Question

I’m trying to optimize SQL queries in Akonadi and came across the following problem that is apparently not easy to solve with SQL, at least for me:

Assume the following table structure (should work in SQLite, PostgreSQL, MySQL):

CREATE TABLE a (
  a_id INT PRIMARY KEY
);

INSERT INTO a (a_id) VALUES (1), (2), (3), (4);

CREATE TABLE b (
  b_id INT PRIMARY KEY,
  a_id INT,
  name VARCHAR(255) NOT NULL
);

INSERT INTO b (b_id, a_id, name)
       VALUES (1, 1, 'foo'), (2, 1, 'bar'), (3, 1, 'asdf'),
              (4, 2, 'foo'), (5, 2, 'bar'), (6, 3, 'foo');

Now my problem is to find entries in a that are missing name entries in table b. E.g. I need to make sure each entry in a has at least the name entries "foo" and "bar" in table b. Hence the query should return something similar to:

a_id = 3 is missing name "bar"
a_id = 4 is missing name "foo" and "bar"

Since both tables are potentially huge in Akonadi, performance is of utmost importance.

One solution in MySQL would be:

SELECT a.a_id,
       CONCAT('|', GROUP_CONCAT(name ORDER BY NAME ASC SEPARATOR '|'), '|') as names
  FROM a
  LEFT JOIN b USING( a_id )
  GROUP BY a.a_id
  HAVING names IS NULL OR names NOT LIKE '%|bar|foo|%';

I have yet to measure the performance tomorrow, but severly doubt it’s any fast for tens of thousand of entries in a and thrice as many in b. Furthermore we want to support SQLite and PostgreSQL where to my knowledge the GROUP_CONCAT function is not available.

Thanks, good night.

Answer 1

turns out that none of these are any faster than simply doing that stuff in the program itself… and the latter is much easier to do, hence I opted for that after all.