oracle 提供了start with connect by 语法结构可以实现递归查询。
1. 一个简单举例:
SQL> select * from test;
BILL_MONTH DAY_NUMBER MSISDN
-------------------- ---------- --------------------
200803 1 13800
200803 3 13800
200803 2 13800
200803 2 13801
200803 4 13804
200803 5 13804
200803 7 13804
200803 8 13804
200803 6 13802
200803 6 13801
200803 7 13801
200803 8 13801
12 rows selected
SQL>
SQL> select * from test
2 start with day_number=1
3 connect by prior day_number=day_number-1 and prior msisdn= msisdn
4 ;
BILL_MONTH DAY_NUMBER MSISDN
-------------------- ---------- --------------------
200803 1 13800
200803 2 13800
200803 3 13800
SQL>
上面的语句查找出了从1开始,并且day_number 逐渐+1 递增的,并且 msisdn 相同的哪些个数据.
2. start with connect by 语法结构
如上面说看到的 例子, 其语法结构为 start with condition connect by condition (含 prior 关键字)
start with conditon 给出的seed 数据的范围, connect by 后面给出了递归查询的条件,prior 关键字表示父数据,prior 条件表示子数据需要满足父数据的什么条件。
在下面的这个start with connect by 结构中,就表示 查找出了从1开始,并且day_number 逐渐+1 递增的,并且 msisdn 相同的那些个数据.
start with day_number=1
connect by prior day_number=day_number-1 and prior msisdn= msisdn
3. 执行计划
对于这个特殊的语法结构,我们来看看它的执行计划。
通过下面的执行计划,我们可以看出,对于简单的访问一个对象的递归查询,实际上oracle 要三次访问要查询的对象。因此,这一个告诉我们,在使用递归查询时,一定要谨慎,因为即使原表数据不多,但是三倍的访问喜爱来,代价也会很大。
SQL> explain plan for
2
2 select * from test
3 --where bill_month='200803'
4 start with day_number=1
5 connect by prior day_number=day_number-1 and prior msisdn= msisdn
6 ;
Explained
SQL> select * from table( dbms_xplan.display);
PLAN_TABLE_OUTPUT
--------------------------------------------------------------------------------
-------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes | Cost |
-------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | | | |
|* 1 | CONNECT BY WITH FILTERING| | | | |
|* 2 | FILTER | | | | |
| 3 | TABLE ACCESS FULL | TEST | | | |
| 4 | NESTED LOOPS | | | | |
| 5 | BUFFER SORT | | | | |
| 6 | CONNECT BY PUMP | | | | |
|* 7 | TABLE ACCESS FULL | TEST | | | |
| 8 | TABLE ACCESS FULL | TEST | | | |
-------------------------------------------------------------------------
Predicate Information (identified by operation id):
---------------------------------------------------
1 - filter("TEST"."DAY_NUMBER"=1)
2 - filter("TEST"."DAY_NUMBER"=1)
PLAN_TABLE_OUTPUT
--------------------------------------------------------------------------------
7 - filter("TEST"."MSISDN"=NULL AND "TEST"."DAY_NUMBER"-1=NULL)
Note: rule based optimization
23 rows selected
SQL>
另外,发现了在含有其他条件的递归中,是先处理所有的递归查询,最后才用加入的条件过滤.
请看下面的例子。
和上面的执行计划对比下我们可以知道,加入条件 where bill_month='200803' 后,实际上却是在递归完成后,最后才执行的 1 - filter("TEST"."BILL_MONTH"='200803') 。
所以,为了确保语句的性能,不要直接加入条件在start with connect by 结构中,而是要想办法将原表的数据控制住。这个可以采用子查询的办法,或者使用临时表等(最好采用临时表,将数据量从本源上控制住;因为从子查询的执行计划我们可以看到,它每次也都是访问全表,再用条件过滤,要重复三次,不是一次过滤就够了).
