I have this membertype table:
| member_id | member_name |
|-----------|-------------|
| 901 | Liz |
| 902 | Margaret |
| 903 | Bob |
and this revenue table:
| GIS_ID | Member_ID | Total_Revenue | Total_Discount | Number_Transaction |
|--------|-----------|---------------|----------------|--------------------|
| 1001 | 901 | 24,290,288 | 12,894,668 | 266,534 |
| 1001 | 902 | 522,922 | 252,436 | 3,963 |
| 1001 | 903 | 1,581,487 | 847,775 | 19,949 |
| 1002 | 901 | 475,306,161 | 261,595,973 | 4,548,597 |
| 1002 | 902 | 7,194,315 | 3,543,723 | 92,303 |
| 1002 | 903 | 12,293,012 | 3,830,069 | 65,159 |
| 1003 | 901 | 186,170 | 67,250 | 992 |
| 1003 | 902 | 711,765 | 257,145 | 6,195 |
| 1003 | 903 | 109,095 | 37,031 | 1,238 |
| 1004 | 901 | 525,795 | 212,636 | 4,107 |
| 1004 | 902 | 3,545,303 | 1,844,247 | 39,762 |
| 1004 | 903 | 5,153,924 | 1,881,473 | 33,497 |
| 1005 | 901 | 71,538 | 38,579 | 916 |
I want to select which member has the minimum sum value of total discount and its corresponding total discount value. This is what I got (total discount) if I just query their sum value of total discount.
SELECT SUM(revenue.total_discount) as 'Total Discount', membertype.member_id
FROM revenue
INNER JOIN membertype on membertype.member_id = revenue.member_id
GROUP by membertype.member_id;
| Total Discount | member_id |
|----------------|-----------|
| 274809106 | 901 |
| 5897551 | 902 |
| 6596348 | 903 |
I want the total discount data for member 902 to be selected (has the minimum sum value of total discount). I’ve tried this query:
SELECT MIN(SUM(revenue.total_discount)) as 'Total Discount', membertype.member_id
FROM revenue
INNER JOIN membertype on membertype.member_id = revenue.member_id;
but this produces an error:
#1111 - Invalid use of group function
What query should I use to solve this problem?
2
Answers
Would something like this work for you or do you exclusively want to achieve this in one main query? Wrapping the query shouldn’t matter a lot.
You can use analytic function RANK() in order to resolve the task and you can try the following SQL query:
dbfiddle