-- 查询 当天: select * from info where DateDiff(dd,datetime,getdate())=0 -- 查询 24小时内的: select * from info where DateDiff(hh,datetime,getDate())=24 --本月记录 SELECT * FROM 表 WHERE datediff(month,[dateadd],getdate())=0 --本周记录 SE
--查询当天:
select * from info where DateDiff(dd,datetime,getdate())=0
--查询24小时内的:
select * from info where DateDiff(hh,datetime,getDate())
--本月记录
SELECT * FROM 表 WHERE datediff(month,[dateadd],getdate())=0
--本周记录
SELECT * FROM 表 WHERE datediff(week,[dateadd],getdate())=0
sql server中的时间函数
1. 当前系统日期、时间
select getdate()
2. dateadd 在向指定日期加上一段时间的基础上,返回新的 datetime 值
例如:向日期加上2天
select dateadd(day,2,'2004-10-15') --返回:2004-10-17 00:00:00.000
3. datediff 返回跨两个指定日期的日期和时间边界数。
select datediff(day,'2004-09-01','2004-09-18') --返回:17
4. datepart 返回代表指定日期的指定日期部分的整数。
SELECT DATEPART(month, '2004-10-15') --返回 10
5. datename 返回代表指定日期的指定日期部分的字符串
SELECT datename(weekday, '2004-10-15') --返回:星期五
6. day(), month(),year() --可以与datepart对照一下
select 当前日期=convert(varchar(10),getdate(),120)
,当前时间=convert(varchar(8),getdate(),114)
select datename(dw,'2004-10-15')
select 本年第多少周=datename(week,'2004-10-15')
,今天是周几=datename(weekday,'2004-10-15')
函数 参数/功能
GetDate( ) 返回系统目前的日期与时间
DateDiff (interval,date1,date2) 以interval 指定的方式,返回date2 与date1两个日期之间的差值 date2-date1
DateAdd (interval,number,date) 以interval指定的方式,加上number之后的日期
DatePart (interval,date) 返回日期date中,interval指定部分所对应的整数值
DateName (interval,date) 返回日期date中,interval指定部分所对应的字符串名称
参数 interval的设定值如下:
值 缩 写(Sql Server) Access 和 ASP 说明
Year Yy yyyy 年 1753 ~ 9999
Quarter Qq q 季 1 ~ 4
Month Mm m 月1 ~ 12
Day of year Dy y 一年的日数,一年中的第几日 1-366
Day Dd d 日,1-31
Weekday Dw w 一周的日数,一周中的第几日 1-7
Week Wk ww 周,一年中的第几周 0 ~ 51
Hour Hh h 时0 ~ 23
Minute Mi n 分钟0 ~ 59
Second Ss s 秒 0 ~ 59
Millisecond Ms - 毫秒 0 ~ 999
access 和 asp 中用date()和now()取得系统日期时间;其中DateDiff,DateAdd,DatePart也同是能用于Access和asp中,这些函数的用法也类似
举例:
1.GetDate() 用于sql server :select GetDate()
2.DateDiff('s','2005-07-20','2005-7-25 22:56:32')返回值为 514592 秒
DateDiff('d','2005-07-20','2005-7-25 22:56:32')返回值为 5 天
3.DatePart('w','2005-7-25 22:56:32')返回值为 2 即星期一(周日为1,周六为7)
DatePart('d','2005-7-25 22:56:32')返回值为 25即25号
DatePart('y','2005-7-25 22:56:32')返回值为 206即这一年中第206天
DatePart('yyyy','2005-7-25 22:56:32')返回值为 2005即2005年

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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