Object cache to defend against replay attacks.
使高速缓存抵御重播攻击(replay attacks)。
Second, in Figure 2 there are no existing object cache instances.
第二，图2 中不存在现有的对象缓存实例。
Next, navigate to the Object Cache Instances, as shown in Figure 1.
下一步，导航到对象缓存实例，如图1所示。
Define an Object Cache instance with the parameters shown in Figure 9.
定义一个Object Cache实例，并使用如图9所示的参数。
The Memcache daemon, called memcached, is a high-performance distributed object cache.
名为memcached的Memcache守护程序是一种高性能的分布式对象缓存。
After selecting Object cache instances, you are presented with a screen similar to Figure 2.
选择对象缓存实例以后，您将看到与图2所示类似的屏幕。
One of the biggest misconceptions is that the object cache invalidates the need for an output cache.
其中最大的误解是，缓存的对象无效，需要有一个输出的高速缓存。
You will need to define a new Object Cache instance as shown in Figure 2 to execute the example code.
您将需要定义一个新的Object Cache实例，如图2所示，以执行示例代码。
Consider using an object cache like WebSphere eXtreme Scale rather than using the session for caching.
考虑使用WebSphereeXtremeScale之类的对象缓存，而不是使用会话进行缓存。
The proxy caching capability is built on the object cache infrastructure of WebSphere Application Server V6.
该代理缓存功能是建立在WebSphereApplicationServerV6对象缓存基础设施之上的。
A portlet that receives a portlet request can use the object cache to store data required to render the response.
接收Portlet请求的Portlet可使用对象缓存存储呈现相应响应所需的数据。
When compiling queries, the host server USES a feature called the object cache to accelerate query performance.
在编译查询时，主机服务器将使用称为对象缓存(object cache)的特性加速查询性能。
The fragment cache supports two primary types of cache instances: object cache instances and servlet cache instances.
片段缓存支持两种主要的缓存实例：对象缓存实例和Servlet缓存实例。
Only if the data is not available in the object cache, a backend system might be called to deliver the requested data.
仅当数据在对象缓存中不可用时，才会调用后端系统交付请求的数据。
Each instance of the DistributedMap interface has its own properties that you can set using Object cache instance Settings.
Distributed Map接口的每一个实例都具有其自己的属性，可以使用对象缓存实例设置设置这些属性。
So object cache must solve problems in system scalability, data integrity, data consistency and data fault tolerance etc.
对象缓存需要解决诸如系统的可伸缩性，数据完整性，数据一致性以及数据的容错性。
In general, and especially for Fabric clustering, it is important to create the object cache instances at the widest scope possible.
一般来讲，尤其是对于Fabric集群，在尽可能最广的范围内创建对象缓存实例是非常重要的。
While sessions might be convenient, the APIs are not purposed as a cache and do not meet many of the needs you could encounter with an object cache.
虽然会话可能比较方便，但其API并未针对作为缓存使用而设计，不能满足很多可通过对象缓存加以满足的需求。
This is one of the first major pitfalls of transaction processing: ORM-based frameworks require a transaction in order to trigger the synchronization between the object cache and the database.
这是事务处理的主要陷阱之一：基于 ORM 的框架需要一个事务来触发对象缓存与数据库之间的同步。
When you retrieve the object from another mechanism, you should set that object to the cache so that the next retrieval can get it directly from the cache.
根据另一种机制检索该对象时，应该将该对象设置为缓存，以便下一次检索可以直接从该缓存获取这个对象。
As mentioned earlier, each object can also cache the JNDI references it USES in instance variables, so that each object only has to access a reference one time.
正如前文所述，每个对象也可以缓存它在实例变量中使用的JNDI引用，所以每个对象在某一时刻只能访问一个资源。
Recall that the constructor takes the cache object as an optional argument.
回想一下，构造函数以可选参数的方式接受缓存对象。
The code example shows how the application looks up a cache instance through its JNDI name, puts an object into a cache instance, and then retrieves it later.
下面的代码示例显示了应用程序如何通过其JNDI名称查找缓存实例，将对象放入缓存实例中，并稍后对其进行检索。
It guarantees everyone's cache sees the same version of each object, except when a near cache is used.
它保证每个缓存中只存在每个对象的同一版本，除非使用了一个近缓存。
This program demonstrates a basic memory leaking operation involving an unbounded growth in a cache object.
此程序演示的基本内存泄漏操作涉及缓存对象中的无限增长。
They are traditionally lightweight and used for executing tasks such as cache cleanup and object cleanup.
这些线程通常都是轻量级的，用于执行缓存清理和对象清理之类的事务。
Only the code creating the cache object needs to know about the new kind of cache.
只有创建缓存对象的代码需要了解新的缓存类型。
While you implemented the generic cache object in a flow scenario, you can use it elsewhere.
虽然您是在流方案中实现这个通用的高速缓存对象，但是您也可以在其他场合使用它。
As a result, allocating an object on the heap will likely entail more cache misses than allocating that object on the stack.
所以，在堆上分配对象，比起在堆栈上分配对象，会带来更多缓存遗漏。
As a result, allocating an object on the heap will likely entail more cache misses than allocating that object on the stack.
所以，在堆上分配对象，比起在堆栈上分配对象，会带来更多缓存遗漏。
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