sql多表查询有很多种方法,如有自然连接 INNER JOIN,外边查询LEFT JOIN,交叉查询JOIN,交叉连接JOIN等join on left on 等多的是哦。
sql多表查询语句与方法
sql多表查询有很多种方法,如有自然连接 INNER JOIN,外边查询LEFT JOIN,交叉查询
JOIN,交叉连接JOIN等join on left on 等多的是哦。
下面使用等值连接列出authors和publishers表中位于同一城市的作者和出版社:
Select *
FROM authors AS a INNER JOIN publishers AS p
ON a.city=p.city
又如使用自然连接,在选择列表中删除authors 和publishers 表中重复列(city和state)
:
Select a.*,p.pub_id,p.pub_name,p.country
FROM authors AS a INNER JOIN publishers AS p
ON a.city=p.city
外边查询
Select a.*,b.* FROM luntan LEFT JOIN usertable as b
ON a.username=b.username
下面使用全外连接将city表中的所有作者以及user表中的所有作者,以及他们所在的城市
:
Select a.*,b.*
FROM city as a FULL OUTER JOIN user as b
ON a.username=b.username
交叉查询
交叉连接不带Where 子句,它返回被连接的两个表所有数据行的笛卡尔积,返回到结果集
合中的数据行数等于第一个表中符合查询条件的数据行数乘以第二个表中符合查询条件的
数据行数。例,titles表中有6类图书,而publishers表中有8家出版社,则下列交叉连接
检索到的记录数将等于6*8=48行。
Select type,pub_name
FROM titles CROSS JOIN publishers
ORDER BY type
使用左外连接将论坛内容和作者信息连接起来:
Select a.*,b.* FROM luntan LEFT JOIN usertable as b
ON a.username=b.username
下面使用全外连接将city表中的所有作者以及user表中的所有作者,以及他们所在的城市
:
Select a.*,b.*
FROM city as a FULL OUTER JOIN user as b
ON a.username=b.username
(三)交叉连接
交叉连接不带Where 子句,它返回被连接的两个表所有数据行的笛卡尔积,返回到结果集
合中的数据行数等于第一个表中符合查询条件的数据行数乘以第二个表中符合查询条件的
数据行数。
例,titles表中有6类图书,而publishers表中有8家出版社,则下列交叉连接检索到的记
录数将等
于6*8=48行。
Select type,pub_name
FROM titles CROSS JOIN publishers
orDER BY type
下面我们来看一个我写的多表查询吧
$sql = "Select zgy_jobs_faces.*,zgy_jobs_index.*,zgy_jobs_option.* from
zgy_jobs_faces,zgy_jobs_index,zgy_jobs_option where zgy_jobs_option.mulplace
='$city' and zgy_jobs_faces.djobskinds ='$parttime' and zgy_jobs_faces.cid=
zgy_jobs_option.cid and zgy_jobs_option.cid = zgy_jobs_index.cid group by
zgy_jobs_faces.jname order by zgy_jobs_option.jid desc limit 0,30";
用group by 过滤重复的数据
关键词:sql查询,多表查询

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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