本文为博主原创,允许转载,但请声明原文地址:http://www.coselding.cn/blog/8/8-142.html HQL语法结构类SQL语句, Query query = session.createQuery(String HQL); 通过一个HQL查询语句得到一个Query的对象,可以通过这个对象得到HQL语句的查询结果集 查
本文为博主原创,允许转载,但请声明原文地址:http://www.coselding.cn/blog/8/8-142.html
- HQL语法结构类似SQL语句,
- Query query = session.createQuery(String HQL); 通过一个HQL查询语句得到一个Query的对象,可以通过这个对象得到HQL语句的查询结果集
- 查询支持内链接,左右外连接,支持对Hibernate实体类的直接查询,以及对A实体类中的其他B实体类成员直接用”.”来作为A实体类的列来调用(已设置关联关系);
- From,select,where,order by,group by,子查询都和SQL一样,具体查询文档
- ?序号是从0位开始的
- Query.list的数据用完才能session.close()
- Query支持正常的SQL、HQL、EJBQL。功能强弱:NativeSQL>HQL>EJBQL>QBC>QBE。
- HQL占位符:”:参数名”或者”?”,使用setInteger等方法直接替换占位符中的参数。
- 分页:setMaxResults:设置每页条数,setFirstResult设置从第几条开始。
- 可以像SQL一样返回每个列的属性值,每个属性值以Object返回,形成一个Object数组。也可以把这些返回的列值合成一个临时的包装对象进行保存,在HQL写”new 类限定名”。
- HQL用”join”进行导航连接,join t.topic不能用join Topic,因为要设定t中的哪个对象和Topic进行连接。
- query.uniqueResult():返回查询唯一对象。
- count(*)返回long类型,用query.uniqueResult()。
- 聚合函数、between…and、in、not null、is empty、is not empty、like、exists、not exists。Exists的执行效率比in高。
- EJBQL常用函数,变大小写、连接字符串、去空格、平均数、求和等函数。(不重要)
- 日期直接用>、
- group by、having、子查询、ALL函数。
- NameQuery:将查询命名起来,之后直接用key调用,@NameQueries定义命名查询,将查询语句集中化管理。
- createSQLQuery():使用正常的SQL语句查询,返回SQLQuery,@NameNativeQueries。
- QBC(Query By Criterial):Criteria约束集合,用Restrictions产生查询约束条件,即where后面的子句,相当于把SQL语句变得面向对象化!!!DetachedCriteria:创建好再绑定session的对象,可以脱离session管理。
- QBE(Query By Example):Example e = Example.create(Object obj);产生一个约束条件对象,可以当作Criteria的约束对象加入进去,使面向对象更彻底。
本文为博主原创,允许转载,但请声明原文地址:http://www.coselding.cn/blog/8/8-142.html

Stored procedures are precompiled SQL statements in MySQL for improving performance and simplifying complex operations. 1. Improve performance: After the first compilation, subsequent calls do not need to be recompiled. 2. Improve security: Restrict data table access through permission control. 3. Simplify complex operations: combine multiple SQL statements to simplify application layer logic.

The working principle of MySQL query cache is to store the results of SELECT query, and when the same query is executed again, the cached results are directly returned. 1) Query cache improves database reading performance and finds cached results through hash values. 2) Simple configuration, set query_cache_type and query_cache_size in MySQL configuration file. 3) Use the SQL_NO_CACHE keyword to disable the cache of specific queries. 4) In high-frequency update environments, query cache may cause performance bottlenecks and needs to be optimized for use through monitoring and adjustment of parameters.

The reasons why MySQL is widely used in various projects include: 1. High performance and scalability, supporting multiple storage engines; 2. Easy to use and maintain, simple configuration and rich tools; 3. Rich ecosystem, attracting a large number of community and third-party tool support; 4. Cross-platform support, suitable for multiple operating systems.

The steps for upgrading MySQL database include: 1. Backup the database, 2. Stop the current MySQL service, 3. Install the new version of MySQL, 4. Start the new version of MySQL service, 5. Recover the database. Compatibility issues are required during the upgrade process, and advanced tools such as PerconaToolkit can be used for testing and optimization.

MySQL backup policies include logical backup, physical backup, incremental backup, replication-based backup, and cloud backup. 1. Logical backup uses mysqldump to export database structure and data, which is suitable for small databases and version migrations. 2. Physical backups are fast and comprehensive by copying data files, but require database consistency. 3. Incremental backup uses binary logging to record changes, which is suitable for large databases. 4. Replication-based backup reduces the impact on the production system by backing up from the server. 5. Cloud backups such as AmazonRDS provide automation solutions, but costs and control need to be considered. When selecting a policy, database size, downtime tolerance, recovery time, and recovery point goals should be considered.

MySQLclusteringenhancesdatabaserobustnessandscalabilitybydistributingdataacrossmultiplenodes.ItusestheNDBenginefordatareplicationandfaulttolerance,ensuringhighavailability.Setupinvolvesconfiguringmanagement,data,andSQLnodes,withcarefulmonitoringandpe

Optimizing database schema design in MySQL can improve performance through the following steps: 1. Index optimization: Create indexes on common query columns, balancing the overhead of query and inserting updates. 2. Table structure optimization: Reduce data redundancy through normalization or anti-normalization and improve access efficiency. 3. Data type selection: Use appropriate data types, such as INT instead of VARCHAR, to reduce storage space. 4. Partitioning and sub-table: For large data volumes, use partitioning and sub-table to disperse data to improve query and maintenance efficiency.

TooptimizeMySQLperformance,followthesesteps:1)Implementproperindexingtospeedupqueries,2)UseEXPLAINtoanalyzeandoptimizequeryperformance,3)Adjustserverconfigurationsettingslikeinnodb_buffer_pool_sizeandmax_connections,4)Usepartitioningforlargetablestoi


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