-- 创建表语句 ORACLE: create table _table_name( column1 varchar2(10) primary key, column2 number(5) not null, memo varchar2(100) ); comment on column _table_name.column1 is '这是column1的注释'; SQLSERVER: create table _table_name( column1
-- 创建表语句
ORACLE:
create table _table_name(
column1 varchar2(10) primary key,
column2 number(5) not null,
memo varchar2(100)
);
comment on column _table_name.column1
is '这是column1的注释';
SQLSERVER:
create table _table_name(
column1 varchar(10) primary key,
column2 int not null,
memo varchar(100)
);
MYSQL:
create table `_table_name`
(
`column1` VARCHAR(32) primary key COMMENT '注释',
`column2` VARCHAR(30) not null COMMENT '注释',
PRIMARY KEY (`column1`) -- 主键定义也可放在此处
)ENGINE=InnoDB DEFAULT CHARSET=gbk;
-- 修改字段语句
ORACLE:
alter table _table_name add/modify column_name varchar2(505);
alter table _table_name drop column column_name;
SQLSERVER:
alter table _table_name add column_name VARCHAR(20);
alter table _table_name alter column column_name varchar(2000);
alter table _table_name drop column column_name;
MYSQL:
alter table _table_name add/modify column column_name varchar(2000);
alter table _table_name drop `column_name`;
-- 创建删除索引语句,,索引只能删除重建,不能修改
ORACLE:
-- 主键索引
alter table _table_name add constraint index_name primary key (column_name) using index tablespace URMSPK;
-- 普通列索引
create index index_name$cl2 on _table_name (column1_name,column2_name DESC) tablespace URMSIDX;
-- 删除索引
drop index index_name;
SQLSERVER:
-- 主键索引
Alter table _table_name add primary key(column_name);
alter table _table_name add constraint index_name primary key CLUSTERED (column_name)
WITH (
PAD_INDEX = OFF,
IGNORE_DUP_KEY = OFF,
STATISTICS_NORECOMPUTE = OFF,
ALLOW_ROW_LOCKS = ON,
ALLOW_PAGE_LOCKS = ON)
ON URMSPK
go
-- 普通列索引 ,非唯一索引需要去掉 UNIQUE NONCLUSTERED 关键字
CREATE UNIQUE NONCLUSTERED INDEX [index_name] ON [_table_name]
([ORGRANGE], [SHOWORDER] DESC)
WITH (
PAD_INDEX = OFF,
IGNORE_DUP_KEY = OFF,
DROP_EXISTING = OFF,
STATISTICS_NORECOMPUTE = OFF,
SORT_IN_TEMPDB = OFF,
ONLINE = OFF,
ALLOW_ROW_LOCKS = ON,
ALLOW_PAGE_LOCKS = ON)
ON [URMSIDX]
GO
-- 删除索引
drop index _table_name.idxname;
MYSQL:
-- 普通索引
ALTER TABLE _table_name ADD INDEX index_name (APPID, CREATEDATE DESC);
-- 唯一索引
ALTER TABLE _table_name ADD UNIQUE index_name (column_list);
-- 主键索引
ALTER TABLE _table_name ADD PRIMARY KEY index_name (column_list);
-- 删除索引
alter table _table_name drop index index_name;
-- 插入语句
ORACLE:
insert into _table_name (column_list) values ('value_list');
SQLSERVER:
insert into _table_name (column_list) values ('value_list');
MYSQL:
insert into UMFRAMESET (`column_list`) values ('value_list'),('value_list2');-- 可以插入多条记录
-- 修改表名
ORACLE:
alter table leave rename to Leave01;
SQLSERVER:
EXEC sp_rename leave,leave01;
MYSQL:
alter table `leave` RENAME to `leave01`;
-- 删除表语句
ORACLE:
drop table table_name;
SQLSERVER:
drop table table_name;
MYSQL:
drop table table_name
-- 删除所有表的语句
SQLSERVER:
exec sp_msforeachtable 'drop table ?';
-- 修改列名
SQLSERVER:
EXEC sp_rename '表名.列名','新列名','column';
-- 删除记录
ORACLE:
delete (from) tablename where _column_name=?;

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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