Before WebSphere eXtreme Scale, logon took 700 ms with two back-end calls.
在WebSphereeXtreme Scale之前，登录需要700ms，两次后端调用。
WebSphere eXtreme scale USES the concept of a partition to scale out a cache.
WebSphereeXtreme Scale使用分区的概念扩展缓存。
WebSphere eXtreme Scale enables much larger cache capacities than in the past.
WebSphereeXtreme Scale能实现比过去更大的缓存容量。
WebSphere extreme Scale provides an extremely powerful coherent distributed cache.
WebSphereeXtreme Scale提供了极其强大的一致性分布式缓存。
WebSphere eXtreme Scale brings data closer to applications via caching technology.
WebSphereeXtreme Scale通过缓存技术将数据拉近应用程序。
For best performance results it is best not to cache distributed maps in eXtreme Scale.
想要达到最佳性能，最好不要在eXtreme Scale中缓存分布式映射。
WebSphere eXtreme Scale offers a better quality of service for SIP session replication.
WebSphereeXtreme Scale能提供更好的SIP会话复制服务质量。
A key feature of WebSphere eXtreme Scale is that it provides a large, scalable, elastic cache.
WebSphereeXtreme Scale的关键功能是提供大型、可扩展、弹性的缓存。
Other items to consider when using WebSphere eXtreme Scale with a super cluster topology include.
在结合使用WebSphereeXtreme Scale和超级集群拓扑结构时需要考虑的其他事项包括。
With WebSphere eXtreme Scale, logon took 20 ms with profile cache access, which is 35 times faster.
使用WebSphereeXtreme Scale时，带配置文件缓存访问的登录只需要20ms，速度提高了35倍。
The results, as shown in listing 8, show a dramatic speed-up for using WebSphere eXtreme Scale Cache.
结果如清单8 所示，显示了使用WebSphereeXtreme ScaleCache 后的显著加速。
Consider using an object cache like WebSphere eXtreme Scale rather than using the session for caching.
考虑使用WebSphereeXtreme Scale之类的对象缓存，而不是使用会话进行缓存。
WebSphere eXtreme Scale can be deployed in either 32 bit (the more popular environment) or 64 bit JVMs.
WebSphereeXtreme Scale可以被部署到32位(更普遍的环境)或64位JVM中。
WebSphere eXtreme Scale enables applications to scale to support large volumes of users and transactions.
WebSphereeXtreme Scale 实现这些应用程序的扩展性，以支持大量用户和事务。
Figure 2 shows the conceptual difference between the dynacache-based and eXtreme Scale-based caching topology.
图2显示了基于dynacache和基于eXtreme Scale缓存拓扑概念上的差异。
WebSphere eXtreme Scale uses loaders to read data from and write data to the database from the in-memory cache.
WebSphereeXtreme Scale使用了加载器读取内存中缓存的数据，以及将数据写入到数据库中。
As a rule, WebSphere eXtreme Scale users are expected to use less memory per JVM than with a conventional cache.
一般来说，与传统缓存相比，WebSphereeXtreme Scale用户预期对每个JVM使用更少的内存。
We will discuss how eXtreme Scale can potentially reduce the impact of a full or partial site restart for end users.
我们将讨论eXtreme Scale如何减少重启全部或部分网站对终端用户的影响。
Because of its implementation, WebSphere eXtreme Scale never permits different versions of the same data in its cache.
由于其实现，WebSphereeXtreme Scale从不允许在其缓存中有同一数据的不同版本。
Just as in a relational database, WebSphere eXtreme Scale supports the use of indices to improve the speed of queries.
如同在关系数据库中一样，WebSphereeXtreme Scale支持使用索引提高查询速度。
WebSphere eXtreme Scale also provides features to replicate data throughout the environment, further improving resiliency.
WebSphereeXtreme Scale还提供了复制整个环境中的数据的特性，从而进一步提高弹性。
Although WebSphere eXtreme Scale can be deployed in a single JVM, such a deployment would not provide any high availability.
尽管WebSphereeXtreme Scale可以部署到一个单个JVM中，但是这类部署不会提供高可用性。
The eXtreme Scale topology shows less statistical scatter in response times, and overall consistently faster response times.
eXtreme Scale拓扑的响应时间分散性小，总体上比较一致且快速。
They're also influenced by network conditions, WebSphere eXtreme Scale configuration, and the processing speed of your servers.
它们还受网络状况、WebSphereeXtreme Scale配置和服务器处理速度的影响。
This article reviewed the write-behind caching scenario and showed how this feature is implemented with WebSphere eXtreme Scale.
本文重新审视了write - behind缓存技术，并展示了如何在WebSphereeXtreme Scale下实现这一特性。
Improvement in average response time is another notable benefit of employing eXtreme Scale to help with the cold start situation.
提高平均响应时间是采用eXtreme Scale帮助解决冷启动问题的另一个明显的效益。
WebSphere eXtreme Scale has two different APIs for defining the ways in which objects are placed into and fetched from the cache.
WebSphereeXtreme Scale有两个不同的API，用于定义将对象放入缓存和从缓存中获取对象的方式。
If you extend this analogy to WebSphere eXtreme Scale, you can compare a file cabinet to a container server, which runs in a JVM.
如果将这种类比应用到WebSphereeXtreme Scale，您可以将文件柜看做在JVM中运行的容器服务器。
When you define a WebSphere eXtreme Scale cache, you specify the level of replication by specifying the number of replica shards.
定义WebSphereeXtreme Scale缓存时，您通过指定复制碎片（replica shard）缓存指定复制水平。
Replicas can be synchronous or asynchronous; the distinction is important when data is written to a WebSphere eXtreme Scale cache.
复制可以是同步或异步的；将数据写入WebSphereeXtreme Scale缓存时区别很重要。
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