SQL aggregate quarterly records - sql

Question

I'm trying to aggregate quarterly records that belong to unique customer ids. I would then like to filter out those by $amount spent on X.
below is what I've coded:
select year, count(*), sum($spentX), customerid
from table A
where year = 2017
group by year, customerid
having sum($spentX)<=1000
Is this correct? Also, how do I sum the results to give me 2017 total, this query lists all customerids so I have to aggregate in another software.
2nd question:
How do I use the above when I join two tables?
thank you so much in advance

Answer 1

Your code looks correct. The way you have it set up your output would look something like the below. It is already filtered down to 2017 and grouped by the year and customer.
year | count(*) | sum($spentX) | customerid
2017 | 5 | 500.00 | 56
2017 | 8 | 800.00 | 43
2017 | 3 | 300.00 | 85
2017 | 2 | 200.00 | 56
2017 | 5 | 500.00 | 25
If you want to get a sum total for all customers who spent less than or equal to $1000 you would need put the entire thing in a subquery and sum it again
SELECT SUB.YEAR, SUM(SUB.TOTAL_COUNT), SUM(SUB.TOTAL_SPENT)
FROM (
SELECT YEAR, COUNT(*) AS TOTAL_COUNT, SUM($SPENTX) AS TOTAL_SPENT, CUSTOMERID
FROM TABLE A
WHERE YEAR = 2017
GROUP BY YEAR, CUSTOMERID
HAVING SUM($SPENTX)<=1000
) SUB
GROUP BY SUB.YEAR
OUTPUT:
YEAR | SUM(SUB.TOTAL_COUNT) | SUM(SUB.TOTAL_SPENT)
2017 | 23 | 2300.00
If you wanted to join that to another table say one with customer information it would look like this:
SELECT SUB.* , C.CUSTOMER_NAME
FROM (
SELECT YEAR, COUNT(*) AS TOTAL_COUNT, SUM($SPENTX) AS TOTAL_SPENT, CUSTOMERID
FROM TABLE A
WHERE YEAR = 2017
GROUP BY YEAR, CUSTOMERID
HAVING SUM($SPENTX)<=1000
) SUB
INNER JOIN TABLE_CUSTOMERS C ON C.CUSTOMERID = SUB.CUSTOMERID
The output for this query would look something like this:
YEAR | TOTAL_COUNT | TOTAL_SPENT | customerid | CUSTOMER_NAME
2017 | 5 | 500.00 | 56 | LARRY
2017 | 8 | 800.00 | 43 | MARGE
2017 | 3 | 300.00 | 85 | JOHN
2017 | 2 | 200.00 | 56 | RICK
2017 | 5 | 500.00 | 25 | SAM