1. Use MySQL commands to delete data from all tables
Use MySQL commands to easily delete data from all tables. Enter the following command on the command line:
TRUNCATE TABLE table_name;
where table_name is the name of the table where you want to delete data. If you have multiple tables, you need to execute this command for each table.
For example, if we have a table named "employees" and want to delete all the data in the table, we can use the following command:
TRUNCATE TABLE employees;
All the "employees" table data will be been deleted. You need to enter the name of each table separately on the command line if you want to delete multiple tables.
2. Use the graphical interface to delete data from all tables
If you prefer to use the graphical interface to manage the MySQL database, you can use MySQL Workbench. This is a free visual tool that can be used to create and manage MySQL databases and provides a more convenient way to delete data from all tables.
Here are the steps on how to delete data from all tables using MySQL Workbench:
Open MySQL Workbench and connect to your MySQL database.
Select the database where you want to delete data from the left navigation bar.
Click on the "Schema" tab and select the "Tables" submenu.
Select the table to delete data.
Click on the "Table Maintenance" tab and select the "Truncate" option.
Click the "Execute" button to execute the command.
This way you can easily delete data from all tables.
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MySQL is not a programming language, but its query language SQL has the characteristics of a programming language: 1. SQL supports conditional judgment, loops and variable operations; 2. Through stored procedures, triggers and functions, users can perform complex logical operations in the database.

MySQL is an open source relational database management system, mainly used to store and retrieve data quickly and reliably. Its working principle includes client requests, query resolution, execution of queries and return results. Examples of usage include creating tables, inserting and querying data, and advanced features such as JOIN operations. Common errors involve SQL syntax, data types, and permissions, and optimization suggestions include the use of indexes, optimized queries, and partitioning of tables.

MySQL is an open source relational database management system suitable for data storage, management, query and security. 1. It supports a variety of operating systems and is widely used in Web applications and other fields. 2. Through the client-server architecture and different storage engines, MySQL processes data efficiently. 3. Basic usage includes creating databases and tables, inserting, querying and updating data. 4. Advanced usage involves complex queries and stored procedures. 5. Common errors can be debugged through the EXPLAIN statement. 6. Performance optimization includes the rational use of indexes and optimized query statements.

MySQL is chosen for its performance, reliability, ease of use, and community support. 1.MySQL provides efficient data storage and retrieval functions, supporting multiple data types and advanced query operations. 2. Adopt client-server architecture and multiple storage engines to support transaction and query optimization. 3. Easy to use, supports a variety of operating systems and programming languages. 4. Have strong community support and provide rich resources and solutions.

InnoDB's lock mechanisms include shared locks, exclusive locks, intention locks, record locks, gap locks and next key locks. 1. Shared lock allows transactions to read data without preventing other transactions from reading. 2. Exclusive lock prevents other transactions from reading and modifying data. 3. Intention lock optimizes lock efficiency. 4. Record lock lock index record. 5. Gap lock locks index recording gap. 6. The next key lock is a combination of record lock and gap lock to ensure data consistency.

The main reasons for poor MySQL query performance include not using indexes, wrong execution plan selection by the query optimizer, unreasonable table design, excessive data volume and lock competition. 1. No index causes slow querying, and adding indexes can significantly improve performance. 2. Use the EXPLAIN command to analyze the query plan and find out the optimizer error. 3. Reconstructing the table structure and optimizing JOIN conditions can improve table design problems. 4. When the data volume is large, partitioning and table division strategies are adopted. 5. In a high concurrency environment, optimizing transactions and locking strategies can reduce lock competition.

In database optimization, indexing strategies should be selected according to query requirements: 1. When the query involves multiple columns and the order of conditions is fixed, use composite indexes; 2. When the query involves multiple columns but the order of conditions is not fixed, use multiple single-column indexes. Composite indexes are suitable for optimizing multi-column queries, while single-column indexes are suitable for single-column queries.

To optimize MySQL slow query, slowquerylog and performance_schema need to be used: 1. Enable slowquerylog and set thresholds to record slow query; 2. Use performance_schema to analyze query execution details, find out performance bottlenecks and optimize.


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