MySQL self join to get past averages - mysql

Question

I am trying to find an average of past records in the database based on a specific time frame (between 9 and 3 months ago) if there is no value recorded for a recent sale. the reason for this is recent sales on our website sometimes do not immediately collect commissions so i am needing to go back to historic records to find out what a commission rate estimate might be.
Commission rate is calculated as:
total_commission / gross_sales
It is only necessary to find out what an estimate would be if a recent sale has no "total_commission" recorded
here is what i have tried so far but i think this is wrong:
SELECT
cs.*
,SUM(cs2.gross_sales)
,SUM(cs2.total_commission)
FROM
(SELECT
sale_id
, date
, customer_code
, customer_country
, gross_sales
, total_commission
FROM customer_sale cs ) cs
LEFT JOIN customer_sale cs2
ON cs2.customer_code = cs.customer_code
AND cs2.customer_country = cs.customer_country
AND cs2.date > cs.date - interval 9 month
AND cs2.date < cs.date - interval 3 month
GROUP BY cs.sale_id
so that data would be structured as follows:
sale_id date customer_code customer_country gross_sales total_commission
1 2013-12-01 cust1 united states 10000 1500
2 2013-12-01 cust2 france 20000 3000
3 2013-12-01 cust3 united states 15000 2250
4 2013-12-01 cust4 france 14000 2100
5 2013-12-01 cust5 united states 13000 1950
6 2013-12-01 cust6 france 12000 1800
7 2014-04-02 cust1 united states 10000
8 2014-04-02 cust2 france 20000
9 2014-04-02 cust3 united states 15000
10 2014-04-02 cust4 france 14000
11 2014-04-02 cust5 united states 13000
12 2014-04-02 cust6 france 12000
so I would need to output results from the query similar to this: (based on sales between 9 and 3 months ago from the same customer_code in the same customer_country)
sale_id date customer_code customer_country gross_sales total_commission gross_sales_past total_commission_past
1 2013-12-01 cust1 united states 10000 1500
2 2013-12-01 cust2 france 20000 3000
3 2013-12-01 cust3 united states 15000 2250
4 2013-12-01 cust4 france 14000 2100
5 2013-12-01 cust5 united states 13000 1950
6 2013-12-01 cust6 france 12000 1800
7 2014-04-02 cust1 united states 10000 10000 1500
8 2014-04-02 cust2 france 20000 20000 3000
9 2014-04-02 cust3 united states 15000 15000 2250
10 2014-04-02 cust4 france 14000 14000 2100
11 2014-04-02 cust5 united states 13000 13000 1950
12 2014-04-02 cust6 france 12000 12000 1800

Answer 1

Your query looks mostly right, but I think your outer query needs to be GROUP BY cs.sale_id (assuming that sale_id is unique in the customer_sale table, and assuming that the date column is datatype DATE, DATETIME, or TIMESTAMP).
And I think you want to include a join predicate so that you match only match "past" rows to those rows where you don't have a total commission, e.g.
AND cs.total_commission IS NULL
And I don't think you really need an inline view.
Here's what I came up with:
SELECT cs.sale_id
, cs.date
, cs.customer_code
, cs.customer_country
, cs.gross_sales
, cs.total_commission
, SUM(ps.gross_sales) AS gross_sales_past
, SUM(ps.total_commission) AS total_commission_past
FROM customer_sale cs
LEFT
JOIN customer_sale ps
ON ps.customer_code = cs.customer_code
AND ps.customer_country = cs.customer_country
AND ps.date > cs.date - INTERVAL 9 MONTH
AND ps.date < cs.date - INTERVAL 3 MONTH
AND cs.total_commission IS NULL
GROUP
BY cs.sale_id
Appropriate indexes will likely improve performance of the query. Likely, the EXPLAIN output will show "Using temporary; Using filesort", and that can be expensive for large sets.
MySQL will likely be able to make use of a covering index for the JOIN:
... ON customer_sale (customer_code,customer_country,date,gross_sales,total_commission).