直奔主题,如下SQL语句(via:女孩礼物网): SELECT COUNT(* ) AS COUNT,REQUEST,METHOD FROM REQUESTMETH GROUP BY REQUEST,METHOD HAVING (REQUEST = ' FC.OCEAN.JOB.SERVER.CBIZOZBKHEADER ' OR REQUEST= ' FC.Ocean.Job.Server.CBizOzDocHeader ' )AND COU
直奔主题,如下SQL语句(via:女孩礼物网):
SELECT COUNT(*<span>) AS COUNT,REQUEST,METHOD FROM REQUESTMETH GROUP BY REQUEST,METHOD HAVING (REQUEST </span>=<span>'</span><span>FC.OCEAN.JOB.SERVER.CBIZOZBKHEADER</span><span>'</span> OR REQUEST=<span>'</span><span>FC.Ocean.Job.Server.CBizOzDocHeader</span><span>'</span><span>) AND COUNT(</span>*) ><span>3</span><span> ORDER BY REQUEST</span>
注意事项:
HAVING后的条件不能用别名COUNT>3 必须使用COUNT(*) >3,否则报:列名 'COUNT' 无效。
having 子句中的每一个元素并不一定要出现在select列表中
如果把该语句写成:
SELECT COUNT(*<span>) AS COUNT,REQUEST,METHOD FROM REQUESTMETH GROUP BY REQUEST ORDER BY REQUEST</span>
那么将报:
选择列表中的列 'REQUESTMETH.method' 无效,因为该列没有包含在聚合函数或 GROUP BY 子句中。
注意:
1、使用GROUP BY 子句时,SELECT 列表中的非汇总列必须为GROUP BY 列表中的项。
2、分组时,所有的NULL值分为一组。
3、GROUP BY 列表中一般不允许出现复杂的表达试、显示标题以及SELECT列表中的位置标号。
如:
SELECT REQUEST,METHOD, COUNT(*<span>) AS COUNT FROM REQUESTMETH GROUP BY REQUEST,</span><span>2</span> ORDER BY REQUEST
错误信息为:每个 GROUP BY 表达式都必须包含至少一个列引用。
GROUP BY 中使用 ORDER BY注意事项:
SELECT COUNT(*) AS COUNT FROM REQUESTMETH GROUP BY REQUEST,METHOD ORDER BY REQUEST,METHOD
--这样是允许的, ORDER BY后面的字段包含在GROUP BY 子句中
SELECT COUNT(*) AS COUNTS FROM REQUESTMETH GROUP BY REQUEST ORDER BY COUNT(*) DESC
--这样是允许的,ORDER BY后面的字段包含在聚合函数中,结果集同下面语句一样
SELECT COUNT(*) AS COUNTS FROM REQUESTMETH GROUP BY REQUEST ORDER BY COUNTS DESC
--这样是允许的,区别于HAVING,HAVING后不允许跟聚集函数的别名作为过滤条件
SELECT COUNT(*) AS COUNTS FROM REQUESTMETH GROUP BY REQUEST ORDER BY METHOD
--这样是错误的:ORDER BY 子句中的列 "REQUESTMETH.method" 无效,因为该列没有包含在聚合函数或 GROUP BY 子句中。
SELECT DISTINCT 中使用 ORDER BY注意事项:
SELECT DISTINCT BOOKID FROM BOOK ORDER BY BOOKNAME
以上语句将报:
--如果指定了SELECT DISTINCT,那么ORDER BY 子句中的项就必须出现在选择列表中。
因为以上语句类似
SELECT BOOKID FROM BOOK GROUP BY BOOKID ORDER BY BOOKNAME
其实错误信息也为:
--ORDER BY子句中的列"BOOK.BookName" 无效,因为该列没有包含在聚合函数或GROUP BY 子句中。
应该改为:
SELECT DISTINCT BOOKID,BOOKNAME FROM BOOK ORDER BY BOOKNAME
<span>SELECT DISTINCT BOOKID,BOOKNAME FROM BOOK<br></span>
SELECT BOOKID,BOOKNAME FROM BOOK GROUP BY BOOKID,BOOKNAME
以上两句查询结果是一致的,DISTINCT的语句其实完全可以等效的转换为GROUP BY语句

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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