PostgreSQL的window函數應用整理

時間  2019-11-06
標籤 postgresql window 函數 應用 整理 欄目 Postgre SQL 简体版
原文   原文鏈接
PG在8.4之後版本中添加了一些Window Function功能，下面簡單介紹
    A window function performs a calculation across a set of table rows that are somehow related to the current row. This is comparable to the type of calculation that can be done with an aggregate function. But unlike regular aggregate functions, use of a window function does not cause rows to become grouped into a single output row — the rows retain their separate identities. Behind the scenes, the window function is able to access more than just the current row of the query result.
    Window Functions in SQL is an OLAP functionality that provides ranking, cumulative computation, and partitioning aggregation. Many commercial RDMBS such like Oracle, MS SQL Server and DB2 have implemented part of this specification, while open source RDMBS including PostgreSQL, MySQL and Firebird doesn't yet. To implement this functionality on PostgreSQL not only helps many users move from those RDBMS to PostgreSQL but encourages OLAP applications such as BI (Business Inteligence) to analyze large data set. This specification is defined first in SQL:2003, and improved in SQL:2008
簡言之，聚合函數返回的各個分組的結果，窗口函數則爲每一行返回結果,示例以下：
1.建示例表,初始化數據 
DROP TABLE IF EXISTS empsalary;
CREATE TABLE empsalary(
  depname varchar,
  empno bigint,
  salary int,
  enroll_date date
);
INSERT INTO empsalary VALUES('develop',10, 5200, '2007/08/01');
INSERT INTO empsalary VALUES('sales', 1, 5000, '2006/10/01');
INSERT INTO empsalary VALUES('personnel', 5, 3500, '2007/12/10');
INSERT INTO empsalary VALUES('sales', 4, 4800, '2007/08/08');
INSERT INTO empsalary VALUES('sales', 6, 5500, '2007/01/02');
INSERT INTO empsalary VALUES('personnel', 2, 3900, '2006/12/23');
INSERT INTO empsalary VALUES('develop', 7, 4200, '2008/01/01');
INSERT INTO empsalary VALUES('develop', 9, 4500, '2008/01/01');
INSERT INTO empsalary VALUES('sales', 3, 4800, '2007/08/01');
INSERT INTO empsalary VALUES('develop', 8, 6000, '2006/10/01');
INSERT INTO empsalary VALUES('develop', 11, 5200, '2007/08/15');

postgres=# select * from empsalary ;
  depname  | empno | salary | enroll_date 
-----------+-------+--------+-------------
 develop   |    10 |   5200 | 2007-08-01
 sales     |     1 |   5000 | 2006-10-01
 personnel |     5 |   3500 | 2007-12-10
 sales     |     4 |   4800 | 2007-08-08
 sales     |     6 |   5500 | 2007-01-02
 personnel |     2 |   3900 | 2006-12-23
 develop   |     7 |   4200 | 2008-01-01
 develop   |     9 |   4500 | 2008-01-01
 sales     |     3 |   4800 | 2007-08-01
 develop   |     8 |   6000 | 2006-10-01
 develop   |    11 |   5200 | 2007-08-15
(11 rows)
2.統計示例
a.統計各部門的總薪水，平均薪水和部門的詳細狀況 
postgres=# select sum(salary) OVER (PARTITION BY depname),avg(salary) OVER (PARTITION BY depname),* from empsalary;
  sum  |          avg          |  depname  | empno | salary | enroll_date 
-------+-----------------------+-----------+-------+--------+-------------
 25100 | 5020.0000000000000000 | develop   |    10 |   5200 | 2007-08-01
 25100 | 5020.0000000000000000 | develop   |     7 |   4200 | 2008-01-01
 25100 | 5020.0000000000000000 | develop   |     9 |   4500 | 2008-01-01
 25100 | 5020.0000000000000000 | develop   |     8 |   6000 | 2006-10-01
 25100 | 5020.0000000000000000 | develop   |    11 |   5200 | 2007-08-15
  7400 | 3700.0000000000000000 | personnel |     2 |   3900 | 2006-12-23
  7400 | 3700.0000000000000000 | personnel |     5 |   3500 | 2007-12-10
 20100 | 5025.0000000000000000 | sales     |     3 |   4800 | 2007-08-01
 20100 | 5025.0000000000000000 | sales     |     1 |   5000 | 2006-10-01
 20100 | 5025.0000000000000000 | sales     |     4 |   4800 | 2007-08-08
 20100 | 5025.0000000000000000 | sales     |     6 |   5500 | 2007-01-02
(11 rows)
b.統計人員在所在部門的薪水排名狀況 
postgres=# select rank() OVER (PARTITION BY depname ORDER BY salary),* from empsalary;
 rank |  depname  | empno | salary | enroll_date 
------+-----------+-------+--------+-------------
    1 | develop   |     7 |   4200 | 2008-01-01
    2 | develop   |     9 |   4500 | 2008-01-01
    3 | develop   |    10 |   5200 | 2007-08-01
    3 | develop   |    11 |   5200 | 2007-08-15
    5 | develop   |     8 |   6000 | 2006-10-01
    1 | personnel |     5 |   3500 | 2007-12-10
    2 | personnel |     2 |   3900 | 2006-12-23
    1 | sales     |     4 |   4800 | 2007-08-08
    1 | sales     |     3 |   4800 | 2007-08-01
    3 | sales     |     1 |   5000 | 2006-10-01
    4 | sales     |     6 |   5500 | 2007-01-02
(11 rows)
3.一個有趣的例子 注意使用order by,結果會兩樣 
create table foo(a int,b int) ;
insert into foo values (1,1);
insert into foo values (1,1);
insert into foo values (2,1);
insert into foo values (4,1);
insert into foo values (2,1);
insert into foo values (4,1);
insert into foo values (5,1);
insert into foo values (11,3);
insert into foo values (12,3);
insert into foo values (22,3);
insert into foo values (16,3);
insert into foo values (16,3);
insert into foo values (16,3);

