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POSQL magic - query shouldn't take 15 hours, but it does
 

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  1. POSQL magic - query shouldn't take 15 hours, but it does
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    <p>Ok, so i have one really monstrous MySQL table (900k records, 180 MB total), and i want to extract from subgroups records with higher <code>date_updated</code> and calculate weighted average in each group. The calculation runs for ~15 hours, and i have a strong feeling i'm <strong>doing it wrong</strong>.</p> <p>First, monstrous table layout:</p> <ul> <li><code>category</code></li> <li><code>element_id</code></li> <li><code>date_updated</code></li> <li><code>value</code></li> <li><code>weight</code></li> <li><code>source_prefix</code></li> <li><code>source_name</code></li> </ul> <p>Only key here is on <code>element_id</code> (BTREE, ~8k unique elements).</p> <p>And calculation process:</p> <p><em>Make hash for each group and subgroup.</em></p> <pre><code>CREATE TEMPORARY TABLE `temp1` (INDEX ( `ds_hash` )) SELECT `category`, `element_id`, `source_prefix`, `source_name`, `date_updated`, `value`, `weight`, MD5(CONCAT(`category`, `element_id`, `source_prefix`, `source_name`)) AS `subcat_hash`, MD5(CONCAT(`category`, `element_id`, `date_updated`)) AS `cat_hash` FROM `bigbigtable` WHERE `date_updated` &lt;= '2009-04-28' </code></pre> <p>I really don't understand this fuss with hashes, but it worked faster this way. Dark magic, i presume.</p> <p><em>Find maximum date for each subgroup</em></p> <pre><code>CREATE TEMPORARY TABLE `temp2` (INDEX ( `subcat_hash` )) SELECT MAX(`date_updated`) AS `maxdate` , `subcat_hash` FROM `temp1` GROUP BY `subcat_hash`; </code></pre> <p><em>Join temp1 with temp2 to find weighted average values for categories</em></p> <pre><code>CREATE TEMPORARY TABLE `valuebycats` (INDEX ( `category` )) SELECT `temp1`.`element_id`, `temp1`.`category`, `temp1`.`source_prefix`, `temp1`.`source_name`, `temp1`.`date_updated`, AVG(`temp1`.`value`) AS `avg_value`, SUM(`temp1`.`value` * `temp1`.`weight`) / SUM(`weight`) AS `rating` FROM `temp1` LEFT JOIN `temp2` ON `temp1`.`subcat_hash` = `temp2`.`subcat_hash` WHERE `temp2`.`subcat_hash` = `temp1`.`subcat_hash` AND `temp1`.`date_updated` = `temp2`.`maxdate` GROUP BY `temp1`.`cat_hash`; </code></pre> <p>(now that i looked through it and wrote it all down, it seems to me that i should use INNER JOIN in that last query (to avoid 900k*900k temp table)).</p> <p>Still, is there a <strong>normal way</strong> to do so?</p> <p><strong>UPD</strong>: some picture for reference:</p> <p><em>removed dead ImageShack link</em></p> <p><strong>UPD</strong>: EXPLAIN for proposed solution:</p> <pre><code>+----+-------------+-------+------+---------------+------------+---------+--------------------------------------------------------------------------------------+--------+----------+----------------------------------------------+ | id | select_type | table | type | possible_keys | key | key_len | ref | rows | filtered | Extra | +----+-------------+-------+------+---------------+------------+---------+--------------------------------------------------------------------------------------+--------+----------+----------------------------------------------+ | 1 | SIMPLE | cur | ALL | NULL | NULL | NULL | NULL | 893085 | 100.00 | Using where; Using temporary; Using filesort | | 1 | SIMPLE | next | ref | prefix | prefix | 1074 | bigbigtable.cur.source_prefix,bigbigtable.cur.source_name,bigbigtable.cur.element_id | 1 | 100.00 | Using where | +----+-------------+-------+------+---------------+------------+---------+--------------------------------------------------------------------------------------+--------+----------+----------------------------------------------+ </code></pre>
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