sql数据分组最大值,第一条,前三条方法总结,三个实例都比较简单都是根据GROUP BY出来的数据进行一些简单操作即可,有需要的同学可参考一下.
取分组前三第记录
代码如下 | 复制代码 |
SELECT 课程, |
取分组第一第记录
例
表Demo的数据都是字符串类型,按照顺序的时间Time(也是字符串)排序的记录如下:
Num Name Time
1 a 2009/05/01
1 a 2009/05/02
1 a 2009/05/03
2 b 2009/05/04
2 b 2009/05/05
3 c 2009/05/06
3 c 2009/05/07
5 e 2009/05/08
1 a 2009/05/09
1 a 2009/05/10
我想输出类似按照Num分组的每组的第一条数据记录,比如上面的记录我想操作后得到如下记录:
Num Name Time
1 a 2009/05/01
2 b 2009/05/04
3 c 2009/05/06
5 e 2009/05/08
1 a 2009/05/09
sql代码
代码如下 | 复制代码 |
declare @Tab table select * from @Tab t where not exists(select 1 from @Tab where num=t.num and [time] /* (4 行受影响) |
取分组最大记录
示例:test 表 a b c
1 5 abc
2 6 bcd
1 7 ade
2 8 adc
若取按a列分组后,b列最大,的所有列的记录:
result a b c
1 6 bcd
2 8 adc
可以使用如下语句:
代码如下 | 复制代码 |
select * from test where b in (select max(id) from test group by a) 适用于所有数据库: select t1.a,t1.b,t1.c from test t1 inner join (seelct a,max(b) as b from test group by a) t2 on t1.a=t2.a and t1.b=t2.b 适用于所有数据库: select a,b,c from( select a,b,c ,row_number()over(partition by a order by b desc) rn from test ) where rn=1 |

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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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