问题描述
我有以下transactions表：
customer_id purchase_date product category department quantity store_id
1 2020-10-01 Kit Kat Candy Food 2 store_A
1 2020-10-01 Snickers Candy Food 1 store_A
1 2020-10-01 Snickers Candy Food 1 store_A
2 2020-10-01 Snickers Candy Food 2 store_A
2 2020-10-01 Baguette Bread Food 5 store_A
2 2020-10-01 iPhone Cell phones Electronics 2 store_A
3 2020-10-01 Sony PS5 Games Electronics 1 store_A
我想计算购买的平均产品数量（对于表中的每个product）。我还希望通过分别考虑同一category或department中的所有产品来计算每个category和每个department的平均值。应注意划分唯一客户，并且产品quantity大于0（数量为0表示退款，因此不予考虑）。
基本上，输出表如下：
...其中store_id和average_level_type是分区列。
有没有一种方法可以一次通过交易表来实现这一目标？还是需要将我的方法分解为多个步骤？
谢谢！
解决方法
如何按以下方式使用“全部联盟”-
Select store_id,'product' as average_level_type,product as id,sum(quantity) as total_quantity,Count(distinct customer_id) as unique_customer_count,sum(quantity)/count(distinct customer_id) as average
from transactions
where quantity > 0
group by store_id,product
Union all
Select store_id,'category' as average_level_type,category as id,category
Union all
Select store_id,'department' as average_level_type,department as id,department;
如果要避免在这种情况下使用全部并集，可以使用诸如rollup（）或通过对sets（）进行分组来实现相同的目的，但是要获得准确格式的输出，查询会有些复杂您在问题中所显示的。
编辑：以下是如何使用分组集获得相同输出的方法-
Select store_id,case when G_ID = 3 then 'product'
when G_ID = 5 then 'category'
when G_ID = 6 then 'department' end As average_level_type,case when G_ID = 3 then product
when G_ID = 5 then category
when G_ID = 6 then department end As id,total_quantity,unique_customer_count,average
from
(select store_id,product,category,department,sum(quantity)/count(distinct customer_id) as average,GROUPING__ID As G_ID
from transactions
group by store_id,department
grouping sets((store_id,product),(store_id,category),department))
) Tab
order by 2
;