--直接加入条件后的执行计划
SQL> explain plan for
2
2 select * from test
3 where bill_month='200803'
4 start with day_number=1
5 connect by prior day_number=day_number-1 and prior msisdn= msisdn
6 ;
Explained
SQL> select * from table( dbms_xplan.display);
PLAN_TABLE_OUTPUT
--------------------------------------------------------------------------------
--------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes | Cost |
--------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | | | |
|* 1 | FILTER | | | | |
|* 2 | CONNECT BY WITH FILTERING| | | | |
|* 3 | FILTER | | | | |
| 4 | TABLE ACCESS FULL | TEST | | | |
| 5 | NESTED LOOPS | | | | |
| 6 | BUFFER SORT | | | | |
| 7 | CONNECT BY PUMP | | | | |
|* 8 | TABLE ACCESS FULL | TEST | | | |
| 9 | TABLE ACCESS FULL | TEST | | | |
--------------------------------------------------------------------------
Predicate Information (identified by operation id):
---------------------------------------------------
1 - filter("TEST"."BILL_MONTH"='200803')
PLAN_TABLE_OUTPUT
--------------------------------------------------------------------------------
2 - filter("TEST"."DAY_NUMBER"=1)
3 - filter("TEST"."DAY_NUMBER"=1)
8 - filter("TEST"."MSISDN"=NULL AND "TEST"."DAY_NUMBER"-1=NULL)
Note: rule based optimization
25 rows selected
SQL>
--使用子查询,将过滤条件嵌在子查询中
SQL> explain plan for
2
2 select * from (select * from test
3 where bill_month='200803')
4 start with day_number=1
5 connect by prior day_number=day_number-1 and prior msisdn= msisdn
6 ;
Explained
SQL> select * from table(dbms_xplan.display);
PLAN_TABLE_OUTPUT
--------------------------------------------------------------------------------
-------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes | Cost |
-------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | | | |
|* 1 | CONNECT BY WITH FILTERING| | | | |
|* 2 | FILTER | | | | |
|* 3 | TABLE ACCESS FULL | TEST | | | |
| 4 | NESTED LOOPS | | | | |
| 5 | BUFFER SORT | | | | |
| 6 | CONNECT BY PUMP | | | | |
|* 7 | TABLE ACCESS FULL | TEST | | | |
|* 8 | TABLE ACCESS FULL | TEST | | | |
-------------------------------------------------------------------------
Predicate Information (identified by operation id):
---------------------------------------------------
1 - filter("TEST"."DAY_NUMBER"=1)
2 - filter("TEST"."DAY_NUMBER"=1)
PLAN_TABLE_OUTPUT
--------------------------------------------------------------------------------
3 - filter("TEST"."BILL_MONTH"='200803')
7 - filter("TEST"."BILL_MONTH"='200803' AND "TEST"."MSISDN"=NULL AND
"TEST"."DAY_NUMBER"-1=NULL)
8 - filter("TEST"."BILL_MONTH"='200803')
Note: rule based optimization
26 rows selected
SQL>
4. 实际中 递归查询的使用。
问题:
数据库里有字段day_number,msisdn。如何写月度连续3天有记录的手机号?表结构如下:
id bill_month day_number msisdn
1 200803 1 13800000000
2 200803 1 130137.....
3 200803 2 13800000000
4 200803 3 13800000000
..............................
表中3月份连续3天有记录的纪录就是1380000000。请问如何写这样的sql?
