GBase 8a开窗函数子句rows、range的使用方法

GBase 8a 支持开窗子句rows和range, 本文介绍开窗子句的使用方法。

参考

GBase 8a窗口函数使用样例索引

语法

  • rows :指行,包含边界行
  • range :数值范围,包含边界值
  • Unbounded :是无边界
  • Preceding :向上,减去,提前
  • Following :向下,加上,延后
  • Current row :当前行
GBase 8a开窗函数子句rows的使用方法

使用说明

  • _t_gbase_new_window_function_support 参数为控制支持windowing_clause 子句的参数,参数值默认为 0,不支持 windowing_clause 子句,设置为 1 时支持 windowing_clause 子句。set _t_gbase_new_window_function_support=1
  • 不支持 windowing_clause 子句情况下,开窗方式是固定的,范围是:Range between unbounded preceding and current row
  • Partition 子句为空,则不分组,即说明全部数据为一组;order by 子句为空,则每个分组中的所有数据不排序,即一个分组就是一个“子窗口”。
  • between bound1 and bound2。
    • bound1 定义窗口的起始位置,
    • bound2 定义窗口的结束位置。
    • 单独一个 bound 时,为起始位置的定义,结束位置默认为 current row,如:select a,b,c,sum(c)over(partition by a order by b range 2 preceding) as ‘sum(c)’ from t;
  • unbounded preceding 指明起始位置,即当前分组中的行首,不能出现在 bound2 中。
  • unbounded following 指明结束位置,即当前分组中的行尾,不能出现在 bound1 中。
  • current row 指明起始或结束位置为当前行。
  • 在如下情况时,order by 关键字后可以有多个表达式:
    • Range between unbounded preceding and current row
    • Range between unbounded preceding and unbounded following
    • Range between current row and current row
    • Range between current row and unbounded following
  • value_expr preceding | value_expr following
    • 起始位置为 value_expr following 时,则结束位置应为 value_expr following;
    • 结束位置为 value_expr preceding 时,则起始位置应为 value_expr preceding。
  • rows 关键字后接 value_expr 时,不支持 interval 子句
  • value_expr 为 num 时,标识了行的偏移量,为数值常量,正整数(四舍五入)。不可为负数、数值函数、表列。
  • range 关键字后接 value_expr 时支持 interval 子句,且 order by 后只能有一个表达式:
    • value_expr 为 num 时,order by 后的表达式只能为数值或日期(时间)类型;
    • value_expr 为 interval 子句时,order by 后的表达式只能为日期(时间)类型;
    • value_expr 为 num 时,标识了行的偏移量,为数值常量,正整数(四舍五入)。不可为负数、数值函数、表列。
  • range 关键字,order by 后接唯一表达式用于计算窗口范围时:
    • 排序存在 null 值且在行首时,除非 unbounded preceding,该行不计入窗口范围;
    • 排序存在 null 值且在行尾时,除非 unbounded following,该行不计入窗口范围;
    • 当前行为 null 值,除非 unbounded preceding/following,窗口范围仅为该行。
  • 日期(时间)类型的支持范围:date、datetime 和 timestamp。

数据

gbase> create table t2(id int, type int, val int);
Query OK, 0 rows affected (Elapsed: 00:00:00.14)

gbase> insert into t2 values(1,1,111),(2,1,122),(3,1,133),(4,2,222),(5,2,233),(6,2,244),(7,3,333);
Query OK, 7 rows affected (Elapsed: 00:00:00.11)
Records: 7  Duplicates: 0  Warnings: 0

gbase> desc t2;
+-------+---------+------+-----+---------+-------+
| Field | Type    | Null | Key | Default | Extra |
+-------+---------+------+-----+---------+-------+
| id    | int(11) | YES  |     | NULL    |       |
| type  | int(11) | YES  |     | NULL    |       |
| val   | int(11) | YES  |     | NULL    |       |
+-------+---------+------+-----+---------+-------+
3 rows in set (Elapsed: 00:00:00.00)

gbase> select * from t2 order by type,val;
+------+------+------+
| id   | type | val  |
+------+------+------+
|    1 |    1 |  111 |
|    2 |    1 |  122 |
|    3 |    1 |  133 |
|    4 |    2 |  222 |
|    5 |    2 |  233 |
|    6 |    2 |  244 |
|    7 |    3 |  333 |
+------+------+------+
7 rows in set (Elapsed: 00:00:00.02)

