDARY )
values
( s.nextval, :owner:owner_i, :object_name:object_name_i,
:subobject_name:subobject_name_i, :object_id:object_id_i,
:data_object_id:data_object_id_i, :object_type:object_type_i,
:created:created_i, :last_ddl_time:last_ddl_time_i,
:timestamp:timestamp_i, :status:status_i,
:temporary:temporary_i, :generated:generated_i,
:secondary:secondary_i );
if ( (++cnt%100) == 0 )
{
exec sql commit;
}
}
exec sql whenever notfound continue;
exec sql commit;
exec sql close c;

11-2

测试的结果是(书上看的,目前无法测试)使用反向索引高效的多
    降序索引(个人感觉, 作用一般)
        测试:

create table t
as
select *
from all_objects
/ create index t_idx
on t(owner,object_type,object_name); begin
dbms_stats.gather_table_stats
( user, 'T', method_opt=>'for all indexed columns' );
end;
/ set autotrace traceonly explain
select owner, object_type
from t
where owner between 'T' and 'Z'
and object_type is not null
order by owner DESC, object_type DESC; -- oracle 会往前读索引
-- 这个explain 计划中最后没有排序步骤, 数据已经是有序的, 不过, 如果你有一组列,
-- 其中一些列按升序排序(ASC), 另外一些列按降序排列(DESC), 此时降序索引就能用.例如: select owner, object_type
from t
where owner between 'T' and 'Z'
and object_type is not null
order by owner DESC, object_type ASC; -- oracle 不能再使用(owner, object_type, object_name)上索引对数据排序, 它可以往前
-- 读得到按 owner desc 排序的数据, 但是现在还需要"向后读"来得到按object_type升序
-- ASC的数据, 此时oracle的实际做法是, 它会把所有行收集起来,然后排序, 但是如果有
-- DESC索引, 则有:
create index desc_t_idx on t(owner desc,object_type asc); select owner, object_type
from t
where owner between 'T' and 'Z'
and object_type is not null
order by owner DESC, object_type ASC;

11-3

查询中最好别少了 orader by, 即使你的查询计划中包含一个索引, 但这并不表示数据会以"某种顺序"返回, 要想从数据库以某种有序的顺序
        获取数据, 唯一的办法就是在查询中包括一个 order by 子句, order by 是无可替代的.
    什么情况下应该使用 B* 树索引
        仅当要通过索引访问表中很少的一部分(只占很小百分比, 2%), 才能使用 B* 树在裂伤建立索引
        如果要处理表中的多行, 而且可以使用索引而不用表, 就可以使用一个B*树索引.(一个查询, 索引包含了足够的信息来回答查询, 我们根本
            不用去访问表) select count(*) from t 就是只读索引就可以了, 不需要访问表了.
        重要的是, 要了解这两个概念间的区别, 如果必须完成 table access by index rowid, 就必须确保只访问表中很少的一部分块(很小百分比),
        如果我们访问的行太多(所占百分比过大, 20%以上), 那么与全表扫描相比, 通过B*树索引来访问这些数据通常要花更长的时间.
        一般来讲, B*树索引会放在频繁使用查询谓词的裂伤, 而且我们希望从表中只返回少量的数据, 在一个thin表(也就是说很少的列, 或列很小),
        这个百分比相当小(2%~3%), 如果在一个fat表(也就是说, 有很多列, 或列很宽)百分比可能会升到表的20%~25%, 索引按索引建的顺序存储,
        索引会按键的有序顺序访问, 索引指向的块则随机的存储在堆中, 因此,我们通过索引访问表时, 会执行大量分散, 分散是指: 索引会告诉我们
        读取块1, 然后是块1000, 块205, 块321, 等等, 它不会要求我们按一种连续的方式读取块1, 块2, 块3 等等.
        下面来看一个例子:
        假设我们索引读取一个thin表, 而且要读取表中20%的行, 若这个表中有100 000行, 其中20%就是20000行, 如果行大小为80字节,
        在一个块大小为8kb的数据库中, 每个块上大约100行, 这说明, 大约是20000个 table access by rowid 操作, 为此要处理20000个表快来执行
        查询, 不过, 整个表才只有1000个块, 在这种情况下 全表扫描就比索引高效的多.
        1) 物理组织
            数据在磁盘上如何物理地组织, 对上述计算会有显著影响, 因为这会大大影响索引访问的开销, 假设一个表, 其中的行主键由一个序列来
            填充, 向这个表增加数据时, 序列号相邻的行一般存储位置也会彼此相邻.表会很自然的按主键顺序聚簇(因为数据或多或少就是以这种
            顺序增加的), 当然, 它不一定严格按照聚簇(要想做到这一点, 必须使用一个IOT), 一般来讲, 主键值彼此接近的行的物理位置也会靠在
            一起, 如果发生下面查询: select * from t where primary_key between :x and :y;
            你想要的行通常就位于同样的块上, 在这种情况下, 即使要访问大量的行(占很大的百分比), 索引区间扫描可能也很有用, 原因在于:
            我们需要读取和重新读取的数据库块可能会被缓存, 因为数据共同放置在同一个位置, 另一方面, 如果行并非共同存储在一个位置上, 使用
            这个索引对性能来讲可能就是灾难性的. 下面演示:

