一般人们会选择纵向扩展(scale up)SQL Server数据库,而非横向扩展(scale out)。纵向扩展很容易:增加硬件、处理能力、内存、磁盘和提高网络速度。其原理就是仍然在一台服务器上运行数据库,但是增加了服务器的处理能力和资源。这种方法很昂贵,但是非常简单
一般人们会选择纵向扩展(scale up)SQL Server数据库,而非横向扩展(scale out)。纵向扩展很容易:增加硬件、处理能力、内存、磁盘和提高网络速度。其原理就是仍然在一台服务器上运行数据库,但是增加了服务器的处理能力和资源。这种方法很昂贵,但是非常简单直接。
采用云技术
有时候,最简单的方法就是将问题交由其他人处理。微软的Windows Azure云服务包含一个基于云的SQL Server版本SQL Azure.这在技术上并非真正意义的横向扩展,因为它是一种无限纵向扩展方法。所以,转移到Azure并不需要对您的应用程序进行大改动。实际上,您只需要将应用程序迁移到SQL Azure,然后支付存储、处理和数据传输费用。这些都是收费服务,但是您不需要再担心扩展问题。
复制
SQL Server原生复制是一种支持横向扩展的解决方案,与数据库的创建和使用方式有关。您只需要在多台服务器上复制多个数据库副本,然后将不同的用户指向各台服务器。这种方法通常最适合支持地理位置分散的用户,如亚洲办公室的用户使用服务器1,而北美办公室的用户则使用服务器2.每一台服务器都拥有完整的数据副本,并且会复制伙伴服务器的所有修改。
这种方法不支持自动负载均衡,并且最适合用在用户固定只使用一部分数据的情况。换而言之,如果亚洲用户只需要编辑与他们办公室相关的数据--例如,主要是亚洲客户的信息,那么复制能够保证其他数据库副本也包含这些记录的副本。如果所有用户都需要编辑完整的数据集,那么复制就变得有一些复杂,因为SQL Server必须在支持用户的同时,编辑位于不同服务器的同一个数据。
SQL Server的合并复制能够处理这种冲突,但是您必须进行一些自定义合并编程,这意味着您的开发人员必须开发一些算法,确定用户并发访问数据时谁获取编辑权限。客户应用程序也需要增加编程;使它们不仅向数据库提交数据修改,,也要循环检查这些修改是否被其他并发用户重写。用户也需要重新培训,因为客户端应用程序可能会提示:"您正在编程的数据已经发生变化。您需要重新检查,确定您的编辑是否仍然有效。"
联合数据库
另一个重要的横向扩展方法是联合。通过这种方法,您可以将数据库划分到多台服务器上。垂直分割将同一个表的不同行保存到不同的服务器上。同时,地理分区是最常用的方法:将所有亚洲数据记录保存在一台服务器上,而所有欧洲数据则保存在另一台服务器上。这种方法不同于整体复制:每一个位置的服务器都不具备完整的数据库,而只拥有该位置的数据。通过实现一种SQL Server分布式分区视图而形成完整的表,用户就可以浏览一个"联合"或组合的数据视图。水平分割则将表的字段保存在不同的服务器上,因此各台服务器一起协作构成组合的表。
这些数据库的创建并不简单,其中涉及一种整体操作。您需要掌握关于数据访问和使用的详细信息,才能够实现正确的部署。此外,您还需要一位SQL Server数据库架构师,他应该全面理解这些技术,分析您的业务情况,并且能够正确地创建这些组件。
在一些情况中,实现这种横向扩展对客户端应用程序的改动很小。对于本身在设计上大量使用视图和存储过程进行数据访问的应用程序,更是如此。因为这些元素只是是在后台抽象,在客户端上不会发生变化。但是,这些应用程序并不常见;通常,实现横向扩展都需要修改客户端程序,使客户端与后台结构分离。
横向扩展并不简单
毫无疑问,实现SQL Server横向扩展非常复杂--这也是Azure等云数据库系统流行的原因之一。此外,有一些第三方供应商能够帮助实现横向扩展技术,而不需要完全依赖SQL Server的原生特性。您需要自己下功夫了解这些方法,理解数据访问和使用方法,这样才能够选择最符合您要求的方法。

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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