postgres=# select sum(a) over (partition by b), a, b from foo;
 sum | a  | b 
-----+----+---
  19 |  1 | 1
  19 |  1 | 1
  19 |  2 | 1
  19 |  4 | 1
  19 |  2 | 1
  19 |  4 | 1
  19 |  5 | 1
  93 | 11 | 3
  93 | 12 | 3
  93 | 22 | 3
  93 | 16 | 3
  93 | 16 | 3
  93 | 16 | 3
(13 rows)

postgres=# select sum(a) over (partition by b order by a), a, b from foo;
 sum | a  | b 
-----+----+---
   2 |  1 | 1
   2 |  1 | 1
   6 |  2 | 1
   6 |  2 | 1
  14 |  4 | 1
  14 |  4 | 1
  19 |  5 | 1
  11 | 11 | 3
  23 | 12 | 3
  71 | 16 | 3
  71 | 16 | 3
  71 | 16 | 3
  93 | 22 | 3
(13 rows)

postgres=# select a, b, sum(a) over (partition by b order by a ROWS 
postgres(# BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING) from foo;
 a  | b | sum 
----+---+-----
  1 | 1 |  19
  1 | 1 |  19
  2 | 1 |  19
  2 | 1 |  19
  4 | 1 |  19
  4 | 1 |  19
  5 | 1 |  19
 11 | 3 |  93
 12 | 3 |  93
 16 | 3 |  93
 16 | 3 |  93
 16 | 3 |  93
 22 | 3 |  93
(13 rows)
官網中的解釋是： By default, if ORDER BY is supplied then the frame consists of all rows from the start of the partition up through the current row, plus any following rows that are equal to the current row according to the ORDER BY clause. When ORDER BY is omitted the default frame consists of all rows in the partition.
 默認狀況下，帶了order by 參數會從分組的起始值開始一直疊加，直到當前值爲止，當忽略order by 參數則會計算分組中全部值的和。

4.其餘的窗口函數
row_number(): 從當前開始，不間斷,如1，2，3，4，5，6
rank() :從當前開始，會間斷，如1，2，2，4，5，6
dense_rank():從當前開始不間斷，但會重複，如1，2，2，3，4，5
percent_rank()：從當前開始，計算在分組中的比例，如0，0.25，0.25，0.75，1，0，1 從0-1不斷地循環
cume_dist()：當前行的排序除以分組的數量,如分組有4行，則值爲0.25，0.5，0.75，1
ntile(num_buckets integer)：從1到當前值，除以分組的的數量，儘量使分佈平均
lag(value any [, offset integer [, default any ]])：偏移量函數，取滯後值,如lag(column_name,2,0)表示字段偏移量爲2，沒有則用default值代替，這裏是0，不寫默認是null
lead(value any [, offset integer [, default any ]])：偏移量函數，取提早值,類上
first_value(value any)：返回窗口框架中的第一個值
last_value(value any)：返回窗口框架中的最後一個值
nth_value(value any, nth integer)：返回窗口框架中的指定值，如nth_value(salary,2),則表示返回字段salary的第二個窗口函數值