解决方案:
SQL> create table test ( bill_month varchar2(20),day_number number ,msisdn varchar2(20));
Table created
SQL> insert into test values ( '200803',1,'13800');
1 row inserted
SQL> insert into test values ( '200803',3,'13800');
1 row inserted
SQL> insert into test values ( '200803',2,'13800');
1 row inserted
SQL> insert into test values ( '200803',2,'13801');
1 row inserted
SQL> insert into test values ( '200803',4,'13804');
1 row inserted
SQL> insert into test values ( '200803',5,'13804');
1 row inserted
SQL> commit;
Commit complete
SQL> select * from test;
BILL_MONTH DAY_NUMBER MSISDN
-------------------- ---------- --------------------
200803 1 13800
200803 3 13800
200803 2 13800
200803 2 13801
200803 4 13804
200803 5 13804
6 rows selected
SQL>
SQL> select distinct msisdn from test a
2 where bill_month='200803'
3 and exists
4 ( select msisdn from test
5 where bill_month='200803' and msisdn=a.msisdn
6 start with day_number=a.day_number
7 connect by prior day_number=day_number-1 and prior msisdn= msisdn
8 group by msisdn
9 having count(*)>=3
10 );
MSISDN
--------------------
13800
SQL> select * from test;
BILL_MONTH DAY_NUMBER MSISDN
-------------------- ---------- --------------------
200803 1 13800
200803 3 13800
200803 2 13800
200803 2 13801
200803 4 13804
200803 5 13804
6 rows selected
SQL> insert into test values ( '200803',7,'13804');
1 row inserted
SQL> insert into test values ( '200803',8,'13804');
1 row inserted
SQL> insert into test values ( '200803',6,'13802');
1 row inserted
SQL> insert into test values ( '200803',6,'13801');
1 row inserted
SQL> insert into test values ( '200803',7,'13801');
1 row inserted
SQL> insert into test values ( '200803',8,'13801');
1 row inserted
SQL> select * from test;
BILL_MONTH DAY_NUMBER MSISDN
-------------------- ---------- --------------------
200803 1 13800
200803 3 13800
200803 2 13800
200803 2 13801
200803 4 13804
200803 5 13804
200803 7 13804
200803 8 13804
200803 6 13802
200803 6 13801
200803 7 13801
200803 8 13801
12 rows selected
SQL> commit;
Commit complete
SQL>
SQL> select distinct msisdn from test a
2 where bill_month='200803'
3 and exists
4 ( select msisdn from test
5 where bill_month='200803' and msisdn=a.msisdn
6 start with day_number=a.day_number
7 connect by prior day_number=day_number-1 and prior msisdn= msisdn
8 group by msisdn
9 having count(*)>=3
10 );
MSISDN
--------------------
13800
13801
SQL>
1. 一个简单举例:
SQL> select * from test;
BILL_MONTH DAY_NUMBER MSISDN
-------------------- ---------- --------------------
200803 1 13800
200803 3 13800
200803 2 13800
200803 2 13801
200803 4 13804
200803 5 13804
200803 7 13804
200803 8 13804
200803 6 13802
200803 6 13801
200803 7 13801
200803 8 13801
12 rows selected
SQL>
SQL> select * from test
2 start with day_number=1
3 connect by prior day_number=day_number-1 and prior msisdn= msisdn
4 ;
BILL_MONTH DAY_NUMBER MSISDN
-------------------- ---------- --------------------
200803 1 13800
200803 2 13800
200803 3 13800
SQL>
上面的语句查找出了从1开始,并且day_number 逐渐+1 递增的,并且 msisdn 相同的哪些个数据.
2. start with connect by 语法结构
如上面说看到的 例子, 其语法结构为 start with condition connect by condition (含 prior 关键字)
start with conditon 给出的seed 数据的范围, connect by 后面给出了递归查询的条件,prior 关键字表示父数据,prior 条件表示子数据需要满足父数据的什么条件。
在下面的这个start with connect by 结构中,就表示 查找出了从1开始,并且day_number 逐渐+1 递增的,并且 msisdn 相同的那些个数据.
