You can also use JSON to cache data that the user inputs.
您还可以使用JSON来缓存用户输入的数据。
AFS can be configured to cache data locally on disk or in memory.
可以将AFS配置为在本地的磁盘或内存中缓存数据。
This article explains how to configure and use JCS to cache data for your Web applications.
本文将说明如何配置和使用JCS来缓存Web应用程序的数据。
Most of the time, you wouldn't want to completely cache data that is being updated constantly.
在大多数情况下，不希望完全缓存那些经常更新的数据。
A test for cache data validity is an additional method you might need when dealing with a caching system.
测试缓存数据的有效性可能是处理缓存系统时需要使用的另一种方法。
You can use the core regions together to gain great flexibility in how and where you store your cache data.
可以结合使用这些核心区域以在如何存储缓存数据、将缓存数据存储在什么地方等方面获得更大的灵活性。
Describes how to import database files into your projects, and when you can cache data for offline use.
描述如何将数据库文件导入到项目中，以及何时可以缓存数据以供脱机时使用。
Coordinating the invalidation of stale cache data as well as the replication of updated across an N-tier cache.
协调陈旧缓存数据的失效，以及在n层缓存中复制更新。
We showed how to use the WebSphere Application Server dynacache infrastructure in order to cache data in portlets.
我们展示了如何使用WebSphereApplicationServerdynacache基础设施在Portlet中缓存数据。
With no caching API available in the JSR 168 portlet API, many portlet developers use the portlet session in order to cache data.
由于JSR 168PortletAPI中没有缓存api，因此许多Portlet开发人员将Portlet会话用于缓存数据。
Need to cache data from a database or other backend data store that needs to be accessed at speeds that would otherwise be unattainable?
需要缓存数据库或其他后端数据存储区中的数据，并需要以其他方式无法达到的速度访问这些数据？
An example when cache data would be appropriate is a customer record, including the address of the customer, stored in a backend system.
缓存数据所适合的示例是客户记录，包括存储在后端系统的客户地址。
However, using the session for storing cache related data has some severe drawbacks. Session and cache data differ in the following ways.
然而，通过会话存储与缓存相关的数据具有某些严重的缺陷。
Now that you know how to cache data using the dynacache infrastructure, let's look at how you can generate the correct cache key in a portlet.
既然您已经了解了如何使用dynacache基础设施缓存数据，现在让我们看一下如何在Portlet中生成正确的缓存键。
One of the options is to use the dynamic cache service, which is built into WebSphere Application Server, to serve dynamic content and cache data.
其中的一个选项是使用动态缓存服务，WebSphereApplicationServer 中内置了该服务，用于提供动态内容和缓存数据。
If you used the mechanism above, the portlet would always return the same content during the cache time, and the content would only be updated whenever the cache data expires.
如果您使用上面的机制，该portlet在缓存时间内将一直返回相同的内容。该内容只有在缓存数据过期的时候才会被更新。
Applications have complete update control over over how data changes are submitted between the in-memory cache data set and the underlying data source through ADO.NET methods.
对于如何通过ADO.NET方法在内存缓存数据集合与基本数据源之间提交数据更改，这些应用程序拥有完全的更新控制权。
For example, instead of using the default in-memory cache engine, you can create custom providers that store cache data in databases, in custom objects, or in the file system.
例如，与其使用预设的记忆体中快取引擎，您可以建立将快取资料储存在资料库、自订物件或档案系统中的自订提供者。
So by now, we have hopefully convinced you that using a real cache API for cache data, instead of the session, is something that gives you real benefits in performance and scalability.
因此，到目前为止，我们希望已说服您将真正的缓存API用于缓存数据，而不是使用会话，它将向您提供性能和可伸缩性方面的真正好处。
In cases where cache data consistency is important, Ehcache can be distributed using the Terracotta Server Array. This gives developers a distributed cache that maintains data coherence.
在缓存数据的一致性是非常重要的场合下，可以通过TerracottaServerArray实现分布式的Ehcache，这样开发者就拥有了能够维护数据一致性的分布式缓存。
Using the CachedRowSet, one can allow clients to cache data locally when a connection is available and then reconnect to synch up changes they may have performed on the data in question.
使用CachedRowSet可以允许客户机在连接可用时将数据缓存在本地，然后重新连接，以同步对数据执行的更改。
How to: Cache Data for Use Offline or on a Server.
如何：缓存数据以便脱机使用或在服务器上使用。
How to: Cache Data in a Password-Protected Document.
如何：在受密码保护的文档中缓存数据。
In a write-behind cache, data reads and updates are all serviced by the cache, but unlike a write-through cache, updates are not immediately propagated to the data store.
在write - behind缓存中，数据的读取和更新通过缓存进行，与write -through缓存不同，更新的数据并不会立即传到数据库。
In a write-behind cache, data reads and updates are all serviced by the cache, but unlike a write-through cache, updates are not immediately propagated to the data store.
在write - behind缓存中，数据的读取和更新通过缓存进行，与write -through缓存不同，更新的数据并不会立即传到数据库。
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