Question

Imagine the following tables:

create table boxes( id int, name text, …);

create table thingsinboxes( id int, box_id int, thing enum(‘apple,’banana’,’orange’);

And the tables look like:

 Boxes: id | name 1  | orangesOnly 2  | orangesOnly2 3  | orangesBananas 4  | misc  thingsinboxes: id | box_id | thing 1  |  1     | orange 2  |  1     | orange 3  |  2     | orange 4  |  3     | orange 5  |  3     | banana 6  |  4     | orange 7  |  4     | apple 8  |  4     | banana 

How do I select the boxes that contain at least one orange and nothing that isn’t an orange?

How does this scale, assuming I have several hundred thousand boxes and possibly a million things in boxes?

I’d like to keep this all in SQL if possible, rather than post-processing the result set with a script.

I’m using both postgres and mysql, so subqueries are probably bad, given that mysql doesn’t optimize subqueries (pre version 6, anyway).

Answer 1

SELECT b.* FROM boxes b JOIN thingsinboxes t ON (b.id = t.box_id) GROUP BY b.id HAVING COUNT(DISTINCT t.thing) = 1 AND SUM(t.thing = 'orange') > 0; 

---

Here’s another solution that does not use GROUP BY:

SELECT DISTINCT b.* FROM boxes b   JOIN thingsinboxes t1      ON (b.id = t1.box_id AND t1.thing = 'orange')   LEFT OUTER JOIN thingsinboxes t2      ON (b.id = t2.box_id AND t2.thing != 'orange') WHERE t2.box_id IS NULL; 

As always, before you make conclusions about the scalability or performance of a query, you have to try it with a realistic data set, and measure the performance.