![]() Thank you MySQL Table and index statistics You can see this in the following example: For instance, if MySQL detects an impossible condition, it can abort the entire query. The obvious case is a LIMIT clause, but there are several other kinds of early termination. MySQL can stop processing a query (or a step in a query) as soon as it fulfills the query or step. MySQL can convert some types of subqueries into more efficient alternative forms, reducing them to index lookups instead of separate queries. MySQL can sometimes use an index to avoid reading row data, when the index contains all the columns the query needs it returns the data from index itself. Likewise, COUNT(*) queries without a WHERE clause can often be optimized away on some storage engines (such as MyISAM, which keeps an exact count of rows in the table at all times). Similarly, to find the maximum value in a B-Tree index, the server reads the last row. It can even do this in the query optimization stage, and treat the value as a constant for the rest of the query. ![]() For example, to find the minimum value of a column that’s leftmost in a B-Tree index, MySQL can just request the first row in the index. Indexes and column nullability can often help MySQL optimize away these expressions. These rules are very useful for writing conditional queries. ![]() For example, the term (5=5 AND a>5) will reduce to just a>5. It can also fold and reduce constants, eliminating impossible constraints and constant conditions. MySQL applies algebraic transformations to simplify and order expressions. MySQL can recognize this and rewrite the join, which makes it eligible for reordering. Some factors, such as the WHERE clause and table schema, can actually cause an OUTER JOIN to be equivalent to an INNER JOIN. Converting OUTER JOINs to INNER JOINsĪn OUTER JOIN doesn’t necessarily have to be executed as an OUTER JOIN. Determining the best join order is an important optimization. Tables don’t always have to be joined in the order you specify in the query. Here are some types of optimizations MySQL knows how to do: Reordering joins This lets you know what decisions the server is making and gives you a reference point for reworking queries, schemas, and settings to make everything run as efficiently as possible. You can also ask the server to explain various aspects of optimization. You can pass hints to the optimizer through special keywords in the query, affecting its decision making process. These can include rewriting the query, determining the order in which it will read tables, choosing which indexes to use, and so on. MySQL parses queries to create an internal structure (the parse tree), and then applies a variety of optimizations. Mark Callaghan on Plan to remove sql-bench from MySQL 5.For insights of mysql’s architecture take a quick read - MySQL Logical Architecture.Simon J Mudd on What to tune in MySQL 5.6 after installation.Archimedes Trajano on Plan to remove unused command line programs (10 out of 43).What would you like to see in MySQL 5.8?. ![]() MySQL Community Reception at Oracle OpenWorld.Moving to Product Management & European Tour.This blog, now Powered by WordPress + TiDB.TiDB now supported in DBdeployer 1.19.0!.Next Post Next MySQL 5.7.8 – mysqlpump caveat Site Content The supplies of this special edition t-shirt are limited, but I will ship it to you anywhere in the world □ The MySQL 5.7 Community Contributor Polo, as modeled by Daniël van Eeden. If you can demonstrate a reproducible testcase, I have a polo with MySQL 5.7 Community Contributor on it waiting for you. The optimizer team has also allowed cost constants to be configurable on both a server and a storage engine basis, and we are confident that the default InnoDB engine will always work “as good as MyISAM” (which has a natural advantage, in that the optimizer was originally largely built around it.)įind an example where the optimizer picks the wrong execution plan for InnoDB tables but is correct for MyISAM. The hacks of storage engines lying to the optimizer are being rolled back, and your chances of getting an optimal query plan should now be much higher than in prior releases of MySQL. In the MySQL team, we have been working really hard on refactoring the optimizer and improving the cost model.
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