Two left joins gives me untrue data(double data?) with MySQL

Question

This is my query:

SELECT `products`.*, SUM(orders.total_count) AS revenue,
    SUM(orders.quantity) AS qty, ROUND(AVG(product_reviews.stars)) as avg_stars 
FROM          


        

Answer 1

One approach to avoid that problem is to use correlated subquery in the SELECT list, rather than a left join.

SELECT p.*
     , SUM(o.total_count) AS revenue
     , SUM(o.quantity) AS qty
     , ( SELECT ROUND(AVG(r.stars))
           FROM `product_reviews` r
          WHERE r.product_id = p.id 
       ) AS avg_stars
  FROM `products` p
  LEFT
  JOIN `orders` o
    ON o.product_id = p.id
   AND o.status IN ('delivered','new')
 GROUP BY p.id
 ORDER BY p.id DESC
 LIMIT 10
 OFFSET 0

This isn't the only approach, and it's not necessarily the best approach, especially with large sets But given that the subquery will run a maximum of 10 times (given the LIMIT clause), performance should be reasonable (given an appropriate index on product_reviews(product_id,stars).

If you were returning all product ids, or a significant percentage of them, then using an inline view might give better performance (avoiding the nested loops execution of the correlated subquery in the select list)

SELECT p.*
     , SUM(o.total_count) AS revenue
     , SUM(o.quantity) AS qty
     , s.avg_stars
  FROM `products` p
  LEFT
  JOIN `orders` o
    ON o.product_id = p.id
   AND o.status IN ('delivered','new')
  LEFT
  JOIN ( SELECT ROUND(AVG(r.stars)) AS avg_stars
              , r.product_id
           FROM `product_reviews` r
          GROUP BY r.product_id 
       ) s
    ON s.product_id = p.id
 GROUP BY p.id
 ORDER BY p.id DESC
 LIMIT 10
 OFFSET 0

---

Just to be clear: the issue with the original query is that every order for a product is getting matched to every review for the product.

I apologize if my use of the term "semi-cartesian" was misleading or confusing.

The idea that I meant to convey by that was that you had two distinct sets (the set of orders for a product, and the set of reviews for a product), and that your query was generating a "cross product" of those two distinct sets, basically "matching" every order to every review (for a particular product).

For example, given three rows in reviews for product_id 101, and two rows in orders for product_id 101, e.g.:

REVIEWS
pid  stars text
---  ----- --------------
101  4.5   woo hoo perfect
101  3     ehh
101  1     totally sucked


ORDERS
pid  date   qty 
---  -----  ---
101  1/13   100
101  1/22   7

Your original query is essentially forming a result set with six rows in it, each row from order being matched to all three rows from reviews:

id   date   qty   stars text
---  ----   ----  ----  ------------
101  1/13   100   4.5   woo hoo perfect
101  1/13   100   3     ehh
101  1/13   100   1     totally sucked
101  1/22   7     4.5   woo hoo perfect
101  1/22   7     3     ehh
101  1/22   7     1     totally sucked

Then, when the SUM aggregate on qty gets applied, the values returned are way bigger than you expect.