create table colocated ( x int, y varchar2(80) );

begin
for i in 1 .. 100000
loop
insert into colocated(x,y)
values (i, rpad(dbms_random.random,75,'*') );
end loop;
end;
/ alter table colocated
add constraint colocated_pk
primary key(x); begin
dbms_stats.gather_table_stats( user, 'COLOCATED');
end;
/ -- 这个表正好满足前面的描述, 即在块大小为8kb的一个数据库中, 每块大约 100 行,
-- 在这个表中, x = 1,2,3 的行极有可能在同一个块上, 仍取这个表, 但有意的使他
-- "无组织", 在 colocated表中, 我们创建了一个y列, 它带有一个前导随机数, 现在
-- 利用这一点使得数据无组织, 即不再按主键排序: create table disorganized
as
select x,y
from colocated
order by y; -- 这时, 数据已经无序的存储在磁盘上了 alter table disorganized
add constraint disorganized_pk
primary key (x); begin
dbms_stats.gather_table_stats( user, 'DISORGANIZED');
end;
/
-- 比较这两个表,虽然含有相同的结果集, 但是在性能上却天壤之别

11-4

2) 聚簇因子
            我们查看 user_indexes视图中的 clustering_factor 列, 这个列有以下含义:
            根据索引的值指示表中行的有序程度
                如果这个值与块数接近, 则说明表相当有序, 得到了很好的组织, 在这种情况下, 同一个叶子块中的索引条目可能指向同一个数据
                    块上的行.
                如果这个值与行数接近, 表的次序可能就是非常随机的, 在这种情况下, 同一个叶子块上的索引条目不太可能指向同一个数据块上的行.
            可以把聚簇因子看做是通过索引读取整个表时对表执行的逻辑I/O次数. 查看索引时, 会得到以下结果:
            select a.index_name,
            b.num_rows,
            b.blocks,
            a.clustering_factor
            from user_indexes a, user_tables b
            where index_name in ('COLOCATED_PK', 'DISORGANIZED_PK' )
            and a.table_name = b.table_name
            INDEX_NAME NUM_ROWS BLOCKS CLUSTERING_FACTOR
            ------------------------------ ---------- ---------- -----------------
            COLOCATED_PK 100000 1252 1190
            DISORGANIZED_PK 100000 1219 99930
            所以, 数据库说, "如果通过索引 COLOCATED_PK从头到尾读取COLOCATED表中的每一行, 就要执行1190次I/O, 不过我们队DISORGANIZED表做
            同样的事情, 则会对这个表执行 99930次 I/O" 差别的原因在于: 当oracle对索引结构执行区间扫描时, 如果它发现索引中的下一行与前
            一行在同一个数据库块上, 就不会再执行另一个 I/O, 不过, 如果下一行不在同一个块上, 就会释放当前的这个块, 而执行令一个I/O从
            缓冲区缓存获取到处理的下一个块, 因此, 在我们对索引执行区间扫描时, COLOCATED_PK索引就会发现下一行几乎总与前一行在同一个块上,
            DISORGANIZED_PK 索引发现的情况则恰好相反.
位图索引
    是为数据仓库, 即查询环境设计的, 位图索引的结构: 其中用一个索引键条目存储指向多行的指针, 这与 B*树结构部同, 在位图索引中, 可能只有
    很少的索引条目, create BITMAP index job_idx on emp(job);
    什么情况下使用位图索引:
    差异数低的数据最为合适, 比如性别, 在一个上亿条记录的表中, 100000也能算差异低的数据.
位图索引联结(个人感觉用处不大)
    通常在都是在一个表上创建索引,而且值使用这个表的列, 位图联结索引则打破了这个规则, 它允许使用另外某个表的列对一个给定表建立索引, 例如:
    create bitmap index emp_bm_idx
    on emp( d.dname )
    from emp e, dept d
    where e.deptno = d.deptno
    /
基于函数的索引(有点用)
    利用基于函数的索引, 我们能够对计算得出的列建立索引, 并在查询中使用这些索引.
    简单的基于函数索引的例子:
    我们想在EMP表的ENAME列上执行一个大小写无关的搜索, 在基于函数的索引引入之前, 我们可能必须采用另外一种完全不同的方式来做, 可能要为EMP
    表增加一个额外的列, 例如名为 UPPER_ENAME的列, 这个列由 insert 和 update 上的一个触发器维护, 这个触发器只是设置
    NEW.UPPER_NAME := UPPER(:NEW.ENAME). 另外要在这个额外的列上建立索引, 但是, 现在我们可以利用基于函数的索引了.