 5.其餘窗口函數示例 
postgres=# select row_number() over (partition by depname order by salary desc),* from empsalary;
 row_number |  depname  | empno | salary | enroll_date 
------------+-----------+-------+--------+-------------
          1 | develop   |     8 |   6000 | 2006-10-01
          2 | develop   |    10 |   5200 | 2007-08-01
          3 | develop   |    11 |   5200 | 2007-08-15
          4 | develop   |     9 |   4500 | 2008-01-01
          5 | develop   |     7 |   4200 | 2008-01-01
          1 | personnel |     2 |   3900 | 2006-12-23
          2 | personnel |     5 |   3500 | 2007-12-10
          1 | sales     |     6 |   5500 | 2007-01-02
          2 | sales     |     1 |   5000 | 2006-10-01
          3 | sales     |     3 |   4800 | 2007-08-01
          4 | sales     |     4 |   4800 | 2007-08-08
(11 rows)

postgres=# select rank() over(partition by depname order by salary desc),* from empsalary;
 rank |  depname  | empno | salary | enroll_date 
------+-----------+-------+--------+-------------
    1 | develop   |     8 |   6000 | 2006-10-01
    2 | develop   |    10 |   5200 | 2007-08-01
    2 | develop   |    11 |   5200 | 2007-08-15
    4 | develop   |     9 |   4500 | 2008-01-01
    5 | develop   |     7 |   4200 | 2008-01-01
    1 | personnel |     2 |   3900 | 2006-12-23
    2 | personnel |     5 |   3500 | 2007-12-10
    1 | sales     |     6 |   5500 | 2007-01-02
    2 | sales     |     1 |   5000 | 2006-10-01
    3 | sales     |     3 |   4800 | 2007-08-01
    3 | sales     |     4 |   4800 | 2007-08-08
(11 rows)


postgres=# select dense_rank() over(partition by depname order by salary desc),* from empsalary;
 dense_rank |  depname  | empno | salary | enroll_date 
------------+-----------+-------+--------+-------------
          1 | develop   |     8 |   6000 | 2006-10-01
          2 | develop   |    10 |   5200 | 2007-08-01
          2 | develop   |    11 |   5200 | 2007-08-15
          3 | develop   |     9 |   4500 | 2008-01-01
          4 | develop   |     7 |   4200 | 2008-01-01
          1 | personnel |     2 |   3900 | 2006-12-23
          2 | personnel |     5 |   3500 | 2007-12-10
          1 | sales     |     6 |   5500 | 2007-01-02
          2 | sales     |     1 |   5000 | 2006-10-01
          3 | sales     |     3 |   4800 | 2007-08-01
          3 | sales     |     4 |   4800 | 2007-08-08
(11 rows)

postgres=# select percent_rank() over(partition by depname order by salary desc),* from empsalary;
   percent_rank    |  depname  | empno | salary | enroll_date 
-------------------+-----------+-------+--------+-------------
                 0 | develop   |     8 |   6000 | 2006-10-01
              0.25 | develop   |    10 |   5200 | 2007-08-01
              0.25 | develop   |    11 |   5200 | 2007-08-15
              0.75 | develop   |     9 |   4500 | 2008-01-01
                 1 | develop   |     7 |   4200 | 2008-01-01
                 0 | personnel |     2 |   3900 | 2006-12-23
                 1 | personnel |     5 |   3500 | 2007-12-10
                 0 | sales     |     6 |   5500 | 2007-01-02
 0.333333333333333 | sales     |     1 |   5000 | 2006-10-01
 0.666666666666667 | sales     |     3 |   4800 | 2007-08-01
 0.666666666666667 | sales     |     4 |   4800 | 2007-08-08
(11 rows)

