Question

Let’s say I have the following tables:

TAGS

id: integer
name: string

POSTS

id: integer
body: text

TAGGINGS

id: integer
tag_id: integer
post_id: integer

How would I go about writing a query that select all posts that are tagged with ALL of the following tags (name attribute of tags table): "Cheese", "Wine", "Paris", "Frace", "City", "Scenic", "Art"

See also: Sql query to find things with most specified tags (note: similar, but not a duplicate!)

Answer 1

Using IN:

SELECT p.*
  FROM POSTS p
 WHERE p.id IN (SELECT tg.post_id
                  FROM TAGGINGS tg
                  JOIN TAGS t ON t.id = tg.tag_id
                 WHERE t.name IN ('Cheese','Wine','Paris','Frace','City','Scenic','Art')
              GROUP BY tg.post_id
                HAVING COUNT(DISTINCT t.name) = 7)

Using a JOIN

SELECT p.*
  FROM POSTS p
  JOIN (SELECT tg.post_id
          FROM TAGGINGS tg
          JOIN TAGS t ON t.id = tg.tag_id
         WHERE t.name IN ('Cheese','Wine','Paris','Frace','City','Scenic','Art')
      GROUP BY tg.post_id
        HAVING COUNT(DISTINCT t.name) = 7) x ON x.post_id = p.id

Using EXISTS

SELECT p.*
  FROM POSTS p
 WHERE EXISTS (SELECT NULL
                 FROM TAGGINGS tg
                 JOIN TAGS t ON t.id = tg.tag_id
                WHERE t.name IN ('Cheese','Wine','Paris','Frace','City','Scenic','Art')
                  AND tg.post_id = p.id
             GROUP BY tg.post_id
               HAVING COUNT(DISTINCT t.name) = 7)

Explanation

The crux of things is that the COUNT(DISTINCT t.name) needs to match the number of tag names to ensure that all those tags are related to the post. Without the DISTINCT, there’s a risk that duplicates of one of the names could return a count of 7–so you’d have a false positive.

Performance

Most will tell you the JOIN is optimal, but JOINs also risk duplicating rows in the resultset. EXISTS would be my next choice–no duplicate risk, and generally faster execution but checking the explain plan will ultimately tell you what’s best based on your setup and data.