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Database

Mysql Tutorial

MySQL database audit function configuration and log analysis

MySQL database auditing mainly relies on the audit_log plug-in to implement. 1. Install the plug-in INSTALLPLUGINaudit_logSONAME'audit_log.so';; 2. Enable the plug-in SETGLOBALplugin_audit_log=ON;; 3. Use the CREATEAUDITDEFINITION statement to create an audit strategy, such as recording DML operations of a specific database; 4. View the log storage location through SHOWVARIABLESLIKE'audit_log%'; and use tools to analyze the log; 5. Advanced usage includes real-time monitoring and alarming in combination with monitoring tools. Properly configure policies and clear them regularly

Apr 08, 2025 am 10:36 AM

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Getting started with MySQL plug-in development: writing custom functions (UDFs)

This article introduces the development of MySQL custom functions (UDF). 1. UDF allows users to extend MySQL functions and handle tasks that cannot be handled by built-in functions; 2. UDF development usually uses C language and requires familiarity with MySQL architecture and API; 3. Development steps include: initializing functions (checking parameters), core logic functions (implementing functions), and cleaning functions; 4. Pay attention to error handling, performance optimization, security and code maintainability. Through learning, developers can write UDFs that meet specific needs and improve database functions.

Apr 08, 2025 am 10:33 AM

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Detailed explanation of nested usage scenarios for CASE WHEN conditional judgment

Nested CASEWHEN statements are used to handle complex SQL conditional branches. 1. It achieves multi-condition judgment through multi-layer nesting, similar to a tree-like structure, with the outer layer as a tree trunk and the inner layer as a tree branch. 2. In order to improve readability and maintainability, it is necessary to make good use of comments, standardize code formats, and consider using auxiliary tables or functions to simplify logic. 3. The key to avoiding traps is to avoid missing ELSE statements, carefully check the logic to avoid errors, and pay attention to optimizing performance to prevent excessive nesting from affecting query efficiency. Only by mastering these skills can you efficiently use nested CASEWHEN statements.

Apr 08, 2025 am 10:30 AM

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Analysis of the failure scenario of the leftmost prefix principle of composite index

The failure of composite indexes is mainly caused by the following situations: 1. Range query (such as LIKE or >) appears in the middle of the composite index column, resulting in the index only using the columns before the range query; 2. The query conditions are not arranged in the order of the index columns, and MySQL cannot take advantage of the order characteristics of the index; 3. Use functions or expression operations on the index columns, and MySQL cannot directly use the index; 4. The index column type does not match the query condition type, and type conversion is required; 5. The index column contains NULL values, and the query conditions use ISNULL or ISNOTNULL. Only by understanding these failure scenarios and designing appropriate composite indexes based on query conditions can we improve database query efficiency.

Apr 08, 2025 am 10:27 AM

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Emergency handling of insufficient disk space causing MySQL crash

The solution to the crash caused by insufficient MySQL disk space is: 1. Confirm the problem: Check the error information in the system log; 2. Make room: delete unnecessary files (operate with caution, backup first), clean the MySQL log (clear ib_logfile or slow_query.log after backup, or use mysqlbinlog to clean the binary log and set the log rotation policy); 3. Expand the disk space: Contact the server provider or administrator. Preventive measures include regularly monitoring disk space, setting up alarm mechanisms, rational database design, regular cleaning of useless data, optimizing database performance, and formulating complete backup and recovery strategies to avoid data loss.

Apr 08, 2025 am 10:24 AM

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Use scenarios and deadlock checks for row locks, table locks, and gap locks

The article mainly introduces the three lock mechanisms of row lock, table lock and gap lock in the database and their deadlock problems. 1. Row locks locks specific data rows, with high concurrency, and the InnoDB engine uses by default; 2. Table locks locks the entire table, with low concurrency, and is used for batch operations or database maintenance; 3. Gap locks locks the gap between data rows, preventing phantom reading. Deadlock occurs when transactions hold each other's resources required by each other. The troubleshooting method includes viewing the database log, analyzing the causes of deadlock (such as circular dependency, lock granularity), and solving it by optimizing code, reducing lock holding time, or adjusting lock sequence. The ultimate goal is to choose the right lock type and properly handle concurrency, avoid deadlocks, and improve database stability and efficiency.