create table emp
as
select *
from scott.emp
where 1=0; insert into emp
(empno,ename,job,mgr,hiredate,sal,comm,deptno)
select rownum empno,
initcap(substr(object_name,1,10)) ename,
substr(object_type,1,9) JOB,
rownum MGR,
created hiredate,
rownum SAL,
rownum COMM,
(mod(rownum,4)+1)*10 DEPTNO
from all_objects
where rownum < 10000; create index emp_upper_idx on emp(upper(ename)); -- 接下来分析这个表, 让查询使用函数索引
-- 从 oracle 10g以后, 这步骤不必要, 因为默认就会使用
begin
dbms_stats.gather_table_stats
(user,'EMP',cascade=>true);
end;
/ select *
from emp
where upper(ename) = 'KING'; -- 通过执行计划, 可以看到, access(upper("ENAME")='KING')

11-5

计划函数的索引除了对使用内置函数的查询显然有帮助之外(自定义的函数也可以), 还可以用来有选择地只是对表中的某些行建立索引, 如果在表T上
    有一个索引 I: create index I on t(a, b); -- 这是B*树索引, 而且行中的A和B都为NULL, 索引结构中就没有相应的条目, 如果只对表中的某些行
    建立索引, 这就能用的上, 考虑一个很大的表, 其中有一个 NOT NULL列, 名为 PROCESSED_FLAG, 它有两个可取值: Y或N, 默认为N, 增加新行时,
    这个值都为N, 指示这一行未得到处理, 等到处理了这一行后, 则会将其更新为Y来指示已处理, 我们可能想对这个列建立索引, 从而能很快速的获取
    值为N的记录, 但是这里有数百万行, 而且几乎所有的行的值都为Y, 所得到的B*树索引将会很大, 如果我们把值从N更新为Y, 维护这样一个大索引的
    开销也相当高, 如果我们能只对感兴趣的记录建立索引(即该列值为 N 的记录).我们可以编写一个函数, 如果不想对某个给定的行加索引, 则这个
    函数就返回NULL, 而对想加索引的行则返回一个非NULL值. 例如, 由于我们只对列值为N的记录感兴趣, 所以只对这些记录加索引:

create index processed_flag_idx
on big_table( case temporary when 'N' then 'N' end ); analyze index processed_flag_idx
validate structure; select name, btree_space, lf_rows, height
from index_stats;

11-6

当你在 to_date 函数上创建索引, 有时候并不能成功, 要在基于函数的索引使用to_date, 必须使用一种无歧义的确定性日期格式, 比如你用YYYY,
    to_date就是不确定的.
应用域索引(个人感觉没用)
    oracle 所谓的扩展索引, 利用应用域索引, 你可以创建自己的索引结构, 使之像oracle提供的索引一样工作. 举例, oracle自己的文本索引
索引的常见问题
    以下就是大师回答过最多关于索引的问题的一个小总结.
    1) 视图能使用索引么?
        视图实际上就是一个存储查询, oracle 会把查询中访问视图的有关文本代之以视图定义本身, 视图只是为了方便最终用户, 优化器还是对基表
        使用查询, 使用视图时, 完全可以考虑使用为基表编写的查询中所能用的所有索引, 对视图建立索引实际上就是对基表建立索引.
    2) null 和 索引能协作么?
        B*树索引不会存储完全为null的条目, 而位图和聚簇索引则不同, 另外, 还有人问, 为什么我的查询不使用索引, select * from t where x
        is null; 这个查询无法使用索引, 正是因为 B*树索引不会存储完全为null的条目, 但是如果你的索引键值中包含1列不为null的情况, 那么就
        可以使用索引, 如下例子:

create table t ( x int, y int NOT NULL );

create unique index t_idx on t(x,y);

insert into t values ( 1, 1 );

insert into t values ( NULL, 1 );

begin
dbms_stats.gather_table_stats(user,'T');
end;
/ set autotrace on select * from t where x is null; -- 这时, 显示使用了索引

