I’ve seen a few people link to an INFORMATION_SCHEMA query to be able to find any indexes that have low cardinality, in an effort to find out what indexes should be removed. This method is flawed – here’s the first reason why:
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 | CREATE TABLE `sales` ( `id` int(11) NOT NULL AUTO_INCREMENT, `customer_id` int(11) DEFAULT NULL, `status` enum('archived','active') DEFAULT NULL, PRIMARY KEY (`id`), KEY `status` (`status`) ) ENGINE=MyISAM AUTO_INCREMENT=65691 DEFAULT CHARSET=latin1; mysql> SELECT count(*), status FROM sales GROUP by status; +----------+---------+ | count(*) | status | +----------+---------+ |   65536 | archived | |     154 | active | +----------+---------+ 2 rows in set (0.17 sec) mysql> EXPLAIN SELECT * FROM sales WHERE status='active'; # query 1 +----+-------------+-------+------+---------------+--------+---------+-------+------+-------------+ | id | select_type | table | type | possible_keys | key   | key_len | ref  | rows | Extra      | +----+-------------+-------+------+---------------+--------+---------+-------+------+-------------+ | 1 | SIMPLE     | sales | ref | status       | status | 2      | const | 196 | Using where | +----+-------------+-------+------+---------------+--------+---------+-------+------+-------------+ 1 row in set (0.06 sec) mysql> EXPLAIN SELECT * FROM sales WHERE status='archived'; # query 2 +----+-------------+-------+------+---------------+------+---------+------+-------+-------------+ | id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra      | +----+-------------+-------+------+---------------+------+---------+------+-------+-------------+ | 1 | SIMPLE     | sales | ALL | status       | NULL | NULL   | NULL | 65690 | Using where | +----+-------------+-------+------+---------------+------+---------+------+-------+-------------+ 1 row in set (0.01 sec) |
The cardinality of status index is woeful, but provided that the application [...]


mk-query-digest, query comments and the query cache
I very much like the fact that MySQL allows you to embed comments into SQL statements. These comments are extremely convenient, because they are written into MySQL log files as part of the query. This includes the general log, the binary log and the slow query log. Maatkit includes tools which interact with these logs, [...]