在ORACLE中的分析函數(shù)都是基于某幾個(gè)字段劃分計(jì)算窗口，然后在窗口內(nèi)進(jìn)行聚合，排名，等等計(jì)算。我想如果我們數(shù)據(jù)表的hash分區(qū)字段與分析函數(shù)中的partition by 字段一致的時(shí)候，應(yīng)該可以大大加快分析函數(shù)的運(yùn)行效率。因?yàn)槊總€(gè)分區(qū)上的數(shù)據(jù)可以單獨(dú)進(jìn)行運(yùn)算?；ゲ桓缮?，下面試驗(yàn)來驗(yàn)證我的想法.

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***步：創(chuàng)建一個(gè)分區(qū)表和普通表，表結(jié)構(gòu)與DBA_OBJECTS一致：

create table t_partition_hash(
object_name varchar2(128),
subobject_name varchar2(30),
object_id number,
data_object_id number,
object_type varchar2(19),
created date,
last_ddl_time date,
timestamp varchar2(19),
status varchar2(7),
temporary varchar2(1),
generated varchar2(1),
secondary varchar2(1)
)
 partition by hash(object_type)(
 partition t_hash_p1 tablespace USERS,
 partition t_hash_p2 tablespace USERS,
 partition t_hash_p3 tablespace USERS,
 partition t_hash_p4 tablespace USERS,
 partition t_hash_p5 tablespace USERS,
 partition t_hash_p6 tablespace USERS,
 partition t_hash_p7 tablespace USERS,
 partition t_hash_p8 tablespace USERS
 );
create table t_big_hash(
object_name varchar2(128),
subobject_name varchar2(30),
object_id number,
data_object_id number,
object_type varchar2(19),
created date,
last_ddl_time date,
timestamp varchar2(19),
status varchar2(7),
temporary varchar2(1),
generated varchar2(1),
secondary varchar2(1)
);

第二步：準(zhǔn)備數(shù)據(jù)，從dba_object中把數(shù)據(jù)插入到兩個(gè)表?？偣膊迦霐?shù)據(jù)1610880。

insert into t_partition_hash select * from dba_objects;
insert into t_partition_hash select * from dba_objects;

第三步：本采用RANK函數(shù)對(duì)兩個(gè)表進(jìn)行查詢。

begin
insert into  t_rank
select object_id, 
rank() over (partition by object_type order by object_id)  r_object_id,
rank() over (partition by object_type order by subobject_name) r_subobject_name ,
rank() over (partition by object_type order by created) r_created,
rank() over (partition by object_type order by last_ddl_time) r_last_ddl_time ,
rank() over (partition by object_type order by status) r_object_type
 from t_partition_hash;
end;

使用hash分區(qū)表總共執(zhí)行5次的運(yùn)行時(shí)間分別為：46.156s,33.39s,40.516s 34.875s 38.938s.

begin
insert into  t_rank
select object_id, 
rank() over (partition by object_type order by object_id)  r_object_id,
rank() over (partition by object_type order by subobject_name) r_subobject_name ,
rank() over (partition by object_type order by created) r_created,
rank() over (partition by object_type order by last_ddl_time) r_last_ddl_time ,
rank() over (partition by object_type order by status) r_object_type
 from t_big_table;
end; 
使用非分區(qū)表執(zhí)行5次的執(zhí)行時(shí)間分別為：141.954s，89.656s，77.906s，98.5s，75.906s.

由此可見采用有效的HASH分區(qū)表可以有效提升分析函數(shù)在oracle中的執(zhí)行效率。我相信隨著數(shù)據(jù)量的增加，將會(huì)有更明顯的效果，回頭再測(cè)試一個(gè)項(xiàng)目中遇到的類似問題。