11-8

3) 外键是否应该加索引?
        前面章节中已经讨论过, 外键必须加索引.前几张也讨论了什么情况可以不对外键加索引(个人建议, 强烈加索引)
    4) 为什么没有使用我的索引?
        情况1, 我们在使用一个B*树索引, 而且谓词中没有使用索引的最前列.
            如果是这种情况, 可以假设一个表T, 在T(X,Y)上有一个索引, 我们要做查询: select * from t where y = 5, 此时, 优化器不打算使用
            T(x,y)上的索引, 因为谓词中不涉及X列, 在这种情况下, 倘若使用索引, 可能就必须查询每一个索引条目(稍后会讨论一种索引跳跃式扫描,
            这是一种例外情况), 而优化器通常更倾向于对T做全表扫描, 但这并不完全排除使用索引, 如果查询是 select x, y from t where y = 5,
            优化器就会注意到, 它不必全面扫描表来得到X 或 y, 对索引本身做一个快速的全面扫描会更合适, 因为这个索引一般比底层表小的多. 另
            一种情况下CBO也会使用T(X,Y)上的索引, 这就是索引跳跃式扫描, 当且仅当索引的最前列(在上一个例子中, 最前列就是x)只有很少的几个
            不同值, 而且优化器了解这一点, 跳跃式扫描就能很好的发挥作用.
        情况2, 我们使用 select count(*) from t 查询(或类似查询), 而且在表t上有一个B*树索引, 不过, 优化器并不是统计索引条目, 而是全表扫描
            在这种情况下, 索引可能建立在一些允许有null值的列上, 由于对于索引键完全为null的行不会建立相应的索引条目, 所以索引中的行数可
            能并不是表中的行数, 这里优化器选择是对的(当然, 如果这种情况使用索引, 那返回的行就不够了)
        情况3, 对于一个有索引的列, 做以下查询: select * from t where f(indexed_column) = value, 发现没有使用索引?
            原因是这个列上使用了函数, 我们是对 index_column 的值建立的索引, 而不是对 f(indexed_column)建立的索引, 因此不能使用这个索引,
            如果愿意, 可以另外对函数建立索引.(这个列上即有普通索引, 又有函数索引)
        情况4, 我们已经对一个字符列建立了索引, 这个列只包含数值数据, 如果使用以下语法来查询:
            select * from t where indexed_column = 5 注意查询中的数字5是常数5(而不是一个字符串), 此时就没有用indexed_column上的索引.
            因为, 我们队这个列隐式的应用了一个函数, select * from t where to_number(indexed_column) = 5, 这样就跟情况3一样了. 如果可能
            的话, 陶若谓词中有函数, 尽量不要对数据库列应用这些函数, 比如:
            where date_col >= trunc(sysdate) and date_col < trunc(sysdate+1), 可见应该尽量将函数应用在值上, 而不是列上.
        情况5, 有时使用了索引, 实际上反而会更慢, 例如:

create table t
( x, y , primary key (x) )
as
select rownum x, object_name
from all_objects
/ begin
dbms_stats.gather_table_stats
( user, 'T', cascade=>true );
end;
/ set autotrace on explain select count(y) from t where x < 50; -- 优化器使用索引 select count(y) from t where x < 15000; -- 全表扫描

11-9

对于查询调优时, 如果发现你认为本该使用的某个索引实际上并没有使用, 就不要冒然强制使用这个索引, 而应该先做个测试, 并证明使用
            这个索引后确实会加快速度, 然后再考虑强制使用索引.
        情况6, 有一段时间没有分析表, 这些表起先很小, 但等到查看时, 它已经增长的非常大, 有时候, 分析这个表, 然后就会使用索引. 分析表的
            作用时, 将这个表的正确的统计信息反馈给 CBO, 这样CBO能作出正确的选择.