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Oracle中使用Rownum分页详细例子

程序员文章站 2024-01-04 12:07:46
在mysql中,我们通常都使用limit来完成数据集获取的分页操作,而在oracle数据库中,并没有类似limit一样的方便方法来实现分页,因此我们通常都是直接在sql语句...

在mysql中,我们通常都使用limit来完成数据集获取的分页操作,而在oracle数据库中,并没有类似limit一样的方便方法来实现分页,因此我们通常都是直接在sql语句中完成分页,这里就需要借助于rownum伪列或row_number()函数了,本文将分别展示使用rownum伪列和row_number()分析函数来完成oracle数据分页操作的具体使用方法,并分析和比较两者的性能优劣。

一、初始化测试数据

首先测试数据我选取了数据字典all_objects表中的70000条数据,创建步骤如下:

复制代码 代码如下:

-- 为了方便验证结果集以及避免不必要的排序,这里我直接使用了rownum来产生了有序的object_id列
sql> create table my_objects as
2 select rownum as object_id,object_name,object_type
3 from all_objects where rownum < 70001;

table created.

-- 对ojbect_id列建立主键
sql> alter table my_objects add primary key (object_id);

table altered.

sql> select count(*) from my_objects;

count(*)
----------
70000

-- 分析该表
sql> exec dbms_stats.gather_table_stats(user,'my_objects',cascade => true);

pl/sql procedure successfully completed.

二、分页数据获取

为了完成分页,我们需要获得该表中的第59991-60000条的10条记录,这个工作我们分别使用rownum和rown_number()来实现

复制代码 代码如下:

-- 方法一,rownum伪列方式
sql> select t.* from (select d.*,rownum num from my_objects d where rownum<=60000) t where t.num>=59991;

object_id object_name object_type num
---------- ------------------------------ ------------------- ----------
59991 /585bb929_dicomrepos24 java class 59991
59992 /13a1874f_dicomrepos25 java class 59992
59993 /2322ccf0_dicomrepos26 java class 59993
59994 /6c82abc6_dicomrepos27 java class 59994
59995 /34be1a57_dicomrepos28 java class 59995
59996 /b7ee0c7f_dicomrepos29 java class 59996
59997 /bb1d935c_dicomrepos30 java class 59997
59998 /deb95b4f_dicomrepos31 java class 59998
59999 /9b5f55c0_dicomrepos32 java class 59999
60000 /572f1657_dicomrepos33 java class 60000

10 rows selected.

-- 方法二,row_number分析函数方式
sql> select * from
2 (select t.*,row_number() over (order by t.object_id) as num
3 from my_objects t)
4 where num between 59991 and 60000;

object_id object_name object_type num
---------- ------------------------------ ------------------- ----------
59991 /585bb929_dicomrepos24 java class 59991
59992 /13a1874f_dicomrepos25 java class 59992
59993 /2322ccf0_dicomrepos26 java class 59993
59994 /6c82abc6_dicomrepos27 java class 59994
59995 /34be1a57_dicomrepos28 java class 59995
59996 /b7ee0c7f_dicomrepos29 java class 59996
59997 /bb1d935c_dicomrepos30 java class 59997
59998 /deb95b4f_dicomrepos31 java class 59998
59999 /9b5f55c0_dicomrepos32 java class 59999
60000 /572f1657_dicomrepos33 java class 60000

10 rows selected.

可以看到这两种方式都返回了正确的结果集;在rownum方法中,由于不可以直接使用rownum伪列执行”大于“比较运算,所以这里是先从子查询中使用rownum来获得前60000条数据,然后在外层查询中使用大于运算去除不需要的行。而对于row_number()方法,row_number()分析函数以object_id排序并为其生成了唯一的标识,然后通过between这种便于理解的方式来获取区间数据,那么实际的执行是不是这样的呢?我们来简单分析一下两者的执行细节。

三、分页性能分析

首先还是看一下他们的执行计划:

复制代码 代码如下:

sql> set autotrace traceonly
sql> set linesize 200

-- rownum伪列分页的执行计划
sql> select t.* from (select d.*,rownum num from my_objects d where rownum<=60000) t where t.num>=59991;