start with day_number=1
connect by prior day_number=day_number-1 and prior msisdn= msisdn
3. 执行计划
对于这个特殊的语法结构,我们来看看它的执行计划。
通过下面的执行计划,我们可以看出,对于简单的访问一个对象的递归查询,实际上oracle 要三次访问要查询的对象。因此,这一个告诉我们,在使用递归查询时,一定要谨慎,因为即使原表数据不多,但是三倍的访问喜爱来,代价也会很大。
SQL> explain plan for
2
2 select * from test
3 --where bill_month='200803'
4 start with day_number=1
5 connect by prior day_number=day_number-1 and prior msisdn= msisdn
6 ;
Explained
SQL> select * from table( dbms_xplan.display);
PLAN_TABLE_OUTPUT
--------------------------------------------------------------------------------
-------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes | Cost |
-------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | | | |
|* 1 | CONNECT BY WITH FILTERING| | | | |
|* 2 | FILTER | | | | |
| 3 | TABLE ACCESS FULL | TEST | | | |
| 4 | NESTED LOOPS | | | | |
| 5 | BUFFER SORT | | | | |
| 6 | CONNECT BY PUMP | | | | |
|* 7 | TABLE ACCESS FULL | TEST | | | |
| 8 | TABLE ACCESS FULL | TEST | | | |
-------------------------------------------------------------------------
Predicate Information (identified by operation id):
---------------------------------------------------
1 - filter("TEST"."DAY_NUMBER"=1)
2 - filter("TEST"."DAY_NUMBER"=1)
PLAN_TABLE_OUTPUT
--------------------------------------------------------------------------------
7 - filter("TEST"."MSISDN"=NULL AND "TEST"."DAY_NUMBER"-1=NULL)
Note: rule based optimization
23 rows selected
SQL>
另外,发现了在含有其他条件的递归中,是先处理所有的递归查询,最后才用加入的条件过滤.
请看下面的例子。
和上面的执行计划对比下我们可以知道,加入条件 where bill_month='200803' 后,实际上却是在递归完成后,最后才执行的 1 - filter("TEST"."BILL_MONTH"='200803') 。
所以,为了确保语句的性能,不要直接加入条件在start with connect by 结构中,而是要想办法将原表的数据控制住。这个可以采用子查询的办法,或者使用临时表等(最好采用临时表,将数据量从本源上控制住;因为从子查询的执行计划我们可以看到,它每次也都是访问全表,再用条件过滤,要重复三次,不是一次过滤就够了).
--直接加入条件后的执行计划
SQL> explain plan for
2
2 select * from test
3 where bill_month='200803'
4 start with day_number=1
5 connect by prior day_number=day_number-1 and prior msisdn= msisdn
6 ;
Explained
SQL> select * from table( dbms_xplan.display);
PLAN_TABLE_OUTPUT
--------------------------------------------------------------------------------
--------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes | Cost |
--------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | | | |
|* 1 | FILTER | | | | |
|* 2 | CONNECT BY WITH FILTERING| | | | |
|* 3 | FILTER | | | | |
| 4 | TABLE ACCESS FULL | TEST | | | |
| 5 | NESTED LOOPS | | | | |
| 6 | BUFFER SORT | | | | |
| 7 | CONNECT BY PUMP | | | | |
|* 8 | TABLE ACCESS FULL | TEST | | | |
| 9 | TABLE ACCESS FULL | TEST | | | |
--------------------------------------------------------------------------
Predicate Information (identified by operation id):
---------------------------------------------------
1 - filter("TEST"."BILL_MONTH"='200803')
PLAN_TABLE_OUTPUT
--------------------------------------------------------------------------------
2 - filter("TEST"."DAY_NUMBER"=1)
3 - filter("TEST"."DAY_NUMBER"=1)
8 - filter("TEST"."MSISDN"=NULL AND "TEST"."DAY_NUMBER"-1=NULL)
Note: rule based optimization
25 rows selected
SQL>
--使用子查询,将过滤条件嵌在子查询中
SQL> explain plan for
2
2 select * from (select * from test
3 where bill_month='200803')
4 start with day_number=1
5 connect by prior day_number=day_number-1 and prior msisdn= msisdn
6 ;
Explained
SQL> select * from table(dbms_xplan.display);
PLAN_TABLE_OUTPUT
--------------------------------------------------------------------------------
-------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes | Cost |
-------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | | | |
|* 1 | CONNECT BY WITH FILTERING| | | | |
|* 2 | FILTER | | | | |
|* 3 | TABLE ACCESS FULL | TEST | | | |
