在postgresql中移动平均值

发布时间：2020-12-13 16:27:33 所属栏目：百科来源：网络整理

导读：我的 Postgresql 9.1数据库中有以下表格： select * from ro;date | shop_id | amount -----------+----------+--------2013-02-07 | 1001 | 32013-01-31 | 1001 | 22013-01-24 | 1001 | 12013-01-17 | 1001 | 52013-02-10 | 1001 | 102013-02-03 | 1001 | 4

我的 Postgresql 9.1数据库中有以下表格：

select * from ro;
date       |  shop_id | amount 
-----------+----------+--------
2013-02-07 |     1001 |      3
2013-01-31 |     1001 |      2
2013-01-24 |     1001 |      1
2013-01-17 |     1001 |      5
2013-02-10 |     1001 |     10
2013-02-03 |     1001 |      4
2012-12-27 |     1001 |      6
2012-12-20 |     1001 |      8
2012-12-13 |     1001 |      4
2012-12-06 |     1001 |      3
2012-10-29 |     1001 |      3

我试图获得一个移动平均数据,比较最近3个星期四的数据,而不包括当前的星期四.这是我的查询：

select date,shop_id,amount,extract(dow from date),avg(amount) OVER (PARTITION BY extract(dow from date) ORDER BY date DESC
                      ROWS BETWEEN 0 PRECEDING AND 2 FOLLOWING)                          
from ro
where extract(dow from date) = 4

这是给出的结果

date       |  shop_id | amount | date_part |        avg         
-----------+----------+--------+-----------+--------------------
2013-02-07 |     1001 |      3 |         4 | 2.0000000000000000
2013-01-31 |     1001 |      2 |         4 | 2.6666666666666667
2013-01-24 |     1001 |      1 |         4 | 4.0000000000000000
2013-01-17 |     1001 |      5 |         4 | 6.3333333333333333
2012-12-27 |     1001 |      6 |         4 | 6.0000000000000000
2012-12-20 |     1001 |      8 |         4 | 5.0000000000000000
2012-12-13 |     1001 |      4 |         4 | 3.5000000000000000
2012-12-06 |     1001 |      3 |         4 | 3.0000000000000000

我预计

date       |  shop_id | amount | date_part |        avg         
-----------+----------+--------+-----------+--------------------
2013-02-07 |     1001 |      3 |         4 | 2.6666666666666667
2013-01-31 |     1001 |      2 |         4 | 4.0000000000000000
2013-01-24 |     1001 |      1 |         4 | 6.3333333333333333
2013-01-17 |     1001 |      5 |         4 | 6.0000000000000000
2012-12-27 |     1001 |      6 |         4 | 5.0000000000000000
2012-12-20 |     1001 |      8 |         4 |
2012-12-13 |     1001 |      4 |         4 |
2012-12-06 |     1001 |      3 |         4 |

SQL Fiddle

select
    "date",case when
        row_number() over (order by date) > 3
        then
            avg(amount) OVER (
                ORDER BY date DESC
                ROWS BETWEEN 1 following AND 3 FOLLOWING
            )
        else null end
from (
    select *
    from ro
    where extract(dow from date) = 4
) s

OP的查询是什么问题是帧规范：

ROWS BETWEEN 0 PRECEDING AND 2 FOLLOWING

除此之外,我的查询避免了在应用昂贵的窗口功能之前过滤星期四不必要的计算.

如果有必要通过shop_id进行分区,那么显然可以通过shop_id将分区添加到这两个函数avg和row_number.

（编辑：李大同）

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