postgres=# select cume_dist()over(partition by depname order by salary desc),* from empsalary;
 cume_dist |  depname  | empno | salary | enroll_date 
-----------+-----------+-------+--------+-------------
       0.2 | develop   |     8 |   6000 | 2006-10-01
       0.6 | develop   |    10 |   5200 | 2007-08-01
       0.6 | develop   |    11 |   5200 | 2007-08-15
       0.8 | develop   |     9 |   4500 | 2008-01-01
         1 | develop   |     7 |   4200 | 2008-01-01
       0.5 | personnel |     2 |   3900 | 2006-12-23
         1 | personnel |     5 |   3500 | 2007-12-10
      0.25 | sales     |     6 |   5500 | 2007-01-02
       0.5 | sales     |     1 |   5000 | 2006-10-01
         1 | sales     |     3 |   4800 | 2007-08-01
         1 | sales     |     4 |   4800 | 2007-08-08
(11 rows)

postgres=# select ntile(3)over(partition by depname order by salary desc),* from empsalary;
 ntile |  depname  | empno | salary | enroll_date 
-------+-----------+-------+--------+-------------
     1 | develop   |     8 |   6000 | 2006-10-01
     1 | develop   |    10 |   5200 | 2007-08-01
     2 | develop   |    11 |   5200 | 2007-08-15
     2 | develop   |     9 |   4500 | 2008-01-01
     3 | develop   |     7 |   4200 | 2008-01-01
     1 | personnel |     2 |   3900 | 2006-12-23
     2 | personnel |     5 |   3500 | 2007-12-10
     1 | sales     |     6 |   5500 | 2007-01-02
     1 | sales     |     1 |   5000 | 2006-10-01
     2 | sales     |     3 |   4800 | 2007-08-01
     3 | sales     |     4 |   4800 | 2007-08-08
(11 rows)

postgres=# select lag(salary,2,null)over(partition by depname order by salary desc),* from empsalary;
 lag  |  depname  | empno | salary | enroll_date 
------+-----------+-------+--------+-------------
      | develop   |     8 |   6000 | 2006-10-01
      | develop   |    10 |   5200 | 2007-08-01
 6000 | develop   |    11 |   5200 | 2007-08-15
 5200 | develop   |     9 |   4500 | 2008-01-01
 5200 | develop   |     7 |   4200 | 2008-01-01
      | personnel |     2 |   3900 | 2006-12-23
      | personnel |     5 |   3500 | 2007-12-10
      | sales     |     6 |   5500 | 2007-01-02
      | sales     |     1 |   5000 | 2006-10-01
 5500 | sales     |     3 |   4800 | 2007-08-01
 5000 | sales     |     4 |   4800 | 2007-08-08
(11 rows)

postgres=# select first_value(salary)over(partition by depname order by salary desc),* from empsalary;
 first_value |  depname  | empno | salary | enroll_date 
-------------+-----------+-------+--------+-------------
        6000 | develop   |     8 |   6000 | 2006-10-01
        6000 | develop   |    10 |   5200 | 2007-08-01
        6000 | develop   |    11 |   5200 | 2007-08-15
        6000 | develop   |     9 |   4500 | 2008-01-01
        6000 | develop   |     7 |   4200 | 2008-01-01
        3900 | personnel |     2 |   3900 | 2006-12-23
        3900 | personnel |     5 |   3500 | 2007-12-10
        5500 | sales     |     6 |   5500 | 2007-01-02
        5500 | sales     |     1 |   5000 | 2006-10-01
        5500 | sales     |     3 |   4800 | 2007-08-01
        5500 | sales     |     4 |   4800 | 2007-08-08
(11 rows) 

postgres=# select last_value(salary)over(partition by depname order by salary desc),* from empsalary;
 last_value |  depname  | empno | salary | enroll_date 
------------+-----------+-------+--------+-------------
       6000 | develop   |     8 |   6000 | 2006-10-01
       5200 | develop   |    10 |   5200 | 2007-08-01
       5200 | develop   |    11 |   5200 | 2007-08-15
       4500 | develop   |     9 |   4500 | 2008-01-01
       4200 | develop   |     7 |   4200 | 2008-01-01
       3900 | personnel |     2 |   3900 | 2006-12-23
       3500 | personnel |     5 |   3500 | 2007-12-10
       5500 | sales     |     6 |   5500 | 2007-01-02
       5000 | sales     |     1 |   5000 | 2006-10-01
       4800 | sales     |     3 |   4800 | 2007-08-01
       4800 | sales     |     4 |   4800 | 2007-08-08
(11 rows)