ROWS的例子

如下以SUM OVER为例子介绍。

整体汇总值

gbase> select sum(val) v from t2;
+------+
| v    |
+------+
| 1398 |
+------+
1 row in set (Elapsed: 00:00:00.03)

移动汇总值

数据按照类型,数字排序,计算之前的汇总值。

移动汇总可以参考: GBase 8a OLAP函数移动平均值AVG,移动汇总SUM,移动计数count over等使用样例

gbase> select t2.*,sum(val) over(order by type,val) v from t2;
+------+------+------+------+
| id   | type | val  | v    |
+------+------+------+------+
|    1 |    1 |  111 |  111 |
|    2 |    1 |  122 |  233 |
|    3 |    1 |  133 |  366 |
|    4 |    2 |  222 |  588 |
|    5 |    2 |  233 |  821 |
|    6 |    2 |  244 | 1065 |
|    7 |    3 |  333 | 1398 |
+------+------+------+------+
7 rows in set (Elapsed: 00:00:00.03)

按类型分区计算移动汇总值

按照类型不同,各自计算移动汇总值。每个类型各自计算。

移动汇总可以参考: GBase 8a OLAP函数移动平均值AVG,移动汇总SUM,移动计数count over等使用样例

gbase> select t2.*,sum(val) over(partition by type order by type,val) v from t2;
+------+------+------+------+
| id   | type | val  | v    |
+------+------+------+------+
|    4 |    2 |  222 |  222 |
|    5 |    2 |  233 |  455 |
|    6 |    2 |  244 |  699 |
|    1 |    1 |  111 |  111 |
|    2 |    1 |  122 |  233 |
|    3 |    1 |  133 |  366 |
|    7 |    3 |  333 |  333 |
+------+------+------+------+
7 rows in set (Elapsed: 00:00:00.05)

指定rows的整体移动汇总值current row

先看看不分区的整体移动汇总值的情况。我们例子里指定汇总前1个数值和当前值,而不是默认的移动汇总值的,所有前面的。如下贴了2个结果,方便对比。

可以看到普通移动汇总,数值一直在累加之前的,而指定了rows的,只汇总了指定范围内的。

select t2.*,sum(val) over(order by type,val) v from t2;select t2.*,sum(val) over(order by type,val rows between 1 preceding and current row) v from t2;
+------+------+------+------+
| id | type | val | v |
+------+------+------+------+
| 1 | 1 | 111 | 111 |
| 2 | 1 | 122 | 233 |
| 3 | 1 | 133 | 366 |
| 4 | 2 | 222 | 588 |
| 5 | 2 | 233 | 821 |
| 6 | 2 | 244 | 1065 |
| 7 | 3 | 333 | 1398 |
+------+------+------+------+
7 rows in set (Elapsed: 00:00:00.02)
+------+------+------+------+
| id | type | val | v |
+------+------+------+------+
| 1 | 1 | 111 | 111 |
| 2 | 1 | 122 | 233 |
| 3 | 1 | 133 | 255 |
| 4 | 2 | 222 | 355 |
| 5 | 2 | 233 | 455 |
| 6 | 2 | 244 | 477 |
| 7 | 3 | 333 | 577 |
+------+------+------+------+
7 rows in set (Elapsed: 00:00:00.02)

指定rows的整体移动汇总值following

本例指定前1个和后1个,共3个(如果有的话)的移动汇总值。

gbase> select t2.*,sum(val) over(order by type,val rows between 1 preceding and 1 following) v from t2;
+------+------+------+------+
| id   | type | val  | v    |
+------+------+------+------+
|    1 |    1 |  111 |  233 |
|    2 |    1 |  122 |  366 |
|    3 |    1 |  133 |  477 |
|    4 |    2 |  222 |  588 |
|    5 |    2 |  233 |  699 |
|    6 |    2 |  244 |  810 |
|    7 |    3 |  333 |  577 |
+------+------+------+------+
7 rows in set (Elapsed: 00:00:00.02)

指定rows的分区移动汇总值

select t2.*,sum(val) over(partition by type order by type,val) v from t2;select t2.*,sum(val) over(partition by type order by type,val rows between 1 preceding and current row) v from t2;
+------+------+------+------+
| id | type | val | v |
+------+------+------+------+
| 1 | 1 | 111 | 111 |
| 2 | 1 | 122 | 233 |
| 3 | 1 | 133 | 366 |
| 7 | 3 | 333 | 333 |
| 4 | 2 | 222 | 222 |
| 5 | 2 | 233 | 455 |
| 6 | 2 | 244 | 699 |
+------+------+------+------+
7 rows in set (Elapsed: 00:00:00.05)
+------+------+------+------+
| id | type | val | v |
+------+------+------+------+
| 1 | 1 | 111 | 111 |
| 2 | 1 | 122 | 233 |
| 3 | 1 | 133 | 255 |
| 7 | 3 | 333 | 333 |
| 4 | 2 | 222 | 222 |
| 5 | 2 | 233 | 455 |
| 6 | 2 | 244 | 477 |
+------+------+------+------+
7 rows in set (Elapsed: 00:00:00.05)

