1.组函数用法规则
mysql中组函数在select语句中可以随意使用,但在oracle中如果查询语句中有组函数,那其他列名必须是组函数处理过的,或者是group by子句中的列否则报错
eg:select name,count(money) from user;这个放在mysql中没有问题在oracle中就有问题了
2.自动增长的数据类型处理
MYSQL有自动增长的数据类型,插入记录时不用操作此字段,会自动获得数据值。ORACLE没有自动增长的数据类型,需要建立一个自动增长的序列号,插入记录时要把序列号的下一个值赋于此字段。
CREATE SEQUENCE序列号的名称(最好是表名+序列号标记)INCREMENT BY 1 START WITH 1 MAXVALUE 99999 CYCLE NOCACHE;
其中最大的值按字段的长度来定,如果定义的自动增长的序列号NUMBER(6),最大值为999999
INSERT语句插入这个字段值为:序列号的名称.NEXTVAL
3.单引号的处理
MYSQL里可以用双引号包起字符串,ORACLE里只可以用单引号包起字符串。在插入和修改字符串前必须做单引号的替换:把所有出现的一个单引号替换成两个单引号。
4.翻页的SQL语句的处理
MYSQL处理翻页的SQL语句比较简单,用LIMIT开始位置,记录个数;PHP里还可以用SEEK定位到结果集的位置。ORACLE处理翻页的SQL语句就比较繁琐了。每个结果集只有一个ROWNUM字段标明它的位置,并且只能用ROWNUM80。
以下是经过分析后较好的两种ORACLE翻页SQL语句(ID是唯一关键字的字段名):
语句一:
SELECT ID, [FIELD_NAME,...] FROM TABLE_NAME WHERE ID IN ( SELECT ID FROM (SELECT ROWNUM AS NUMROW, ID FROM TABLE_NAME WHERE 条件1 ORDER BY 条件2) WHERE NUMROW > 80 AND NUMROW 语句二:
SELECT * FROM (( SELECT ROWNUM AS NUMROW, c.* from (select [FIELD_NAME,...] FROM TABLE_NAME WHERE 条件1 ORDER BY 条件2) c) WHERE NUMROW > 80 AND NUMROW
5.长字符串的处理
长字符串的处理ORACLE也有它特殊的地方。INSERT和UPDATE时最大可操作的字符串长度小于等于4000个单字节,如果要插入更长的字符串,请考虑字段用CLOB类型,方法借用ORACLE里自带的DBMS_LOB程序包。插入修改记录前一定要做进行非空和长度判断,不能为空的字段值和超出长度字段值都应该提出警告,返回上次操作。
6.日期字段的处理
MYSQL日期字段分DATE和TIME两种,ORACLE日期字段只有DATE,包含年月日时分秒信息,用当前数据库的系统时间为SYSDATE,精确到秒,或者用字符串转换成日期型函数TO_DATE(‘2001-08-01','YYYY-MM-DD')年-月-日24小时:分钟:秒的格式YYYY-MM-DD HH24:MI:SS TO_DATE()还有很多种日期格式,可以参看ORACLE DOC.日期型字段转换成字符串函数TO_CHAR(‘2001-08-01','YYYY-MM-DD HH24:MI:SS')
日期字段的数学运算公式有很大的不同。MYSQL找到离当前时间7天用DATE_FIELD_NAME > SUBDATE(NOW(),INTERVAL 7 DAY)ORACLE找到离当前时间7天用 DATE_FIELD_NAME >SYSDATE

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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