Data storage structure analysis method in MySQL

MySQL is a commonly used database management system that is widely used in Web applications due to its high efficiency, high performance and high reliability. In MySQL, data storage structure is a very important concept. It helps us understand the way database is stored and enables us to better optimize database performance. This article will introduce the data storage structure analysis method in MySQL.

1. InnoDB storage engine

InnoDB is the most commonly used storage engine in MySQL. It stores data in behavioral units and supports transactions and locking mechanisms. In InnoDB, the data storage structure mainly consists of the following components:

(1) Clustered index

Clustered index is the structure for storing rows in InnoDB, which stores data rows in On disk, the primary key of the clustered index is the index of the table data, that is, the data rows are sorted according to the value of the primary key. Since adjacent rows are usually adjacent on the hard disk, this storage structure can read adjacent rows very quickly.

(2) Auxiliary index

Auxiliary index is a technology that uses non-primary key columns to build an index. Unlike a clustered index, a secondary index stores information about primary key values ​​and secondary index columns. If there is no auxiliary index, the query results need to be achieved through a full table scan, which is less efficient.

(3) Page

The page is the smallest unit in InnoDB to store its data and index items. Each page is typically 16KB in size, and each table usually has multiple pages to store data.

2. MyISAM storage engine

MyISAM is another commonly used storage engine in MySQL. Unlike InnoDB, MyISAM does not support transactions and locking mechanisms. In MyISAM, the data storage structure mainly consists of the following components:

(1) Data row

The data row is the structure for storing data in MyISAM. Unlike InnoDB, data rows are stored on disk rather than in memory. Of course, MySQL will put rows of data into memory when necessary.

(2) Index

The index is a structure for quickly retrieving data. In MyISAM, indexes are stored on disk in the form of B-trees. Each index node stores the index column and a pointer to the next node, and the index tree is usually balanced.

3. Fragmentation of database tables

When data is continuously inserted and deleted from the table, the data in the table may become fragmented. In this case, the query efficiency will be reduced because the query results need to skip the deleted data. MySQL provides the optimize table command to defragment the table. During this process, MySQL reorganizes the data and stores it in a more compact space.

4. Summary

MySQL’s data storage structure is an important concept in database design and performance optimization. This article introduces the data storage structures of InnoDB and MyISAM storage engines, as well as the optimization methods of defragmentation. For MySQL developers and DBAs, understanding MySQL's data storage structure is a critical step in achieving an efficient MySQL database.

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