该死的mysql没有提供unix时间戳的专门处理函数,所以,如果遇到时间分组,而你用的又是整型unix时间戳,则只有转化为mysql的其他日期类型! FROM_UNIXTIM()将unix时间戳转为datetime等日期型! 一、年度查询 查询 本年度的数据 SELECT * FROM blog_article W
该死的mysql没有提供unix时间戳的专门处理函数,所以,如果遇到时间分组,而你用的又是整型unix时间戳,则只有转化为mysql的其他日期类型!
FROM_UNIXTIM()将unix时间戳转为datetime等日期型!
一、年度查询
查询 本年度的数据
SELECT *
FROM blog_article
WHERE year( FROM_UNIXTIME( BlogCreateTime ) ) = year( curdate( ))
二、查询季度数据
查询数据附带季度数
SELECT ArticleId, quarter( FROM_UNIXTIME( `BlogCreateTime` ) )
FROM `blog_article`
其他的同前面部分:查询 本季度的数据
SELECT
*
FROM blog_article
WHERE quarter( FROM_UNIXTIME( BlogCreateTime ) ) = quarter( curdate( ))
三、查询月度数据
本月统计(MySQL)
select * from booking where month(booking_time) =
month(curdate()) and year(booking_time) = year(curdate())
本周统计(MySQL)
select * from spf_booking where month(booking_time) =
month(curdate()) and week(booking_time) = week(curdate())
四、时间段
N天内记录
WHERE TO_DAYS(NOW()) - TO_DAYS(时间字段) N
当天的记录
where date(时间字段)=date(now())
或
where to_days(时间字段) = to_days(now());
查询一周:
select * from table where DATE_SUB(CURDATE(), INTERVAL 7 DAY) date(column_time);
查询一个月:
select * from table where DATE_SUB(CURDATE(), INTERVAL INTERVAL 1 MONTH) date(column_time);
查询'06-03'到'07-08'这个时间段内所有过生日的会员:
Select * From user Where
DATE_FORMAT(birthday,'%m-%d') >= '06-03' and DATE_FORMAT(birthday,'%m-%d')
统计一季度数据,表时间字段为:savetime
group by concat(date_format(savetime, '%Y '),FLOOR((date_format(savetime, '%m ')+2)/3))
或
select YEAR(savetime)*10+((MONTH(savetime)-1)
DIV 3) +1,count(*)
from yourTable
group by YEAR(savetime)*10+((MONTH(savetime)-1)
DIV 3) +1;
五、分组查询
1、年度分组
2、月度分组
3、先按年度分组,再按月度分组
4、按年月分组
SELECT count(ArticleId), date_format(FROM_UNIXTIME( `BlogCreateTime`),'%y%m') sdate FROM `blog_article` group by sdate
结果:
count( ArticleId ) sdate
17 0901
11 0902
5 0903
6 0904
2 0905
1 0907
12 0908
6 0909
11 0910
3 0911

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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