尽管这个问题总是被忽视，但在数据密集型应用程序中，数据流确实会消耗大量带宽。
While often overlooked, data flow consumes a larger share of bandwidth in data-intensive applications.
Moonlight在设计时已经考虑到对于数据和存储密集型Web应用程序的处理。
Moonlight was designed with data and memory intensive web application processes in mind.
比如数据库连接池就是单例设计模式的一个例子：我们一般不想让应用程序具有连接池类的多个资源密集型实例。
An example use case for a singleton would be a database connection pool: you don't want your application to have multiple resource-intensive instances of a connection pool class.
如果对源数据库的访问不可靠，在缓存层争取弹性可能会提高读密集型应用程序的总体稳定性。
If access to the source database is unreliable, striving for resiliency in the cache layer might improve overall stability for read-intensive applications.
就JFS2而言，这种情况不再可能发生，甚至不再需要，因为已经对它进行了优化，以便更加高效地处理元数据密集型的应用程序。
With JFS2, that is no longer possible, or even necessary, because it was tuned in order to handle metadata-intensive types of applications much more efficiently.
数据密集型程序有着广泛的应用，已经成为高性能计算中最重要的应用程序之一。
Recently data intensive applications have been focused as one of the most important applications for high performance computing.
数据密集型程序有着广泛的应用，已经成为高性能计算中最重要的应用程序之一。
Recently data intensive applications have been focused as one of the most important applications for high performance computing.
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