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    <p>This should return the same results and perform slightly faster: </p> <pre><code>SELECT MIN( `quantities`.`start_timestamp` ) AS `start`, MAX( `quantities`.`end_timestamp` ) AS `end`, SUM( `quantities`.`quantity` * `prices`.`price` ) * COUNT(DISTINCT `quantities`.`id`) / COUNT(DISTINCT `prices`.`id`) AS total FROM `quantities` JOIN `prices` ON `prices`.`timestamp` &gt;= `quantities`.`start_timestamp` AND `prices`.`timestamp` &lt; `quantities`.`end_timestamp` AND `prices`.`type_id` = 1 WHERE `quantities`.`start_timestamp` &gt;= '2010-07-01 00:00:00' AND `quantities`.`start_timestamp` &lt; '2010-07-02 00:00:00' GROUP BY HOUR( `quantities`.`start_timestamp` ); </code></pre> <p>Since you can't calculate <code>AVG()</code> inside the <code>SUM()</code>, I had to do some interesting <code>COUNT(DISTINCT)</code> to calculate the number of <code>prices</code> returned per <code>quantities</code>. I'm wondering if this gives you the same results with "real" data...</p> <p>Using <code>JOIN</code>:</p> <pre>+----+-------------+------------+-------+-------------------------------+-----------------+---------+------+-------+----------+----------------------------------------------+ | id | select_type | table | type | possible_keys | key | key_len | ref | rows | filtered | Extra | +----+-------------+------------+-------+-------------------------------+-----------------+---------+------+-------+----------+----------------------------------------------+ | 1 | SIMPLE | quantities | range | start_timestamp,end_timestamp | start_timestamp | 8 | NULL | 89 | 100.00 | Using where; Using temporary; Using filesort | | 1 | SIMPLE | prices | ALL | timestamp,type_id | NULL | NULL | NULL | 36862 | 62.20 | Using where; Using join buffer | +----+-------------+------------+-------+-------------------------------+-----------------+---------+------+-------+----------+----------------------------------------------+ </pre> <p>vs. the same query only adding <code>LEFT</code> to the <code>JOIN</code></p> <pre>+----+-------------+------------+-------+-------------------+-----------------+---------+-------+-------+----------+----------------------------------------------+ | id | select_type | table | type | possible_keys | key | key_len | ref | rows | filtered | Extra | +----+-------------+------------+-------+-------------------+-----------------+---------+-------+-------+----------+----------------------------------------------+ | 1 | SIMPLE | quantities | range | start_timestamp | start_timestamp | 8 | NULL | 89 | 100.00 | Using where; Using temporary; Using filesort | | 1 | SIMPLE | prices | ref | timestamp,type_id | type_id | 4 | const | 22930 | 100.00 | | +----+-------------+------------+-------+-------------------+-----------------+---------+-------+-------+----------+----------------------------------------------+ </pre> <p>Interesting that <code>LEFT</code> can completely removes the <code>end_timestamp</code> as a possible key, and changes the selected keys so much, making it take 15 times as long...</p> <p><a href="http://dev.mysql.com/doc/refman/5.0/en/index-hints.html" rel="nofollow noreferrer">This reference page</a> could help you out a little more if you want to look at specifying index hints for your JOINS</p>
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    1. POMySQL query with dependent subquery takes too long
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    1. CO+1 This is good, also adding composite indexes on (start_timestamp, end_timestamp) and on (type_id, timestamp) should help. However, I think I'll be able to bring it down to ~0.01 sec
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    2. CO@Unreason --- *scratches head* you say +1, but noone has voted yet ;) --- `</impatience>` --- I'm interested in seeing how you get it down that far!
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    3. COThanks gnarf, this is almost spot on. It is running in about 0.4 secs on my machine but the results are different to my original query. The reason I think is because you are dividing by COUNT(`prices`.`price`), which with the GROUP clause and this data will be 4 quantity rows * 3 price rows = 12, but if you divide by 3 then it generates the same results as my original query. Trouble is I don't want to hard code 3 in the query, but I can't figure out what the SQL is to derive that value from the data. Once that part is sorted, it'll all be perfect. Any ideas much appreciated?
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