How to make the use of database indexes more efficient?
Indexes have a crucial impact on query speed. Understanding indexes is also the starting point for database performance tuning. During actual operations, which fields in the table should be selected as indexes? In order to make the use of indexes more efficient, when creating an index, you must consider which fields to create the index on and what type of index to create. There are 7 major principles:
1. Select a unique index
The value of the unique index is unique, and a record can be determined more quickly through the index. For example, the middle school ID in the student table is a unique field. Establishing a unique index for this field can quickly determine a student's information. If you use names, there may be the same name, which will slow down the query speed.
2. Create indexes for fields that often require sorting, grouping, and union operations
For fields that often require operations such as ORDER BY, GROUP BY, DISTINCT, and UNION, sorting operations will waste a lot of time. If you index it, you can effectively avoid the sort operation.
3. Create indexes for fields that are often used as query conditions
If a field is often used as a query condition, the query speed of this field will affect the query speed of the entire table. Therefore, indexing such fields can improve the query speed of the entire table.
4. Limit the number of indexes
The more indexes, the better. Each index requires disk space. The more indexes, the more disk space is required. When the table is modified, it is troublesome to reconstruct and update the index. The more indexes, the more time-consuming it becomes to update the table.
5. Try to use an index with a small amount of data
If the index value is very long, the query speed will be affected. For example, a full-text search for a CHAR(100) type field will definitely take more time than a CHAR(10) type field.
6. Try to use prefixes to index
If the value of the index field is very long, it is best to use the prefix of the value to index. For example, full-text search for TEXT and BLOG type fields will be a waste of time. If only the first few characters of the field are retrieved, the retrieval speed can be improved.
7. Delete indexes that are no longer used or rarely used
After the data in the table is updated a lot, or the way the data is used is changed, some of the original indexes may no longer be needed. Database administrators should regularly identify these indexes and delete them to reduce the impact of the indexes on update operations.
Note: The ultimate purpose of selecting an index is to make the query faster. The principles given above are the most basic guidelines, but you cannot stick to the above guidelines. Readers should continue to practice in their future studies and work. Analyze and judge based on the actual situation of the application, and select the most appropriate indexing method.
For example, let’s say you are making a membership card system for a shopping mall. This system has a membership table (roughly the fields are as follows):
Member number INT
Member name VARCHAR(10)
Member ID number VARCHAR(18)
Member phone number VARCHAR(10)
Member address VARCHAR(50)
Member remark information TEXT
Then this member number, as the primary key, use PRIMARY
If the member name is to be indexed, then it is ordinary INDEX
If you want to build an index for the member’s ID card number, you can choose UNIQUE (unique, no duplicates allowed)
Member’s remarks information. If you need to build an index, you can choose FULLTEXT for full-text search. .
The above 7 points are to make the use of indexes more efficient. I hope it will be helpful to everyone.
Related recommendations:
In order to make the use of indexes more efficient
The difference between btree and hash indexes in MySQL
How to use mysql index optimization
The above is the detailed content of How to make the use of database indexes more efficient?. For more information, please follow other related articles on the PHP Chinese website!

Stored procedures are precompiled SQL statements in MySQL for improving performance and simplifying complex operations. 1. Improve performance: After the first compilation, subsequent calls do not need to be recompiled. 2. Improve security: Restrict data table access through permission control. 3. Simplify complex operations: combine multiple SQL statements to simplify application layer logic.

The working principle of MySQL query cache is to store the results of SELECT query, and when the same query is executed again, the cached results are directly returned. 1) Query cache improves database reading performance and finds cached results through hash values. 2) Simple configuration, set query_cache_type and query_cache_size in MySQL configuration file. 3) Use the SQL_NO_CACHE keyword to disable the cache of specific queries. 4) In high-frequency update environments, query cache may cause performance bottlenecks and needs to be optimized for use through monitoring and adjustment of parameters.

The reasons why MySQL is widely used in various projects include: 1. High performance and scalability, supporting multiple storage engines; 2. Easy to use and maintain, simple configuration and rich tools; 3. Rich ecosystem, attracting a large number of community and third-party tool support; 4. Cross-platform support, suitable for multiple operating systems.

The steps for upgrading MySQL database include: 1. Backup the database, 2. Stop the current MySQL service, 3. Install the new version of MySQL, 4. Start the new version of MySQL service, 5. Recover the database. Compatibility issues are required during the upgrade process, and advanced tools such as PerconaToolkit can be used for testing and optimization.

MySQL backup policies include logical backup, physical backup, incremental backup, replication-based backup, and cloud backup. 1. Logical backup uses mysqldump to export database structure and data, which is suitable for small databases and version migrations. 2. Physical backups are fast and comprehensive by copying data files, but require database consistency. 3. Incremental backup uses binary logging to record changes, which is suitable for large databases. 4. Replication-based backup reduces the impact on the production system by backing up from the server. 5. Cloud backups such as AmazonRDS provide automation solutions, but costs and control need to be considered. When selecting a policy, database size, downtime tolerance, recovery time, and recovery point goals should be considered.

MySQLclusteringenhancesdatabaserobustnessandscalabilitybydistributingdataacrossmultiplenodes.ItusestheNDBenginefordatareplicationandfaulttolerance,ensuringhighavailability.Setupinvolvesconfiguringmanagement,data,andSQLnodes,withcarefulmonitoringandpe

Optimizing database schema design in MySQL can improve performance through the following steps: 1. Index optimization: Create indexes on common query columns, balancing the overhead of query and inserting updates. 2. Table structure optimization: Reduce data redundancy through normalization or anti-normalization and improve access efficiency. 3. Data type selection: Use appropriate data types, such as INT instead of VARCHAR, to reduce storage space. 4. Partitioning and sub-table: For large data volumes, use partitioning and sub-table to disperse data to improve query and maintenance efficiency.

TooptimizeMySQLperformance,followthesesteps:1)Implementproperindexingtospeedupqueries,2)UseEXPLAINtoanalyzeandoptimizequeryperformance,3)Adjustserverconfigurationsettingslikeinnodb_buffer_pool_sizeandmax_connections,4)Usepartitioningforlargetablestoi


Hot AI Tools

Undresser.AI Undress
AI-powered app for creating realistic nude photos

AI Clothes Remover
Online AI tool for removing clothes from photos.

Undress AI Tool
Undress images for free

Clothoff.io
AI clothes remover

Video Face Swap
Swap faces in any video effortlessly with our completely free AI face swap tool!

Hot Article

Hot Tools

Atom editor mac version download
The most popular open source editor

SublimeText3 Mac version
God-level code editing software (SublimeText3)

PhpStorm Mac version
The latest (2018.2.1) professional PHP integrated development tool

MantisBT
Mantis is an easy-to-deploy web-based defect tracking tool designed to aid in product defect tracking. It requires PHP, MySQL and a web server. Check out our demo and hosting services.

mPDF
mPDF is a PHP library that can generate PDF files from UTF-8 encoded HTML. The original author, Ian Back, wrote mPDF to output PDF files "on the fly" from his website and handle different languages. It is slower than original scripts like HTML2FPDF and produces larger files when using Unicode fonts, but supports CSS styles etc. and has a lot of enhancements. Supports almost all languages, including RTL (Arabic and Hebrew) and CJK (Chinese, Japanese and Korean). Supports nested block-level elements (such as P, DIV),