| 4 | NESTED LOOPS | | | | |
| 5 | BUFFER SORT | | | | |
| 6 | CONNECT BY PUMP | | | | |
|* 7 | TABLE ACCESS FULL | TEST | | | |
|* 8 | TABLE ACCESS FULL | TEST | | | |
-------------------------------------------------------------------------
Predicate Information (identified by operation id):
---------------------------------------------------
1 - filter("TEST"."DAY_NUMBER"=1)
2 - filter("TEST"."DAY_NUMBER"=1)
PLAN_TABLE_OUTPUT
--------------------------------------------------------------------------------
3 - filter("TEST"."BILL_MONTH"='200803')
7 - filter("TEST"."BILL_MONTH"='200803' AND "TEST"."MSISDN"=NULL AND
"TEST"."DAY_NUMBER"-1=NULL)
8 - filter("TEST"."BILL_MONTH"='200803')
Note: rule based optimization
26 rows selected
SQL>
4. 实际中 递归查询的使用。
问题:
数据库里有字段day_number,msisdn。如何写月度连续3天有记录的手机号?表结构如下:
id bill_month day_number msisdn
1 200803 1 13800000000
2 200803 1 130137.....
3 200803 2 13800000000
4 200803 3 13800000000
..............................
表中3月份连续3天有记录的纪录就是1380000000。请问如何写这样的sql?
解决方案:
SQL> create table test ( bill_month varchar2(20),day_number number ,msisdn varchar2(20));
Table created
SQL> insert into test values ( '200803',1,'13800');
1 row inserted
SQL> insert into test values ( '200803',3,'13800');
1 row inserted
SQL> insert into test values ( '200803',2,'13800');
1 row inserted
SQL> insert into test values ( '200803',2,'13801');
1 row inserted
SQL> insert into test values ( '200803',4,'13804');
1 row inserted
SQL> insert into test values ( '200803',5,'13804');
1 row inserted
SQL> commit;
Commit complete
SQL> select * from test;
BILL_MONTH DAY_NUMBER MSISDN
-------------------- ---------- --------------------
200803 1 13800
200803 3 13800
200803 2 13800
200803 2 13801
200803 4 13804
200803 5 13804
6 rows selected
SQL>
SQL> select distinct msisdn from test a
2 where bill_month='200803'
3 and exists
4 ( select msisdn from test
5 where bill_month='200803' and msisdn=a.msisdn
6 start with day_number=a.day_number
7 connect by prior day_number=day_number-1 and prior msisdn= msisdn
8 group by msisdn
9 having count(*)>=3
10 );
MSISDN
--------------------
13800
SQL> select * from test;
BILL_MONTH DAY_NUMBER MSISDN
-------------------- ---------- --------------------
200803 1 13800
200803 3 13800
200803 2 13800
200803 2 13801
200803 4 13804
200803 5 13804
6 rows selected
SQL> insert into test values ( '200803',7,'13804');
1 row inserted
SQL> insert into test values ( '200803',8,'13804');
1 row inserted
SQL> insert into test values ( '200803',6,'13802');
1 row inserted
SQL> insert into test values ( '200803',6,'13801');
1 row inserted
SQL> insert into test values ( '200803',7,'13801');
1 row inserted
SQL> insert into test values ( '200803',8,'13801');
1 row inserted
SQL> select * from test;
BILL_MONTH DAY_NUMBER MSISDN
-------------------- ---------- --------------------
200803 1 13800
200803 3 13800
200803 2 13800
200803 2 13801
200803 4 13804
200803 5 13804
200803 7 13804
200803 8 13804
200803 6 13802
200803 6 13801
200803 7 13801
200803 8 13801
12 rows selected
SQL> commit;
Commit complete
SQL>
SQL> select distinct msisdn from test a
2 where bill_month='200803'
3 and exists
4 ( select msisdn from test
5 where bill_month='200803' and msisdn=a.msisdn
6 start with day_number=a.day_number
7 connect by prior day_number=day_number-1 and prior msisdn= msisdn
8 group by msisdn
9 having count(*)>=3
10 );
MSISDN
--------------------
13800
13801
SQL>
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本文章详细介绍了Oracle中connect by...start with...的用法。
Oracle 连接查询是指使用 START WITH 和 CONNECT BY 语句来实现递归查询的方法,这种方法可以生成树形结构的数据。在 Oracle 中,START WITH 语句用于指定递归查询的开始记录,而 CONNECT BY 语句用于指定递归查询的...