10 rows selected.

execution plan
----------------------------------------------------------
plan hash value: 341064162

----------------------------------------------------------------------------------
| id | operation | name | rows | bytes | cost (%cpu)| time |
----------------------------------------------------------------------------------
| 0 | select statement | | 60000 | 3164k| 103 (0)| 00:00:02 |
|* 1 | view | | 60000 | 3164k| 103 (0)| 00:00:02 |
|* 2 | count stopkey | | | | | |
| 3 | table access full| my_objects | 60000 | 2226k| 103 (0)| 00:00:02 |
----------------------------------------------------------------------------------

predicate information (identified by operation id):
---------------------------------------------------

1 - filter("t"."num">=59991)
2 - filter(rownum<=60000)

statistics
----------------------------------------------------------
163 recursive calls
0 db block gets
399 consistent gets
0 physical reads
0 redo size
1030 bytes sent via sql*net to client
419 bytes received via sql*net from client
2 sql*net roundtrips to/from client
5 sorts (memory)
0 sorts (disk)
10 rows processed

-- row_number()分页的执行计划
sql> select * from
2 (select t.*,row_number() over (order by t.object_id) as num
3 from my_objects t)
4 where num between 59991 and 60000;

10 rows selected.

execution plan
----------------------------------------------------------
plan hash value: 2942654422

----------------------------------------------------------------------------------------------
| id | operation | name | rows | bytes | cost (%cpu)| time |
----------------------------------------------------------------------------------------------
| 0 | select statement | | 70000 | 3691k| 565 (1)| 00:00:07 |
|* 1 | view | | 70000 | 3691k| 565 (1)| 00:00:07 |
|* 2 | window nosort stopkey | | 70000 | 2597k| 565 (1)| 00:00:07 |
| 3 | table access by index rowid| my_objects | 70000 | 2597k| 565 (1)| 00:00:07 |
| 4 | index full scan | sys_c0011057 | 70000 | | 146 (0)| 00:00:02 |
----------------------------------------------------------------------------------------------

predicate information (identified by operation id):
---------------------------------------------------

1 - filter("num">=59991 and "num"<=60000)
2 - filter(row_number() over ( order by "t"."object_id")<=60000)

statistics
----------------------------------------------------------
1 recursive calls
0 db block gets
490 consistent gets
0 physical reads
0 redo size
1030 bytes sent via sql*net to client
419 bytes received via sql*net from client
2 sql*net roundtrips to/from client
0 sorts (memory)
0 sorts (disk)
10 rows processed

从上面的执行计划中我们可以看出,rownum方法使用了全表扫描来获得表中的前60000行,然后使用谓词条件”t”.”num”>=59991来过滤掉了不需要的行;而row_number()方法虽然利用到了主键索引来省去了分析函数本身产生的window的排序操作,但它还是先获取了表中的所有70000行数据,然后再使用between关键字来过滤数据行,这个操作的很多资源都消耗在了数据读取上了,所以上面的例子中,rownum伪列方法获得了较好的性能,而实际上,在大多数情况下,第一种rownum方法都会获得较好的性能。

可能有人会疑问,既然row_number()方法在数据读取上面花费了这么多的资源,为什么不直接让它全表扫描呢,那么我们来看看使用全表扫描的情形:

复制代码 代码如下:

-- 直接禁用主键
sql> alter table my_objects disable primary key;

table altered.

sql> select * from
2 (select t.*,row_number() over (order by t.object_id) as num
3 from my_objects t)
4 where num between 59991 and 60000;

10 rows selected.

execution plan
----------------------------------------------------------
plan hash value: 2855691782

-----------------------------------------------------------------------------------------------
| id | operation | name | rows | bytes |tempspc| cost (%cpu)| time |
-----------------------------------------------------------------------------------------------
| 0 | select statement | | 70000 | 3691k| | 812 (1)| 00:00:10 |
|* 1 | view | | 70000 | 3691k| | 812 (1)| 00:00:10 |
|* 2 | window sort pushed rank| | 70000 | 2597k| 3304k| 812 (1)| 00:00:10 |
| 3 | table access full | my_objects | 70000 | 2597k| | 120 (1)| 00:00:02 |
-----------------------------------------------------------------------------------------------

predicate information (identified by operation id):
---------------------------------------------------

