在 PostgreSQL 中滚动 12 个月总和
Rolling 12 month Sum in PostgreSQL
我需要能够使用 SQL (PostgreSQL) 创建一个 Trailing Twelve Month 报告 - 本质上是一个 window/rolling 12 个月的总和,它总结了当前月份的总数 +每个月的前 11 个月。
我有这个table:
CREATE TABLE order_test(
order_id text,
sale_date date,
delivery_date date,
customer_id text,
vendor_id text,
order_total float);
具有这些值:
insert into order_test
values ('1', '2016-06-01', '2016-06-10', '2', '3', 200.10),
('2', '2016-06-02', '2016-06-11', '2', '4', 150.50),
('3', '2016-07-02', '2016-07-11', '5', '4', 100.50),
('4', '2016-07-02', '2016-07-11', '1', '4', 150.50),
('5', '2016-07-02', '2016-07-11', '1', '4', 150.50),
('6', '2016-08-02', '2016-08-11', '6', '4', 300.50),
('7', '2016-08-02', '2016-08-11', '6', '4', 150.50),
('8', '2016-09-02', '2016-09-11', '1', '4', 150.50),
('9', '2016-10-02', '2016-10-11', '1', '4', 150.50),
('10', '2016-11-02', '2016-11-11', '1', '4', 150.50),
('11', '2016-12-02', '2016-12-11', '6', '4', 150.50),
('12', '2017-01-02', '2017-01-11', '7', '4', 150.50),
('13', '2017-01-02', '2017-01-11', '1', '4', 150.50),
('14', '2017-01-02', '2017-01-11', '1', '4', 100.50),
('15', '2017-02-02', '2017-02-11', '1', '4', 150.50),
('16', '2017-02-02', '2017-02-11', '1', '4', 150.50),
('17', '2017-03-02', '2017-03-11', '2', '4', 150.50),
('18', '2017-03-02', '2017-03-11', '2', '4', 150.50),
('19', '2017-04-02', '2017-04-11', '6', '4', 120.50),
('20', '2017-05-02', '2017-05-11', '1', '4', 150.50),
('21', '2017-06-02', '2017-06-11', '2', '4', 150.50),
('22', '2017-06-02', '2017-06-11', '1', '4', 130.50),
('23', '2017-07-02', '2017-07-11', '1', '4', 150.50),
('24', '2017-07-02', '2017-07-11', '5', '4', 200.50),
('25', '2017-08-02', '2017-08-11', '1', '4', 150.50),
('26', '2017-09-02', '2017-09-11', '2', '4', 100.50),
('27', '2017-09-02', '2017-10-11', '1', '4', 150.50);
这些是个人销售。对于每个月,我需要前 11 个月 + 该月的总计(销售月)。
我试过这样的 window 计算:
select date_trunc('month', sale_date) as sale_month,
sum(order_total) over w as total_sales
from order_test
where (delivery_date < current_date) and
(sale_date >= (date_trunc('month', current_date) - interval '1 year'))
window w as (Partition by date_trunc('month', sale_date)
order by sale_date
rows between current row and 11 following)
但它给了我这个:
sale_month total_sales
1 01.09.2016 00:00:00 150,5
2 01.10.2016 00:00:00 150,5
3 01.11.2016 00:00:00 150,5
4 01.12.2016 00:00:00 150,5
5 01.01.2017 00:00:00 401,5
6 01.01.2017 00:00:00 251
7 01.01.2017 00:00:00 100,5
8 01.02.2017 00:00:00 301
9 01.02.2017 00:00:00 150,5
10 01.03.2017 00:00:00 301
11 01.03.2017 00:00:00 150,5
12 01.04.2017 00:00:00 120,5
13 01.05.2017 00:00:00 150,5
14 01.06.2017 00:00:00 281
15 01.06.2017 00:00:00 130,5
16 01.07.2017 00:00:00 351
17 01.07.2017 00:00:00 200,5
18 01.08.2017 00:00:00 150,5
19 01.09.2017 00:00:00 100,5
每个月应该只有一行。
如果我没理解错的话,您希望所有月份都有最近 11 个月的累积数据。但是前 11 行不会有前面的 11 个条目来计算滚动总和。但是您提到所有月份都应该有一个累计总数。
所以我相信你正在寻找这样的东西。
with x as (
select date_trunc('month', sale_date) as sale_month,sum(order_total) as monthly_order_total from order_test
group by 1 order by 1 asc)