[ WHERE condition ][ [ START WITH condition ] CONNECT BY condition [ ORDER SIBLINGS BY expression ] ] ``` 其中,`START WITH`子句用于指定查询的起始节点,`CONNECT BY`子句用于指定查询的递归条件。 ...
Oracle是甲骨文公司的一款关系型...使用Connect By进行查询时,需要特别注意循环关系的处理,以及正确地使用`START WITH`、`CONNECT BY`子句和相关伪列。掌握这些知识点,对于Oracle数据库开发人员来说是必不可少的。
下面将详细阐述`CONNECT BY`的使用方法、原理以及一些常见的应用场景。 1. **基本语法** `CONNECT BY` 的基本语法如下: ```sql SELECT column1, column2, ... FROM table_name START WITH condition1 CONNECT BY ...
Oracle数据库中的`CONNECT BY PRIOR`是一个强大的查询构造器,用于处理树形数据结构,尤其在组织层级、部门结构或者员工管理系统中非常常见。这个功能允许我们从一个或多个根节点开始,按照指定的规则遍历整个树结构...
### Oracle `CONNECT BY` 用法总结 `CONNECT BY` 是Oracle SQL中用于创建和遍历层次结构数据的语法。它允许你从一个或多个具有层级关系的表中提取出树形结构。以下是`CONNECT BY`的基本用法: 1. **树查询(递归...
Oracle数据库中的`connect by prior`是一个强大的SQL查询构造,用于处理具有层级关系的数据,常见于组织结构、部门层级、时间序列分析等场景。这个特性允许我们遍历和查询树形结构,将层次数据平展为一行一列的形式...
Oracle 数据库树形结构用法总结,例如SYS_CONNECT_BY_PATH 、START WITH . . . CONNECT BY . . .等具体语法介绍
在Oracle中,要查询树形结构的数据,可以使用`START WITH`和`CONNECT BY PRIOR`语句。`START WITH`用于指定查询的起始节点,而`CONNECT BY PRIOR`则定义了节点之间的父子关系。 - **`START WITH`**:指定查询的根...
Oracle允许在`CONNECT BY`之前使用`PRIOR`关键字,但不推荐,因为这可能导致无限循环。 四、性能优化 4.1 使用`CYCLE`子句 当树结构存在循环时,`CYCLE`子句可以用来检测并处理这些循环。例如: ```sql SELECT *...
Oracle 使用 `CONNECT BY` 子句以及 `LEVEL`, `PRIOR`, `CONNECT_BY_ROOT` 等伪列来实现递归查询。相比之下,DB2 使用递归 CTE 和 `UNION ALL` 来实现相同的功能。 #### 动机 在将应用从 Oracle 迁移到 DB2 的过程...
Oracle数据库系统支持对树状结构数据的查询,这种查询方式主要通过`START WITH`和`CONNECT BY`子句实现。这两个子句是Oracle特有的,用于处理层级关系的数据,例如组织结构、产品分类或者树形菜单等。理解并掌握这两...
在Oracle中,树形结构查询可以通过start with和connect by子句来实现。start with子句用于确定开始节点,而connect by子句用于指定父子关系。层次查询语句可以通过level关键字来确定层次关系,level关键字是可选的,...