Contents
How optimize MySQL query with multiple joins?
2 Answers
- Check if you really have to select every column in all of the tables?
- You may also want to consider reducing the load on the database by using caching applications like sphinxsearch and memcached.
- Check none of your joins are to views rather than actual tables.
What are the various techniques for query optimization?
There are two methods of query optimization.
- Cost based Optimization (Physical) This is based on the cost of the query. The query can use different paths based on indexes, constraints, sorting methods etc.
- Heuristic Optimization (Logical) This method is also known as rule based optimization.
Why is the optimization of a query needed?
Importance: The goal of query optimization is to reduce the system resources required to fulfill a query, and ultimately provide the user with the correct result set faster. Secondly, it allows the system to service more queries in the same amount of time, because each request takes less time than unoptimized queries.
How to select from where multiple conditions in MySQL?
SELECT * FROM table WHERE column1 = ‘var1’ OR column2 = ‘var2’; Using OR will tell MySQL to return data if one or both conditions are met. Working with more than two conditions. If more than two conditions need to be met in order to show a result, you need to use parenthesis and nest the conditions according to your needs.
How to reduce the size of a query in MySQL?
To be able to utilize an index for all of the criteria in the WHERE clause, and to reduce the size of the result set as quickly as possible, add a multi-column index on the following columns on the vehicles table: The columns should be in order of highest cardinality to least.
How to optimize mysql query with many joins?
It doesn’t appear that you are using any fields in any of the joined tables, so remove the joins. This will remove all of the additional work of the query, and get you down to one, simple execution plan (one line in the EXPLAIN result). Each JOINed table causes an additional lookup per row of the result set.
Why does MySQL only use one index to select rows?
Your EXPLAIN shows that MySQL is only utilizing one index ( type_id) for selecting the rows that match the WHERE clause, even though you have multiple criteria in the clause.