PostgreSQL 分组集合新功能(GROUPING SETS,CUBE,ROLLUP)

实验环境

操作系统：windows 10 家庭中文版

数据库系统： PostgreSQL 9.6.2

说明

postgresql从9.5版本开始新加入了group by的分组集合功能，提供了GROUPING SETS,CUBE,ROLLUP参数，使用方式与oracle完全一致，下面是实际测试说明

构建测试环境

创建表t并插入测试数据：

create table t(id int,name varchar(20),class int,score int);

insert into t values(1,'math',1,90);

insert into t values(2,'math',2,80);

insert into t values(3,'math',1,70);

insert into t values(4,'chinese',2,60);

insert into t values(5,'chinese',1,50);

insert into t values(6,'chinese',2,60);

insert into t values(7,'physical',1,70);

insert into t values(8,'physical',2,80);

insert into t values(9,'physical',1,90);

结果：

test=# select * from t;

id | name | class | score

----+----------+-------+-------

1 | math | 1 | 90

2 | math | 2 | 80

3 | math | 1 | 70

4 | chinese | 2 | 60

5 | chinese | 1 | 50

6 | chinese | 2 | 60

7 | physical | 1 | 70

8 | physical | 2 | 80

9 | physical | 1 | 90

(9 行记录)

普通的group by

根据name和class字段求和：

test=# select name,class,sum(score)

test-# from t

test-# group by name,class

test-# order by name,class

test-# ;

name | class | sum

----------+-------+-----

chinese | 1 | 50

chinese | 2 | 120

math | 1 | 160

math | 2 | 80

physical | 1 | 160

physical | 2 | 80

(6 行记录)

grouping set

GROUPING SETS的每个子列表可以指定零个或多个列或表达式，并且与其直接在GROUP BY子句中的解释方式相同。 一个空的分组集合意味着所有的行都被聚合到一个组中(即使没有输入行存在，也是输出)。

test=# select name,class,sum(score)

test-# from t

test-# group by grouping sets((name),(class),())

test-# order by name,class

test-# ;

name | class | sum

----------+-------+-----

chinese | | 170

math | | 240

physical | | 240

| 1 | 370

| 2 | 280

| | 650

(6 行记录)

顺带一提，默认的group by语句相当于grouping set在grouping set后的参数填上所有group by的字段。如下：

test=# select name,class,sum(score)

test-# from t

test-# group by grouping sets((name,class))

test-# order by name,class

test-# ;

name | class | sum

----------+-------+-----

chinese | 1 | 50

chinese | 2 | 120

math | 1 | 160

math | 2 | 80

physical | 1 | 160

physical | 2 | 80

(6 行记录)

与不使用grouping set语句时的结果完全相同

rollup

* rollup((a),(b),(c))等价于grouping sets((a,b,c),(a,b),(a),()) *

test=# select name,class,sum(score)

test-# from t

test-# group by rollup((name),(class))

test-# order by name,class

test-# ;

name | class | sum

----------+-------+-----

chinese | 1 | 50

chinese | 2 | 120

chinese | | 170

math | 1 | 160

math | 2 | 80

math | | 240

physical | 1 | 160

physical | 2 | 80

physical | | 240

| | 650

(10 行记录)

等价于：

grouping sets((name,class),(name),())

cube

* cube((a),(b),(c))等价于grouping sets((a,b,c),(a,b),(a,c),(a),(b,c),(b),(c),()) *

test=# select name,class,sum(score)

test-# from t

test-# group by cube((name),(class))

test-# order by name,class

test-# ;

name | class | sum

----------+-------+-----

chinese | 1 | 50

chinese | 2 | 120

chinese | | 170

math | 1 | 160

math | 2 | 80

math | | 240

physical | 1 | 160

physical | 2 | 80

physical | | 240

| 1 | 370

| 2 | 280

| | 650

(12 行记录)

等价于：

grouping sets((name,class),(name),(class),())

实际应用

我遇到一个需求，需要在分组统计总和之外附加所有组的总和，命名为total：

test=# select coalesce(name,'total') as name,

test-# coalesce(class,0) as class,

test-# coalesce(sum(score),0) as sum_score,

test-# coalesce(round(avg(score),2),0) as avg_score

test-# from t

test-# group by grouping sets((name,class),())

test-# order by name,class

test-# ;

name | class | sum_score | avg_score

----------+-------+-----------+-----------

chinese | 1 | 50 | 50.00

chinese | 2 | 120 | 60.00

math | 1 | 160 | 80.00

math | 2 | 80 | 80.00

physical | 1 | 160 | 80.00

physical | 2 | 80 | 80.00

total | 0 | 650 | 72.22

(7 行记录)