大型应用程序的可扩展性
有非常有用的文档解释了 Linkedin、MySpace、Amazon 等服务器架构。
在看到 MySpace 后，我真的很惊讶，因为他们的应用程序使用了 500 多个数据库服务器。
想知道如果数据跨越多个数据库服务器，他们将如何维护 SQL 事务、连接、查找？
There are very useful documents explaining the server architectures like Linkedin, MySpace, Amazon and etc.
After seeing MySpace, I really surprised as they are using 500+ database servers for their application.
Would like to know how will they maintain SQL transactions, joins, look ups if data spans across multiple database servers?
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High Scalability 也在 MySpace 上占有一席之地。 非常值得一读。
我认为关键在于数据库是联合的而不是分布式的。因此，与给定用户相关的所有信息都位于单个物理数据库中。它处理了加入、事务性等方面的大部分问题。
高可扩展性没有提到它，但我认为必须有一些集中数据库充当注册表：用户 #217873828 的数据位于数据库 Profile42 中。参考数据可能有类似的集中化，尽管其中大部分可能位于缓存中而不是从数据库中读取。
High Scalability also has a piece on MySpace. It's well worth a read.
I think the key think is that the databases are federated rather than distributed. So all the information relating to a given user is in a single physical database. That handles most of the issues with joining, transactionality, etc.
High Scalability doesn't mention it, but I presume there must be some centralised database acting as a registry : the data for user #217873828 is in database Profile42. There is probably a similar centralisation for reference data, although most of that is likely to be in cache rather than read from a database.
有一篇关于 eBay 的高可扩展性的精彩文章。他们将其发挥到了极致，应用程序执行所有操作，仅使用数据库进行“哑”存储。该应用程序确实具有连接、引用完整性等功能。考虑到我们大多数人的经验以及数据库在我们的应用程序中扮演的角色，以这种方式思考事情几乎很奇怪。不过显然它是有效的。 :)
http://highscalability.com/ebay-architecture
There's a great article on High Scalability about ebay. They take it to the extreme with the application doing everything and just using the dbs for "dumb" storage. The app does joins, referential integrity, etc. It's almost weird to think of things in that manner given what experience most of us have and what role databases play in our applications. Apparently it's effective, though. :)
http://highscalability.com/ebay-architecture