CDNs work by caching data on the 'edge' of geographically dispersed networks.
内容发布网络(CDN)通过在地理分散的网络边缘缓存数据来起作用。
But the second form of caching data offers an object-oriented approach to caching.
但是第二种缓存数据的方法提供了一种面向对象的方法来缓存。
Data caches can be used for caching data with change rates that are below the page request rate.
可以使用数据缓存对那些更改频率低于页面请求频率的数据进行缓存。
Caching data in memory can dramatically increase performance, but remember that the data is then somewhat vulnerable.
在内存中缓存数据能大大提高性能，但是数据会显得有些脆弱。
Caching data in the final native application form (objects) reduces path length, compared with accessing SQL-based data.
与访问基于SQL的数据相比，以最终的本机应用程序形式(对象)缓存数据可减小路径长度。
Some situations also call for caching data in memory to minimize the number of data base calls for data that does not change.
同样一些情况要求在内存中缓存数据，以此来减少并不改变的数据被数据库调用的次数。
The second use case involves caching data which is only relevant for one portlet instance, and the data is specific to a portlet window.
第二个用例涉及到了只与某个Portlet实例有关的缓存数据，并且数据是特定于 Portlet 窗口的。
This version greatly improved the efficiency of the function, by caching data rather than reloading it, but it did so at the expense of maintainability.
这个版本对数据进行缓存而不是重新加载，很大程度上改善了函数的有效性，但这会需要更多的维护费用。
Application access to locally and remotely exported file systems is coordinated to allow caching data for exported file systems accessed by remote clients.
远程客户端协调对本地和远程输出文件系统应用访问来允许高速缓存的输出文件系统数据的访问。
With a distributed OS, the site won't get swamped because the OS has detected the increased demand on resources and started caching data onto other computers.
而用了分布式操作系统，该站点将不会被冲垮，因为该操作系统已探测到对资源需求的增加，并开始在其它的计算机上缓存数据。
Code that makes common use of static fields or other means of caching data is unsafe for scopes because of the assignment rules, which can result in an IllegalAssignmentError.
由于分配规则的限制，通常使用静态字段或其他缓存数据方式的代码会使范围不安全，可能导致IllegalAssignmentError。
Caching the data as a property saves having to parse the file whenever the plug-in is run.
同时将数据缓冲在属性中，这样就避免了每次运行插件时都需要解析文件。
This includes creating relationships with these tables and various forms of optimization such as hints or data caching to name a couple.
这种整合包括创建与这些表的关系以及各种形式的优化，比如通过提示或数据缓存命名一个耦合。
All caching and in-memory data can be redesigned as replicated nodes based storage.
所有缓存和内存数据都可以重新设计为基于存储的复制节点。
Caching works best for read-only data.
缓存非常适合于只读数据。
How you choose to handle caching is often based on the type of data that you are caching and how that data is used.
如何选择处理高速缓存通常是以您正在高速缓存的数据类型，以及那些数据如何使用为基础的。
The purpose of the data caching tier is to provide scalable, fault tolerant, coherent data grids for your application server tier.
数据缓存层的目的是为您的应用程序服务器层提供一个可伸缩、容错和一致的数据网格。
There is no caching involved for either data or metadata.
数据或原数据都不会涉及缓存的问题。
The server resource issue can be addressed by caching prior data and then aggregating the very newest additions.
服务器资源问题可以这样解决：将以前的数据缓存，然后将最新添加的数据集成进来。
Cloud computing is a distributed deployment model, and for that reason, caching and data accessibility are of far greater strategic importance than before.
云计算是个分布式的部署模型，因此缓存和数据访问的战略意义将达到前所未有的高度。
Whereas the cache API is designed to cache data for a long period or until some condition is met, per-request caching simply means caching the data for the duration of the request.
缓存api的设计目的是为了将数据缓存较长的一段时间，或者缓存至满足某些条件时，但每请求缓存则意味着只将数据缓存为该请求的持续时间。
After that, data retrieval, caching and refreshes are handled automatically.
此后，数据获取、缓存和刷新都是自动处理的。
External data caching can be performed on external content or data returned by CONNECT tags.
可以在CONNECT标记返回的外部内容或数据上进行外部数据高速缓存。
For mobile developers, it's even more exciting as it really opens up the local caching of data.
对于移动开发人员来说，则更为振奋人心，因为它真正开启了数据的本地高速缓存。
Enable data caching to reduce the number of accesses in order to handle large volumes of data requests.
支持数据缓存以减少访问数量，从而处理大量的数据请求。
At the data services orchestration tier, caching is supported by a specialized data caching service.
在数据服务编排层，缓存由专门的数据缓存服务提供支持。
Batch processing usually doesn't need data caching, otherwise you may run out of memory and dramatically increase your GC overhead.
批处理通常不需要数据缓存，否则你会将内存耗尽并大量增加GC开销。
This feature is available on a tablespace-by-tablespace basis, effectively allowing some data in DB2 to use file caching and other data to bypass it.
这个特性是以表空间为单位启用或禁用的，从而可以有效地使DB2中的某些数据使用文件缓存，而另一些数据则绕过文件缓存。
The more common non-contextual scenarios also support caching taxonomy data within the UDDI Business Registry to reduce dependence on the provider's external taxonomy service.
更为常见的无上下文方案也支持将分类法数据缓存在UDDI业务注册中心以减少对提供者的外部分类法服务的依赖。
Scalability - Since caching minimizes data retrieval and formatting operations, it reduces the load on server resources thus increasing the scalability of the application.
数据缓存后，减少了从服务器端加载数据。
应用推荐