1.1.1 摘要 现在,我们经常使用的微博、微信或其他应用都有异步加载功能,简而言之,就是我们在刷微博或微信时,移动到界面的顶端或低端后程序通过异步的方式进行加载数据,这种方式加快了数据的加载速度,由于它每次只加载一部分数据,当我们有大量的数据,
1.1.1 摘要
现在,我们经常使用的微博、微信或其他应用都有异步加载功能,简而言之,就是我们在刷微博或微信时,移动到界面的顶端或低端后程序通过异步的方式进行加载数据,这种方式加快了数据的加载速度,由于它每次只加载一部分数据,当我们有大量的数据,但不能显示所有,这时我们可以考虑使用异步方式加载数据。
数据异步加载可以发生在用户点击“查看更多”按钮或滚动条滚动到窗口的底部时自动加载;在接下来的博文中,我们将介绍如何实现自动加载更多的功能。
本文目录图1 微博加载更多功能
1.1.2 正文假设,在我们的数据库中存放着用户的消息数据,现在,我们需要通过Web Service形式开放API接口让客户端调用,当然我们也可以使用一般处理程序(ASHX文件)让客户端调用(具体请参考这里)。
数据表首先,我们在数据库中创建数据表T_Paginate,,它包含三个字段ID、Name和Message,其中ID是自增值。
-- ============================================= -- Author: JKhuang -- Create date: 10/28/2013 -- Description: A table stores the user information. -- ============================================= CREATE TABLE [dbo].[T_Paginate]( [ID] [int] IDENTITY(1,1) NOT NULL, [Name] [varchar](60) COLLATE Chinese_PRC_CI_AS NULL, [Message] [text] COLLATE Chinese_PRC_CI_AS NULL, CONSTRAINT [PK_T_Paginate] PRIMARY KEY CLUSTERED ( [ID] ASC IGNORE_DUP_KEY [PRIMARY] ) ON [PRIMARY] TEXTIMAGE_ON [PRIMARY]图2 数据表T_Paginate
数据对象模型我们根据数据表T_Paginate定义数据对象模型Message,它包含三个字段分别是:Id、Name和Comment,具体定义如下:
///现在,我们需要实现方法GetListMessages(),它根据客户端传递来的分页数来获取相应的分页数据并且通过JSON格式返回给客户端,在实现GetListMessages()方法之前,我们先介绍数据分页查询的方法。
在Mysql数据库中,我们可以使用limit函数实现数据分页查询,但在SQL Server中没有提供类似的函数,那么,我们可以发挥人的主观能动——自己实现一个吧,具体实现如下:
-- ============================================= -- Author: JKhuang -- Create date: 10/26/2013 -- Description: Creates a pagination function -- ============================================= Declare @Start AS INT Declare @Offset AS INT ;WITH Results_CTE AS ( ROW_NUMBERID) AS RowNum FROM T_Paginate WITH(NOLOCK)) Results_CTE WHERE RowNum BETWEEN @Start AND @Offset上面我们定义了公用表表达式Results_CTE,它获取T_Paginate表中的数据并且根据ID值由小到大排序,然后根据该顺序分配ROW_NUMBER值,其中@Start和@Offset是要查询的数据范围。
接下来,让我们实现方法GetListMessages(),具体实现如下:
///
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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