首先对于MySQL的DISTINCT的关键字的一些用法:
1.在count 不重复的记录的时候能用到,比如SELECT COUNT( DISTINCT id ) FROM tablename;就是计算talbebname表中id不同的记录有多少条。
2,在需要返回记录不同的id的具体值的时候可以用,比如SELECT DISTINCT id FROM tablename;返回talbebname表中不同的id的具体的值。
3.上面的情况2对于需要返回mysql表中2列以上的结果时会有歧义,比如SELECT DISTINCT id, type FROM tablename;实际上返回的是 id与type同时不相同的结果,也就是DISTINCT同时作用了两个字段,必须得id与tyoe都相同的才被排除了,与我们期望的结果不一样。
4.这时候可以考虑使用group_concat函数来进行排除,不过这个mysql函数是在mysql4.1以上才支持的。
5.其实还有另外一种解决方式,就是使用,SELECT id, type, count(DISTINCT id) FROM tablename,虽然这样的返回结果多了一列无用的count数据(或许你就需要这个我说的无用数据),返回的结果是只有id不同的所有结果和上面的4类型可以互补使用,就是看你需要什么样的数据了。
DISTINCT的效率:
SELECT id, type, count(DISTINCT id) FROM tablename;虽然这样的返回结果多了一列无用的count数据(或许你就需要这个我说的无用数据),SELECT id, type from tablename group by id;这样貌似也可以,用distinct的时候,如果它有索引,mysql会把它转成group by的方式执行。
MySQL数据库对于COUNT(*)的不同处理会造成不同的结果,比如,
执行:SELECT COUNT(*) FROM tablename;即使对于千万级别的数据mysql也能非常迅速的返回结果。
执行: SELECT COUNT(*) FROM tablename WHERE…..;mysql的查询时间开始攀升。
网上查资料得知:当没有WHERE语句对于整个mysql的表进行count运算的时候,MyISAM类型的表中保存有总的行数,而当添加有WHERE限定语句的时候Mysql需要对整个表进行检索,从而得出count的数值,因此加上where条件的查询速度就会很慢了。
以上关于MySQL数据库的distinct以及count(*)的使用就介绍到这里了,希望本次的介绍能够带给您一些收获。

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.

MySQL and SQL are essential skills for developers. 1.MySQL is an open source relational database management system, and SQL is the standard language used to manage and operate databases. 2.MySQL supports multiple storage engines through efficient data storage and retrieval functions, and SQL completes complex data operations through simple statements. 3. Examples of usage include basic queries and advanced queries, such as filtering and sorting by condition. 4. Common errors include syntax errors and performance issues, which can be optimized by checking SQL statements and using EXPLAIN commands. 5. Performance optimization techniques include using indexes, avoiding full table scanning, optimizing JOIN operations and improving code readability.


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