select sale_month, monthly_order_total,
sum(monthly_order_total ) over (order by sale_month asc rows between 11 preceding and current row)
from x
在派生的内部查询 table 中,您需要使用 date_trunc
和 group by
结果列将 Sale_Date
列截断为 month
精度以获得Month_total
sales 然后在外部查询中,对按 Sale_Month
排序的 month_total
销售数据使用 cumulative window sum
函数以获得您想要的结果,如下所示。
SELECT sale_Month
,month_total
,sum(month_total) OVER (
ORDER BY sale_Month ASC rows BETWEEN 11 preceding
AND CURRENT row
) AS Sum_Series
FROM (
SELECT date_trunc('month', Sale_Date) AS Sale_Month
,sum(Order_Total) AS Month_Total
FROM order_test
GROUP BY 1
ORDER BY 1
) t
请注意,AND CURRENT row
是可选的,因为累积 window 函数默认包含 current
行,因此查询可以重写如下。
SELECT sale_Month
,month_total
,sum(month_total) OVER (
ORDER BY sale_Month ASC rows 11 preceding
) AS Sum_Series
FROM (
SELECT date_trunc('month', Sale_Date) AS Sale_Month
,sum(Order_Total) AS Month_Total
FROM order_test
GROUP BY 1
ORDER BY 1
) t
Result:
sale_month month_total sum_series
----------------------------------------------
2016-06-01T00:00:00Z 350.6 350.6
2016-07-01T00:00:00Z 401.5 752.1
2016-08-01T00:00:00Z 451 1203.1
2016-09-01T00:00:00Z 150.5 1353.6
2016-10-01T00:00:00Z 150.5 1504.1
2016-11-01T00:00:00Z 150.5 1654.6
2016-12-01T00:00:00Z 150.5 1805.1
2017-01-01T00:00:00Z 401.5 2206.6
2017-02-01T00:00:00Z 301 2507.6
2017-03-01T00:00:00Z 301 2808.6
2017-04-01T00:00:00Z 120.5 2929.1
2017-05-01T00:00:00Z 150.5 3079.6
2017-06-01T00:00:00Z 281 3010
2017-07-01T00:00:00Z 351 2959.5
2017-08-01T00:00:00Z 150.5 2659
2017-09-01T00:00:00Z 251 2759.5
你可以查看演示here
我需要能够使用 SQL (PostgreSQL) 创建一个 Trailing Twelve Month 报告 - 本质上是一个 window/rolling 12 个月的总和,它总结了当前月份的总数 +每个月的前 11 个月。
我有这个table:
CREATE TABLE order_test(
order_id text,
sale_date date,
delivery_date date,
customer_id text,
vendor_id text,
order_total float);
具有这些值:
insert into order_test
values ('1', '2016-06-01', '2016-06-10', '2', '3', 200.10),
('2', '2016-06-02', '2016-06-11', '2', '4', 150.50),
('3', '2016-07-02', '2016-07-11', '5', '4', 100.50),
('4', '2016-07-02', '2016-07-11', '1', '4', 150.50),
('5', '2016-07-02', '2016-07-11', '1', '4', 150.50),
('6', '2016-08-02', '2016-08-11', '6', '4', 300.50),
('7', '2016-08-02', '2016-08-11', '6', '4', 150.50),
('8', '2016-09-02', '2016-09-11', '1', '4', 150.50),
('9', '2016-10-02', '2016-10-11', '1', '4', 150.50),
('10', '2016-11-02', '2016-11-11', '1', '4', 150.50),
('11', '2016-12-02', '2016-12-11', '6', '4', 150.50),
('12', '2017-01-02', '2017-01-11', '7', '4', 150.50),
('13', '2017-01-02', '2017-01-11', '1', '4', 150.50),
('14', '2017-01-02', '2017-01-11', '1', '4', 100.50),
('15', '2017-02-02', '2017-02-11', '1', '4', 150.50),
('16', '2017-02-02', '2017-02-11', '1', '4', 150.50),
('17', '2017-03-02', '2017-03-11', '2', '4', 150.50),
('18', '2017-03-02', '2017-03-11', '2', '4', 150.50),
('19', '2017-04-02', '2017-04-11', '6', '4', 120.50),
('20', '2017-05-02', '2017-05-11', '1', '4', 150.50),
('21', '2017-06-02', '2017-06-11', '2', '4', 150.50),
('22', '2017-06-02', '2017-06-11', '1', '4', 130.50),
