How to set the primary key in the database?
SQL method of setting primary key
Open the [SQL Server Management Studio] management tool and connect to the database
[New table Set the primary key] - Open the new table interface
1) Expand the database where you want to create a new table
2) Right-click the [Table] menu and select [New]->[Table]
[Set the primary key when creating a new table] - Set the primary key
1) In the "New Table Interface", add two test column rows
2) Select any line, right-click and select [Set Primary Key]
3) Combined primary key setting: Hold down the ctrl key and use the left mouse button to select more lines, then right-click and select [Set Primary Key]
4) After adding the column, click the [Save] button, enter the "table name" in the pop-up box, and click the OK button
Recommended tutorial:sql tutorial
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The relationship between SQL and MySQL is: SQL is a language used to manage and operate databases, while MySQL is a database management system that supports SQL. 1.SQL allows CRUD operations and advanced queries of data. 2.MySQL provides indexing, transactions and locking mechanisms to improve performance and security. 3. Optimizing MySQL performance requires attention to query optimization, database design and monitoring and maintenance.

SQL is used for database management and data operations, and its core functions include CRUD operations, complex queries and optimization strategies. 1) CRUD operation: Use INSERTINTO to create data, SELECT reads data, UPDATE updates data, and DELETE deletes data. 2) Complex query: Process complex data through GROUPBY and HAVING clauses. 3) Optimization strategy: Use indexes, avoid full table scanning, optimize JOIN operations and paging queries to improve performance.

SQL is suitable for beginners because it is simple in syntax, powerful in function, and widely used in database systems. 1.SQL is used to manage relational databases and organize data through tables. 2. Basic operations include creating, inserting, querying, updating and deleting data. 3. Advanced usage such as JOIN, subquery and window functions enhance data analysis capabilities. 4. Common errors include syntax, logic and performance issues, which can be solved through inspection and optimization. 5. Performance optimization suggestions include using indexes, avoiding SELECT*, using EXPLAIN to analyze queries, normalizing databases, and improving code readability.

In practical applications, SQL is mainly used for data query and analysis, data integration and reporting, data cleaning and preprocessing, advanced usage and optimization, as well as handling complex queries and avoiding common errors. 1) Data query and analysis can be used to find the most sales product; 2) Data integration and reporting generate customer purchase reports through JOIN operations; 3) Data cleaning and preprocessing can delete abnormal age records; 4) Advanced usage and optimization include using window functions and creating indexes; 5) CTE and JOIN can be used to handle complex queries to avoid common errors such as SQL injection.

SQL is a standard language for managing relational databases, while MySQL is a specific database management system. SQL provides a unified syntax and is suitable for a variety of databases; MySQL is lightweight and open source, with stable performance but has bottlenecks in big data processing.

The SQL learning curve is steep, but it can be mastered through practice and understanding the core concepts. 1. Basic operations include SELECT, INSERT, UPDATE, DELETE. 2. Query execution is divided into three steps: analysis, optimization and execution. 3. Basic usage is such as querying employee information, and advanced usage is such as using JOIN connection table. 4. Common errors include not using alias and SQL injection, and parameterized query is required to prevent it. 5. Performance optimization is achieved by selecting necessary columns and maintaining code readability.

SQL commands are divided into five categories in MySQL: DQL, DDL, DML, DCL and TCL, and are used to define, operate and control database data. MySQL processes SQL commands through lexical analysis, syntax analysis, optimization and execution, and uses index and query optimizers to improve performance. Examples of usage include SELECT for data queries and JOIN for multi-table operations. Common errors include syntax, logic, and performance issues, and optimization strategies include using indexes, optimizing queries, and choosing the right storage engine.

Advanced query skills in SQL include subqueries, window functions, CTEs and complex JOINs, which can handle complex data analysis requirements. 1) Subquery is used to find the employees with the highest salary in each department. 2) Window functions and CTE are used to analyze employee salary growth trends. 3) Performance optimization strategies include index optimization, query rewriting and using partition tables.


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