1 - filter("num">=59991 and "num"<=60000)
2 - filter(row_number() over ( order by "t"."object_id")<=60000)

statistics
----------------------------------------------------------
190 recursive calls
0 db block gets
450 consistent gets
0 physical reads
0 redo size
1030 bytes sent via sql*net to client
419 bytes received via sql*net from client
2 sql*net roundtrips to/from client
6 sorts (memory)
0 sorts (disk)
10 rows processed

可以看到这种全表扫描的情形发生window sort pushed rank方法,也就是说这会cpu资源又花在了对object_id的排序上了,尽管在本例中object_id已经有序了,性能上同样不及rownum方式。

所以在写程序的过程中,对于oracle的分页操作我还是倾向于使用如下的rownum的方式来完成,通常的写法如下:

复制代码 代码如下:

-- 返回第20页数据,每页10行
sql> define pagenum=20
sql> define pagerecord=10
sql> select t.* from (select d.*,rownum num from my_objects d
2 where rownum<=&pagerecord*&pagenum) t
3 where t.num>=(&pagenum-1)*&pagerecord +1;

old 2: where rownum<=&pagerecord*&pagenum) t
new 2: where rownum<=10*20) t
old 3: where t.num>=(&pagenum-1)*&pagerecord +1
new 3: where t.num>=(20-1)*10 +1

object_id object_name object_type num
---------- ------------------------------ ------------------- ----------
191 sqlobj$data_pkey index 191
192 sqlobj$auxdata table 192
193 i_sqlobj$auxdata_pkey index 193
194 i_sqlobj$auxdata_task index 194
195 object_usage table 195
196 i_stats_obj# index 196
197 procedure$ table 197
198 procedureinfo$ table 198
199 argument$ table 199
200 source$ table 200

10 rows selected.

备注:

在写程序的时候为了便于理解,也会有人在rownum方法中使用between来限定数据行,写法如下:

复制代码 代码如下:

select t.* from (select rownum num, d.* from my_objects d) t where t.num between 59991 and 60000;

在他们看来,这样写返回的数据行和第一种rownum方法是一致的,oracle会推进谓词between部分到子查询内部,同样也不影响性能,而这种想法是完全错误的,我们来看一下它的具体执行计划:

复制代码 代码如下:

sql> select t.* from (select rownum num, d.* from my_objects d) t where t.num between 59991 and 60000;

10 rows selected.

execution plan
----------------------------------------------------------
plan hash value: 1665864874

----------------------------------------------------------------------------------
| id | operation | name | rows | bytes | cost (%cpu)| time |
----------------------------------------------------------------------------------
| 0 | select statement | | 70000 | 3691k| 120 (1)| 00:00:02 |
|* 1 | view | | 70000 | 3691k| 120 (1)| 00:00:02 |
| 2 | count | | | | | |
| 3 | table access full| my_objects | 70000 | 2597k| 120 (1)| 00:00:02 |
----------------------------------------------------------------------------------

predicate information (identified by operation id):
---------------------------------------------------

1 - filter("t"."num"<=60000 and "t"."num">=59991)

statistics
----------------------------------------------------------
0 recursive calls
0 db block gets
423 consistent gets
0 physical reads
0 redo size
1030 bytes sent via sql*net to client
419 bytes received via sql*net from client
2 sql*net roundtrips to/from client
0 sorts (memory)
0 sorts (disk)
10 rows processed

可以非常醒目的看到这个查询先发生了70000行的全表扫描,并非预想的60000行,原因还是rownum,在子查询中使用rownum直接禁用了查询转换阶段的谓语前推功能,所以上面的查询只能先获得所有的数据再应用between来过滤了。可以参考我的这篇【cbo-查询转换探究】。

说了这么多,其实也就是oracle的分页的三条sql语句,对于数据量非常大的分页问题,单纯这样做是不会获得高效的,因此还需要借助于一些其他技术,比如反范式化设计,预先计算或者在应用层建立适当的缓存机制。

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