Apr 08, 2025 am 10:21 AM

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Coding specifications and tool recommendations for preventing SQL injection attacks

SQL Injection: Kill in the cradle Have you ever thought that seemingly simple database queries hide risks that are enough to destroy the entire system? SQL injection, this old opponent lurking deep in the code, is waiting for your negligence. In this article, let’s talk about how to effectively prevent SQL injection and make your application indestructible. After reading it, you will master the skills of writing secure code and learn some powerful tools that can help you easily handle SQL injection. Let’s start with the basics. The essence of SQL injection is that an attacker uses maliciously constructed SQL statements to bypass your program logic and directly operate the database. Imagine a statement that should have queryed user information and was inserted into OR1=1 by the attacker. What is the result? All user information is exposed

Apr 08, 2025 am 10:18 AM

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MySQL complete code example of combining multiple pieces of data into one

MySQL data merging is mainly implemented through the GROUP_CONCAT function and the JSON function. 1. Use the GROUP_CONCAT function to concatenate multiple records into strings, control the order and separator through ORDERBY and SEPARATOR, and GROUPBY specifies the grouping basis; 2. For complex data structures (such as JSON), use the JSON_ARRAYAGG function to merge multiple JSON objects into JSON arrays, which requires support from MySQL 5.7 or higher. The selection method depends on the data structure and complexity. Pay attention to the GROUP_CONCAT length limit and choose the optimal solution according to the actual situation.

Apr 08, 2025 am 10:15 AM

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Detailed explanation of the steps for deploying MySQL multi-instance in Linux environment

The key to deploying MySQL multi-instances under Linux is to configure independent data directories and configuration files for each instance. Specific steps: 1. Create an independent instance directory; 2. Copy and modify the configuration file to ensure that the datadir and port parameters of each instance are unique; 3. Use mysql_install_db to initialize the database of each instance; 4. Register each instance as a system service for management; 5. Reasonably allocate system resources and perform performance tuning, and back up data regularly. Only by understanding the principles behind these steps can we effectively avoid errors and ensure the stable operation of multiple instances.

Apr 08, 2025 am 10:12 AM

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How to locate SQL performance bottlenecks through slow query logs?

The main steps to optimize SQL using slow query logs: 1. Turn on the slow query log and set the execution time threshold (for example, modify the my.cnf file in MySQL); 2. Analyze the slow query log and pay attention to execution time, SQL statements and additional information (such as execution plan); 3. Find performance bottlenecks based on the log information, such as missing indexes; 4. Take optimization measures, such as adding indexes (CREATEINDEX statements) or optimizing the SQL statement itself; 5. Combining database monitoring tools and business logic comprehensive analysis, continuously monitor and optimize database performance. Ultimately, we will achieve the goal of improving database efficiency.

Apr 08, 2025 am 10:09 AM

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Password policy strengthening and regular script replacement implementation

This article describes how to use Python scripts to strengthen password policies and change passwords regularly. The steps are as follows: 1. Use Python's random and string modules to generate random passwords that meet the complexity requirements; 2. Use the subprocess module to call system commands (such as Linux's passwd command) to change the password to avoid hard-code the password directly; 3. Use crontab or task scheduler to execute scripts regularly. This script needs to handle errors carefully and add logs, and update regularly to deal with security vulnerabilities. Multi-level security protection can ensure system security.

Apr 08, 2025 am 10:06 AM

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Practical application cases of optimism and pessimistic locks in business

The choice of optimistic locks and pessimistic locks depends on business scenarios and data consistency requirements. 1. Pessimistic locks assume data conflicts, and locks ensure data consistency, but low efficiency under high concurrency, such as bank transfers; 2. Optimistic locks assume data conflict probability is low, and no locks are added, check whether the data is modified before update, with high efficiency but data inconsistency, such as e-commerce inventory management and forum comments; 3. High concurrency scenarios can consider combining optimistic locks and pessimistic locks, first optimistic lock preprocessing, and finally pessimistic lock confirmation, taking into account efficiency and data consistency. The final choice requires the trade-off between efficiency and data consistency.

Apr 08, 2025 am 10:03 AM

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MySQL dual master hot standby solution based on Keepalived

The MySQL dual master hot standby solution based on Keepalived ensures that the database service is not interrupted. 1. Keepalived monitors the database instance, and switches the VIP to the backup library when the main library fails; 2. MySQL replication function (such as GTID) ensures the synchronization and consistency of the data of the two main libraries; 3. Keepalived relies on the heartbeat package to detect the status of the main node through the VRRP protocol, and switches the VIP according to the configuration parameters (priority, detection interval, etc.). Carefully configures to avoid the phenomenon of split brain; 4. A script is required to monitor the MySQL status and troubleshoot problems in combination with logs; 5. High availability requires selecting appropriate hardware, regular backups, reasonable monitoring, and continuous maintenance and optimization.

Apr 08, 2025 am 10:00 AM

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Solution to the rollback segment inflation problem caused by large transactions

Rollback segment bloat caused by big transactions: a nightmare of database performance and how to escape from this pain many developers have experienced: database performance suddenly drops, query slows down, and even goes down directly. The culprit is often those huge affairs, which burst the rollback segment, making the database breathless. In this article, let’s discuss this issue in depth and see how to solve this headache-increasing “expansion”. The purpose of the article is to help you understand the root causes of rollback segment swelling due to large transactions and provide some effective solutions. After reading, you will be able to manage database transactions more effectively, avoid performance bottlenecks, and improve the stability and reliability of the database. Let’s start with the basics. The rollback segment is where the database uses to store transaction rollback information. Be a business

Apr 08, 2025 am 09:57 AM

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