('23', '2017-07-02', '2017-07-11', '1', '4', 150.50),
('24', '2017-07-02', '2017-07-11', '5', '4', 200.50),
('25', '2017-08-02', '2017-08-11', '1', '4', 150.50),
('26', '2017-09-02', '2017-09-11', '2', '4', 100.50),
('27', '2017-09-02', '2017-10-11', '1', '4', 150.50);
这些是个人销售。对于每个月,我需要前 11 个月 + 该月的总计(销售月)。
我试过这样的 window 计算:
select date_trunc('month', sale_date) as sale_month,
sum(order_total) over w as total_sales
from order_test
where (delivery_date < current_date) and
(sale_date >= (date_trunc('month', current_date) - interval '1 year'))
window w as (Partition by date_trunc('month', sale_date)
order by sale_date
rows between current row and 11 following)
但它给了我这个:
sale_month total_sales
1 01.09.2016 00:00:00 150,5
2 01.10.2016 00:00:00 150,5
3 01.11.2016 00:00:00 150,5
4 01.12.2016 00:00:00 150,5
5 01.01.2017 00:00:00 401,5
6 01.01.2017 00:00:00 251
7 01.01.2017 00:00:00 100,5
8 01.02.2017 00:00:00 301
9 01.02.2017 00:00:00 150,5
10 01.03.2017 00:00:00 301
11 01.03.2017 00:00:00 150,5
12 01.04.2017 00:00:00 120,5
13 01.05.2017 00:00:00 150,5
14 01.06.2017 00:00:00 281
15 01.06.2017 00:00:00 130,5
16 01.07.2017 00:00:00 351
17 01.07.2017 00:00:00 200,5
18 01.08.2017 00:00:00 150,5
19 01.09.2017 00:00:00 100,5
每个月应该只有一行。
如果我没理解错的话,您希望所有月份都有最近 11 个月的累积数据。但是前 11 行不会有前面的 11 个条目来计算滚动总和。但是您提到所有月份都应该有一个累计总数。 所以我相信你正在寻找这样的东西。
with x as (
select date_trunc('month', sale_date) as sale_month,sum(order_total) as monthly_order_total from order_test
group by 1 order by 1 asc)
select sale_month, monthly_order_total,
sum(monthly_order_total ) over (order by sale_month asc rows between 11 preceding and current row)
from x
在派生的内部查询 table 中,您需要使用 date_trunc
和 group by
结果列将 Sale_Date
列截断为 month
精度以获得Month_total
sales 然后在外部查询中,对按 Sale_Month
排序的 month_total
销售数据使用 cumulative window sum
函数以获得您想要的结果,如下所示。
SELECT sale_Month
,month_total
,sum(month_total) OVER (
ORDER BY sale_Month ASC rows BETWEEN 11 preceding
AND CURRENT row
) AS Sum_Series
FROM (
SELECT date_trunc('month', Sale_Date) AS Sale_Month
,sum(Order_Total) AS Month_Total
FROM order_test
GROUP BY 1
ORDER BY 1
) t
请注意,AND CURRENT row
是可选的,因为累积 window 函数默认包含 current
行,因此查询可以重写如下。
SELECT sale_Month
,month_total
,sum(month_total) OVER (
ORDER BY sale_Month ASC rows 11 preceding
) AS Sum_Series
FROM (
SELECT date_trunc('month', Sale_Date) AS Sale_Month
,sum(Order_Total) AS Month_Total
FROM order_test
GROUP BY 1
ORDER BY 1
) t
Result:
sale_month month_total sum_series
----------------------------------------------
2016-06-01T00:00:00Z 350.6 350.6
2016-07-01T00:00:00Z 401.5 752.1
2016-08-01T00:00:00Z 451 1203.1
2016-09-01T00:00:00Z 150.5 1353.6
2016-10-01T00:00:00Z 150.5 1504.1
2016-11-01T00:00:00Z 150.5 1654.6
2016-12-01T00:00:00Z 150.5 1805.1
2017-01-01T00:00:00Z 401.5 2206.6
2017-02-01T00:00:00Z 301 2507.6
2017-03-01T00:00:00Z 301 2808.6
2017-04-01T00:00:00Z 120.5 2929.1
2017-05-01T00:00:00Z 150.5 3079.6
2017-06-01T00:00:00Z 281 3010
2017-07-01T00:00:00Z 351 2959.5
2017-08-01T00:00:00Z 150.5 2659
2017-09-01T00:00:00Z 251 2759.5
你可以查看演示here