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In web development, database query is one of the most frequent operations. For databases containing large amounts of data, how to improve query efficiency is an urgent problem that needs to be solved. This article aims to introduce how to improve efficiency when performing two-table queries in PHP.
First of all, it is necessary to understand the concept of database index. An index is a structure that helps us find data quickly. They are usually separate files or special data structures in database tables. Therefore, indexes can improve query speed for find and filter operations. For example, when using the SELECT statement to query, if there are fields using indexes in the WHERE clause, the query time will be greatly reduced.
Secondly, consider using advanced queries such as INNER JOIN to replace loop nested queries. Although loop nested query seems simple, it consumes a lot of system resources, and inner joins can significantly improve query performance. An inner join is a query method that connects data from two tables that meets the join criteria. The following code is an example of using INNER JOIN:
SELECT `table1`.`column1`, `table2`.`column2` FROM `table1` INNER JOIN `table2` ON `table1`.`id` = `table2`.`id` WHERE `table1`.`name` = 'test'
In this example, we join table1
and table2
together by id
Column join data. Using INNER JOIN greatly reduces the amount of data that queries need to traverse, thereby improving efficiency.
In addition, we can also use SELECT subquery to save the results in a temporary table. This approach can significantly increase query speed by reducing the amount of data that needs to be traversed during the query. The following is an example of using a SELECT subquery:
CREATE TEMPORARY TABLE `temp_table` SELECT `column1`, `column2` FROM `table1` WHERE `column1` > 100; SELECT * FROM `table2` WHERE `column2` IN (SELECT `column2` FROM `temp_table`);
In this example, we first store the data that meets a certain condition in table1
in a temporary table, and then use # This temporary table is referenced in the ##IN operator.
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