无详细内容 异常处理 MySQL mysqlmysql delimiter $$mysqlmysql CREATE PROCEDURE myProc - (p_first_name VARCHAR(30), - p_last_name VARCHAR(30), - p_city VARCHAR(30), - p_description VARCHAR(30), - OUT p_sqlcode INT, - OUT p_status_message VARCH
异常处理 MySQLmysql> mysql> delimiter $$ mysql> mysql> CREATE PROCEDURE myProc -> (p_first_name VARCHAR(30), -> p_last_name VARCHAR(30), -> p_city VARCHAR(30), -> p_description VARCHAR(30), -> OUT p_sqlcode INT, -> OUT p_status_message VARCHAR(100)) -> BEGIN -> -> /* START Declare Conditions */ -> -> DECLARE duplicate_key CONDITION FOR 1062; -> DECLARE foreign_key_violated CONDITION FOR 1216; -> -> /* END Declare Conditions */ -> -> /* START Declare variables and cursors */ -> -> DECLARE l_manager_id INT; -> -> DECLARE csr_mgr_id CURSOR FOR -> SELECT id -> FROM employee -> WHERE first_name=p_first_name -> AND last_name=p_last_name; -> -> /* END Declare variables and cursors */ -> -> /* START Declare Exception Handlers */ -> -> DECLARE CONTINUE HANDLER FOR duplicate_key -> BEGIN -> SET p_sqlcode=1052; -> SET p_status_message='Duplicate key error'; -> END; -> -> DECLARE CONTINUE HANDLER FOR foreign_key_violated -> BEGIN -> SET p_sqlcode=1216; -> SET p_status_message='Foreign key violated'; -> END; -> -> DECLARE CONTINUE HANDLER FOR not FOUND -> BEGIN -> SET p_sqlcode=1329; -> SET p_status_message='No record found'; -> END; -> -> /* END Declare Exception Handlers */ -> -> /* START Execution */ -> -> SET p_sqlcode=0; -> OPEN csr_mgr_id; -> FETCH csr_mgr_id INTO l_manager_id; -> -> IF p_sqlcode<>0 THEN /* Failed to get manager id*/ -> SET p_status_message=CONCAT(p_status_message,' when fetching manager id'); -> ELSE -> INSERT INTO employee (first_name,id,city) -> VALUES(p_first_name,l_manager_id,p_city); -> -> IF p_sqlcode<>0 THEN /* Failed to insert new department */ -> SET p_status_message=CONCAT(p_status_message, -> ' when inserting new department'); -> END IF; -> END IF; -> -> CLOSE csr_mgr_id; -> -> /* END Execution */ -> -> END$$ Query OK, 0 rows affected (0.02 sec) mysql> mysql> delimiter ; mysql> set @myCode = 0; Query OK, 0 rows affected (0.00 sec) mysql> set @myMessage = 0; Query OK, 0 rows affected (0.00 sec) mysql> mysql> call myProc('Jason','Martin','New City','New Description',@myCode,@myMessage); Query OK, 1 row affected (0.00 sec) mysql> mysql> select @myCode, @myMessage; +---------+------------+ | @myCode | @myMessage | +---------+------------+ | 0 | NULL | +---------+------------+ 1 row in set (0.00 sec) mysql> mysql> drop procedure myProc; Query OK, 0 rows affected (0.00 sec)

InnoDB uses redologs and undologs to ensure data consistency and reliability. 1.redologs record data page modification to ensure crash recovery and transaction persistence. 2.undologs records the original data value and supports transaction rollback and MVCC.

Key metrics for EXPLAIN commands include type, key, rows, and Extra. 1) The type reflects the access type of the query. The higher the value, the higher the efficiency, such as const is better than ALL. 2) The key displays the index used, and NULL indicates no index. 3) rows estimates the number of scanned rows, affecting query performance. 4) Extra provides additional information, such as Usingfilesort prompts that it needs to be optimized.

Usingtemporary indicates that the need to create temporary tables in MySQL queries, which are commonly found in ORDERBY using DISTINCT, GROUPBY, or non-indexed columns. You can avoid the occurrence of indexes and rewrite queries and improve query performance. Specifically, when Usingtemporary appears in EXPLAIN output, it means that MySQL needs to create temporary tables to handle queries. This usually occurs when: 1) deduplication or grouping when using DISTINCT or GROUPBY; 2) sort when ORDERBY contains non-index columns; 3) use complex subquery or join operations. Optimization methods include: 1) ORDERBY and GROUPB

MySQL/InnoDB supports four transaction isolation levels: ReadUncommitted, ReadCommitted, RepeatableRead and Serializable. 1.ReadUncommitted allows reading of uncommitted data, which may cause dirty reading. 2. ReadCommitted avoids dirty reading, but non-repeatable reading may occur. 3.RepeatableRead is the default level, avoiding dirty reading and non-repeatable reading, but phantom reading may occur. 4. Serializable avoids all concurrency problems but reduces concurrency. Choosing the appropriate isolation level requires balancing data consistency and performance requirements.

MySQL is suitable for web applications and content management systems and is popular for its open source, high performance and ease of use. 1) Compared with PostgreSQL, MySQL performs better in simple queries and high concurrent read operations. 2) Compared with Oracle, MySQL is more popular among small and medium-sized enterprises because of its open source and low cost. 3) Compared with Microsoft SQL Server, MySQL is more suitable for cross-platform applications. 4) Unlike MongoDB, MySQL is more suitable for structured data and transaction processing.

MySQL index cardinality has a significant impact on query performance: 1. High cardinality index can more effectively narrow the data range and improve query efficiency; 2. Low cardinality index may lead to full table scanning and reduce query performance; 3. In joint index, high cardinality sequences should be placed in front to optimize query.

The MySQL learning path includes basic knowledge, core concepts, usage examples, and optimization techniques. 1) Understand basic concepts such as tables, rows, columns, and SQL queries. 2) Learn the definition, working principles and advantages of MySQL. 3) Master basic CRUD operations and advanced usage, such as indexes and stored procedures. 4) Familiar with common error debugging and performance optimization suggestions, such as rational use of indexes and optimization queries. Through these steps, you will have a full grasp of the use and optimization of MySQL.

MySQL's real-world applications include basic database design and complex query optimization. 1) Basic usage: used to store and manage user data, such as inserting, querying, updating and deleting user information. 2) Advanced usage: Handle complex business logic, such as order and inventory management of e-commerce platforms. 3) Performance optimization: Improve performance by rationally using indexes, partition tables and query caches.


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