RANGE的例子

同样以SUM OVER为例子,分别计算前面差距小于100的;前面差距小于100和后面差距小于100的。

gbase> select t2.*,sum(val) over(order by type,val) v from t2;select t2.*,sum(val) over(order by val range between 100 preceding and 1 following) v from t2;select t2.*,sum(val) over(order by val range between 100 preceding and 100 following) v from t2;
+------+------+------+------+
| id | type | val | v |
+------+------+------+------+
| 1 | 1 | 111 | 111 |
| 2 | 1 | 122 | 233 |
| 3 | 1 | 133 | 366 |
| 4 | 2 | 222 | 588 |
| 5 | 2 | 233 | 821 |
| 6 | 2 | 244 | 1065 |
| 7 | 3 | 333 | 1398 |
+------+------+------+------+
7 rows in set (Elapsed: 00:00:00.02)
+------+------+------+------+
| id | type | val | v |
+------+------+------+------+
| 1 | 1 | 111 | 111 |
| 2 | 1 | 122 | 233 |
| 3 | 1 | 133 | 366 |
| 4 | 2 | 222 | 477 |
| 5 | 2 | 233 | 588 |
| 6 | 2 | 244 | 699 |
| 7 | 3 | 333 | 810 |
+------+------+------+------+
7 rows in set (Elapsed: 00:00:00.03)
+------+------+------+------+
| id | type | val | v |
+------+------+------+------+
| 1 | 1 | 111 | 366 |
| 2 | 1 | 122 | 588 |
| 3 | 1 | 133 | 821 |
| 4 | 2 | 222 | 954 |
| 5 | 2 | 233 | 1165 |
| 6 | 2 | 244 | 1032 |
| 7 | 3 | 333 | 810 |
+------+------+------+------+
7 rows in set (Elapsed: 00:00:00.02)

时间类型的RANGE例子

换个数据表

gbase> select * from t3;
+------+--------+------------+
| id   | name   | birth      |
+------+--------+------------+
|    1 | 张三   | 1960-01-01 |
|    2 | 李四   | 1970-01-01 |
|    3 | 王五   | 1980-01-01 |
|    4 | 赵六   | 1990-01-01 |
+------+--------+------------+
4 rows in set (Elapsed: 00:00:00.01)

分别计算:向前无边界,向后5、10、20年生日差距的的数据。

gbase> select t3.*,sum(id)over(order by birth range between unbounded preceding and interval 5 year following) v from t3;
+------+--------+------------+------+
| id   | name   | birth      | v    |
+------+--------+------------+------+
|    1 | 张三   | 1960-01-01 |    1 |
|    2 | 李四   | 1970-01-01 |    3 |
|    3 | 王五   | 1980-01-01 |    6 |
|    4 | 赵六   | 1990-01-01 |   10 |
+------+--------+------------+------+
4 rows in set (Elapsed: 00:00:00.02)

gbase> select t3.*,sum(id)over(order by birth range between unbounded preceding and interval 10 year following) v from t3;
+------+--------+------------+------+
| id   | name   | birth      | v    |
+------+--------+------------+------+
|    1 | 张三   | 1960-01-01 |    3 |
|    2 | 李四   | 1970-01-01 |    6 |
|    3 | 王五   | 1980-01-01 |   10 |
|    4 | 赵六   | 1990-01-01 |   10 |
+------+--------+------------+------+
4 rows in set (Elapsed: 00:00:00.02)

gbase> select t3.*,sum(id)over(order by birth range between unbounded preceding and interval 20 year following) v from t3;
+------+--------+------------+------+
| id   | name   | birth      | v    |
+------+--------+------------+------+
|    1 | 张三   | 1960-01-01 |    6 |
|    2 | 李四   | 1970-01-01 |   10 |
|    3 | 王五   | 1980-01-01 |   10 |
|    4 | 赵六   | 1990-01-01 |   10 |
+------+--------+------------+------+
4 rows in set (Elapsed: 00:00:00.05)

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