ORACLE是ORACLE公司的数据产品,支持海量数据存储,支持分布式布暑,支持多用户,跨平台,数据安全完整性控制性能优越,是一个OR
1、对数据库SQL2005、Oracle熟悉吗?
SQL2005是微软公司的数据库产品。是一个RDBMS数据库,一般应用在一些中型数据库的应用,不能跨平台。
ORACLE是ORACLE公司的数据产品,支持海量数据存储,支持分布式布暑,支持多用户,,跨平台,数据安全完整性控制性能优越,是一个ORDBMS,一般用在大型公司。
2、能不能设计数据库?如何实现数据库导入与导出的更新 使用POWERDISINE工具的使用,一般满足第三范式就可以了。EXP与IMP数据库的逻辑导入与导出
3、如何只显示重复数据,或不显示重复数据
显示重复:
select * from tablename group by id having count(*)>1
不显示重复:
select * from tablename group by id having count(*)=1
4、什么是数据库的映射
就是将数据库的表与字段对应到模型层类名与属性的过程
5、写分页有哪些方法,你一般用什么方法?用SQL语句写一个分页?
如何用存储过程写分页?
在SQLSERVER中使用TOP分页,在ORACLE中用ROWNUM,或分析函数ROW_NUMBER 使用TOP: select top 20,n.* from tablename n minus select top 10,m.* from tablename m
使用分析函数:
select * from (select n.*,row_number() over(order by columnname) num from tablename n) where num>=10 and num <=20;
使用过程时,只要将分页的范围用两个参数就可以实现。在ORACLE中,要将过程封装在包里,还要用动态游标变量才能实现数据集的返回。
6、ORACLE中左连接与右连接
左连接:LEFT JOIN 右连接:RIGHT JOIN
select n.column,m.column from tablename1 n left join tablename2 m on n.columnname=m.columnname
用WHERE实现:
select n.column,m.column from tablename1 n, tablename2 m where n.columnname( )=m.columnname
7、什么是反射、序列化、反序列化?事务有几种级别?
反射是在程序运行时动态访问DDL的一种方式。序列化是将对象对二进制、XML等方式直接向文件的存储。反序列化是将存储到文件的对象取出的过程。事务的级别的三种:页面级、应用程序级、数据库级。
【专题推荐】:2020年oracle面试题汇总(最新)

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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