Optimizing SELECT Statements Indexes are especially important for queries that reference different tables, using features such as joins and foreign keys. You can use the  EXPLAIN  statement to determine which indexes are used for a SELECT . See Section 8.3.1, “How MySQL Uses Indexes”  and Section 8.8.1, “Optimizing Queries with EXPLAIN” . •To make a slow  SELECT ... WHERE  query faster, the first thing to check is whether you can add an index. Set up indexes on columns used in the  WHERE  clause, to speed up evaluation, filtering, and the final retrieval of results. To avoid wasted disk space, construct a small set of indexes that speed up many related queries used in your application. •Isolate and tune any part of the query, such as a function call, that takes excessive time. Depending on how the query is structured, a function could be called once for every row in the result set, or even once for every row in the table, greatly magnifying any inefficiency. •Minimize the number of full table scans in your queries, particularly for big tables. •Keep table statistics up to date by using the  ANALYZE TABLE  statement periodically, so the optimizer has the information needed to construct an efficient execution plan. •Learn the tuning techniques, indexing techniques, and configuration parameters that are specific to the storage engine for each table. Both  InnoDB  and  MyISAM  have sets of guidelines for enabling and sustaining high performance in queries. For details, see Section 8.5.6, “Optimizing InnoDB Queries”  and Section 8.6.1, “Optimizing MyISAM Queries” . •You can optimize single-query transactions for  InnoDB  tables, using the technique in Section 8.5.3, “Optimizing InnoDB Read-Only Transactions” . •Avoid transforming the query in ways that make it hard to understand, especially if the optimizer does some of the same transformations automatically. •If a performance issue is not easily solved by one of the basic guidelines, investigate the internal details of the specific query by reading the  EXPLAIN  plan and adjusting your indexes,  WHERE  clauses, join clauses, and so on. (When you reach a certain level of expertise, reading the  EXPLAIN  plan might be your first step for every query.) •Adjust the size and properties of the memory areas that MySQL uses for caching. With efficient use of the  InnoDB  buffer pool,  MyISAM  key cache, and the MySQL query cache, repeated queries run faster because the results are retrieved from memory the second and subsequent times. •Even for a query that runs fast using the cache memory areas, you might still optimize further so that they require less cache memory, making your application more scalable. Scalability means that your application can handle more simultaneous users, larger requests, and so on without experiencing a big drop in performance. •Deal with locking issues, where the speed of your query might be affected by other sessions accessing the tables at the same time. 1641 Because work on the MySQL optimizer is ongoing, not all of the optimizations that MySQL performs are documented here. This section discusses optimizations that can be made for processing  WHERE  clauses. The examples use  SELECT  statements, but the same optimizations apply for  WHERE  clauses in  DELETE  and  UPDATE statements. 8.2.1.1 WHERE Clause Optimization Note