Question

I have a result set that I obtain from the join between three tables using:

SELECT X.*, Y.Name FROM `A` AS X
INNER JOIN `B` AS Y
INNER JOIN `C` AS Z
ON X.id=Y.id AND X.categoryID=Z.categoryID
WHERE X.userID_FK=%d AND X.listID_FK=%d 
ORDER BY Z.categoryRank ASC

I have a fourth table ‘D’ which contains:

-------------------------------
  id_FK    userID_FK    vote
-------------------------------

Here (id_FK, userID_FK) pair is a PK.

Each X.id returned by the first query could have multiple entries in the D table. Normally, for each returned row, in order to count votes per id, I’d write a query like:

SELECT SUM(vote) FROM D WHERE `id`=%d

I am wondering if I could optimize these two queries into a single query as the current scheme results in O(n) execution time. n being the number of results returned by the first query.

Answer 1

You can simply do it like this

SELECT
X.*,
Y.Name,
(SELECT
   SUM(vote)
   FROM D
   WHERE `id` = X.id) as Count
FROM `A` AS X
INNER JOIN `B` AS Y
INNER JOIN `C` AS Z
ON X.id = Y.id
  AND X.categoryID = Z.categoryID
WHERE X.userID_FK =  % d
AND X.listID_FK =  % d
ORDER BY Z.categoryRank ASC