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copied!<p>you're using innodb but not taking full advantage of your innodb clustered index (primary key) as it looks like your typical query is of the form:</p> <pre><code>select <fields> from <table> where user_id = x and <datefield> between y and z </code></pre> <p>not</p> <pre><code>select <fields> from <table> where id = x </code></pre> <p>the following article should help you optimise your table design for your query.</p> <p><a href="http://www.xaprb.com/blog/2006/07/04/how-to-exploit-mysql-index-optimizations/" rel="nofollow">http://www.xaprb.com/blog/2006/07/04/how-to-exploit-mysql-index-optimizations/</a></p> <p>If you understand the article correctly you should find youself with something like the following:</p> <pre><code>drop table if exists user_log; create table user_log ( user_id int unsigned not null, created_date datetime not null, log_type_id tinyint unsigned not null default 0, -- 1 byte vs varchar(10) ... ... primary key (user_id, created_date, log_type_id) ) engine=innodb; </code></pre> <p>Here's some query performance stats from the above design:</p> <p><strong>Counts</strong></p> <pre><code>select count(*) as counter from user_log counter ======= 37770394 select count(*) as counter from user_log where created_date between '2010-09-01 00:00:00' and '2010-11-30 00:00:00' counter ======= 35547897 </code></pre> <p><strong>User and date based queries (all queries run with cold buffers)</strong></p> <pre><code>select count(*) as counter from user_log where user_id = 4755 counter ======= 7624 runtime = 0.215 secs select count(*) as counter from user_log where user_id = 4755 and created_date between '2010-09-01 00:00:00' and '2010-11-30 00:00:00' counter ======= 7404 runtime = 0.015 secs select user_id, created_date, count(*) as counter from user_log where user_id = 4755 and created_date between '2010-09-01 00:00:00' and '2010-11-30 00:00:00' group by user_id, created_date order by counter desc limit 10; runtime = 0.031 secs </code></pre> <p>Hope this helps :)</p>

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