sum() over(partition by … order by …):求分组后的总和。 first_value() over(partition by … order by …):求分组后的第一个。 last_value() over(partition by … order by …):求分组后的最后一个。 count() over(partition by … order by …):求分组后的总数。 max() over(partition by...
order_noVARCHAR2(20),--订单号product_noVARCHAR2(10),--产品编号product_quantityVARCHAR2(1),--产品数量is_discountVARCHAR2(2)--是否折扣 1是0否); 初始数据 insertintocux_orderinfovalues('001','101','1','0');insertintocux_orderinfovalues('001','102','2','0');insertintocux_orderinfov...
sum(...) over( partition by... order by ... ),同第1点中的排序求和原理,只是范围限制在组内 view sql
SUM(NVL(T2.IS_VISHEARTEXPMEMBER, 0)) OVER(PARTITION BY T3.I_IDENTITY_CARD) EXP_NUM, SUM(NVL(T2.IS_VISHEARTPOLMEMBER, 0)) OVER(PARTITION BY T3.I_IDENTITY_CARD) POL_NUM, T1.CREATE_TIME, FIRST_VALUE(T2.CREATE_DATE) OVER(PARTITION BY T3.I_IDENTITY_CARD ORDER BY T2.CREATE_DATE ...
order by e.deptno, e.sal; 上面我们用到了min()和max(),前者求最小值,后者求最大值。如果这两个方法配合over(partition by ...)使用会是什么效果呢?大家看看下面的SQL语句: [sql]view plaincopy select e.ename, e.job, e.sal, e.deptno, ...
sum(sal) over (order by deptno,ename) 不按部门“连续”求总和 sum(sal) over () 不按部门,求所有员工总和,效果等同于sum(sal)。 1.有partition by有order by : 在partition by分组下,按照不同的order by col3实现递增汇总.. SQL>>select DEPT_ID,ENAME,SAL,sum(SAL) over(partition by dept_id ...
使用sum(sal) over (order by ename)… 查询员工的薪水“连续”求和, 注意over (order by ename)如果没有order by 子句,求和就不是“连续”的. 放在一起,体会一下不同之处: 代码语言:javascript 代码运行次数:0 运行 AI代码解释 SQL> select e.deptno, 2 e.ename, 3 e.sal, 4 sum(sal) over(order...
使用sum(sal) over (order by ename)… 查询员工的薪水“连续”求和, 注意over (order by ename)如果没有order by 子句,求和就不是“连续”的. 放在一起,体会一下不同之处: SQL> select e.deptno,2 e.ename,3 e.sal,4 sum(sal) over(order by e.ename) 连续求和,5 sum(sal) over() 总和, -...
```sql SELECT product_id, sales_date, revenue, SUM(revenue) OVER (PARTITION BY product_id ORDER BY sales_date) AS running_total FROM sales; ``` 在这个查询中,`SUM(revenue) OVER (PARTITION BY product_id ORDER BY sales_date)`表示计算每个产品的销售总额,同时在每个产品内按照销售日期排序。`...
sql 复制代码 SELECT column1, column2, SUM(column3) OVER (PARTITION BY column1) AS sum_value FROM table_name; 在上述语法中,column1是用于分组的列名,column2是要选择的列,SUM(column3) OVER (PARTITION BY column1)表示按照column1分组,并对每个组的column3列进行求和。结果中的sum_value列将包含每个...