一、DataBase保存数据,以表的形式表现数据二、SQLSQL(structure query language 结构化查询语言),是操作关系型数据库中的对象
一、DataBase
保存数据,以表的形式表现数据
二、SQL
SQL(structure query language 结构化查询语言),是操作关系型数据库中的对象
DDL(data definition language 数据定义语言),用于建表或删表操作,以及对表约束进行修改。
create table , alter table , drop table 对表结构的增、删、改操作。
DML(Data manipulation language 数据操作语言),向表中插入纪录,修改纪录
insert , update , delete
transaction,事务控制语言,由DML语句组成的,commit; ,rollback,savepoint
select 查询语句
dcl 数据控制语言,授权语句 grant,revoke
alter session alter system
三、Oracle
DB (database)
DBMS 数据库管理系统(database management system)
DBA 数据库管理员
数据库管理系统有:ms微软的sql server,
IBM的db2,imformix,
mysql,
oracle的oracle920,
sybase的ase
四、相关操作
echo $PATH 配置环境变量,加/oracledata/oracle/product/9.2.0/bin,把oracle命令加上
echo $ORACLE_SID 查看Oracle数据库的实例,实例是访问数据库的方法。缺省端口号是:1521
1、sqlplus 访问数据库命令(本地访问/远程访问),和数据库建立连接的命令,是数据库操作的环境
sqlplus 用户名/密码
2、show user 显示当前用户的用户名
改变身份可以直接connect 用户名/密码 --- 这个是sqlplus命令
在sqlplus中可以使用 ! 可以在shell和sqlplus间切换,!shell命令可以在sqlplus中使用shell命令。
实际上是sqlplus开了子进程来执行shell命令。
3、Oracle数据库中的表分两类:用户表(用户使用操作的表),系统表(数据库系统维护的表,也叫数据字典)
对用户表的DDL操作触发了对系统表的DML操作!

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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