postgres=# select last_value(aa.salary)over(partition by aa.depname),* from     
(select depname,empno,salary,enroll_date from empsalary order by depname,salary ) aa;
 last_value |  depname  | empno | salary | enroll_date 
------------+-----------+-------+--------+-------------
       6000 | develop   |     7 |   4200 | 2008-01-01
       6000 | develop   |     9 |   4500 | 2008-01-01
       6000 | develop   |    10 |   5200 | 2007-08-01
       6000 | develop   |    11 |   5200 | 2007-08-15
       6000 | develop   |     8 |   6000 | 2006-10-01
       3900 | personnel |     5 |   3500 | 2007-12-10
       3900 | personnel |     2 |   3900 | 2006-12-23
       5500 | sales     |     4 |   4800 | 2007-08-08
       5500 | sales     |     3 |   4800 | 2007-08-01
       5500 | sales     |     1 |   5000 | 2006-10-01
       5500 | sales     |     6 |   5500 | 2007-01-02
(11 rows)

postgres=# select nth_value(salary,2)over(partition by depname order by salary desc),* from empsalary;
 nth_value |  depname  | empno | salary | enroll_date 
-----------+-----------+-------+--------+-------------
           | develop   |     8 |   6000 | 2006-10-01
      5200 | develop   |    10 |   5200 | 2007-08-01
      5200 | develop   |    11 |   5200 | 2007-08-15
      5200 | develop   |     9 |   4500 | 2008-01-01
      5200 | develop   |     7 |   4200 | 2008-01-01
           | personnel |     2 |   3900 | 2006-12-23
      3500 | personnel |     5 |   3500 | 2007-12-10
           | sales     |     6 |   5500 | 2007-01-02
      5000 | sales     |     1 |   5000 | 2006-10-01
      5000 | sales     |     3 |   4800 | 2007-08-01
      5000 | sales     |     4 |   4800 | 2007-08-08
(11 rows)
當一個查詢涉及多個窗口函數的時候，能夠用別名的辦法來使用，更簡單： 
postgres=# select sum(salary)over w,avg(salary) over w,* from empsalary window w as (partition by depname order by salary desc);
  sum  |          avg          |  depname  | empno | salary | enroll_date 
-------+-----------------------+-----------+-------+--------+-------------
  6000 | 6000.0000000000000000 | develop   |     8 |   6000 | 2006-10-01
 16400 | 5466.6666666666666667 | develop   |    10 |   5200 | 2007-08-01
 16400 | 5466.6666666666666667 | develop   |    11 |   5200 | 2007-08-15
 20900 | 5225.0000000000000000 | develop   |     9 |   4500 | 2008-01-01
 25100 | 5020.0000000000000000 | develop   |     7 |   4200 | 2008-01-01
  3900 | 3900.0000000000000000 | personnel |     2 |   3900 | 2006-12-23
  7400 | 3700.0000000000000000 | personnel |     5 |   3500 | 2007-12-10
  5500 | 5500.0000000000000000 | sales     |     6 |   5500 | 2007-01-02
 10500 | 5250.0000000000000000 | sales     |     1 |   5000 | 2006-10-01
 20100 | 5025.0000000000000000 | sales     |     3 |   4800 | 2007-08-01
 20100 | 5025.0000000000000000 | sales     |     4 |   4800 | 2007-08-08
(11 rows)
這個寫法和下面的是同樣的，不過更簡單
SELECT sum(salary) OVER (PARTITION BY depname ORDER BY salary DESC), avg(salary) OVER (PARTITION BY depname ORDER BY salary DESC),* FROM empsalary;


上面給了兩個last_value的示例，可是第一種寫法是沒有問題的，雖然並不能達到返回窗口最後一個值的效果，並且first_value沒有這種問題的，其實，參考前面的官網提醒，同樣可得出相似的結論：都是order by 惹的禍
官網中的解釋是： By default, if ORDER BY is supplied then the frame consists of all rows from the start of the partition up through the current row, plus any following rows that are equal to the current row according to the ORDER BY clause. When ORDER BY is omitted the default frame consists of all rows in the partition. 
 默認狀況下，帶了order by 參數會從分組的起始值開始一直疊加，直到當前值爲止，當忽略order by 參數則會計算分組中全部值的和。 

感謝joan_he@189.cn的提醒和digoal的解釋。 html

參考文檔：http://umitanuki.net/pgsql/wfv08/design.html sql

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