Processing large messages tends to be more complex.
较大的消息的处理常常更为复杂。
Use a dedicated server for processing large messages.
使用专用服务器处理大消息。
Network bandwidth can be a limiting factor when processing large messages.
处理大消息时，网络带宽可能是一个限制因素。
There are two properties that need to be considered when processing large messages.
处理大消息时需要考虑两个属性。
You Can adjust the Disk Space preference to prevent the downloading of large messages.
还可以调整“磁盘空间”首选项，以防止下载大型消息。
If you're signing large messages, much more time is spent on the canonicalization and digesting steps.
如果对大消息签名，更多的时间花在规范化和消化步骤上。
This section provides a number of design patterns to improve performance for processing of large messages.
本节提供几个设计模式，以提高大消息处理性能。
Typically, large messages are composed of multiple smaller messages, which have to be processed individually.
较大的消息常常由必须被分别处理的多个较小的消息组成。
This section provides information on the main considerations and affecting factors when processing large messages.
本节提供关于处理大型对象时的主要注意事项和影响因素的信息。
Processing a number of large messages, especially when running with concurrent threads, can lead to JVM Heap exhaustion.
处理一些大消息，特别是使用并发线程运行时，可能会导致JVMheap耗尽。
Could the processing of the large messages cause resource constraints and hinder other process Server solution processing?
大容量消息的处理会导致资源限制并阻碍其他ProcessServer解决方案的处理吗？
If multiple large messages are being processed by a service at the same time, then available space within the JVM Heap can quickly disappear.
如果一个服务同时处理多个大消息，那么J VMHeap中的可用空间可能会迅速耗尽。
In general, we do not recommend passing large messages through Process Server and WebSphere ESB, especially if they are not doing anything useful.
一般而言，我们不推荐通过ProcessServer和WebSphereESB传递大容量消息，特别是在它们没有多少用处时。
For example, POP3's single mailbox model can lead to thousands of large messages in a single location, making access and control of the mailbox a tedious affair.
例如，POP3的单一邮箱模型会导致数千条大型消息都处于一个位置，从而使得对邮箱的访问和控制成了件麻烦事。
Throttling incoming client requests with large messages to arrive sequentially into WebSphere ESB can be achieved by a front end server such as a DataPower appliance for instance.
限制包含大消息的入站客户机请求、使其顺序进入WebSphereESB可以通过DataPower设备这样的前端服务器实现。
Moreover, these large messages often contain very large embedded binary information encoded using base-64 encoding as part of the main body of the XML message. This typically happens when a.
而且，这些大消息往往包含了非常大的、作为XML消息主体的、采用base- 64编码的二进制编码信息。
The messages contain a large number of abbreviations that are essential to understanding its contents.
包含着数量巨大缩写的信息是理解它的内容的关键所在。
Typical cause for these symptoms are very large - sometimes 50 MB or more - messages.
导致这些症状的典型原因是非常大的（有时会达到50MB或者更大）消息。
When working on large projects, a rebuild generates dozens of messages.
当处理大项目时，重新构建会生成众多消息。
Membership lists can also form the basis of a telephone tree, a system for getting messages out to large Numbers of people.
成员名单也可以组成一个电话树状图的基础，一个可以发出给外面更多人们信息的系统。
Decomposition of an input message is a technique that aims to decompose a large message into multiple smaller messages for individual submission.
输入消息分解技术旨在将一条大消息分解为多条小消息，以便逐个提交。
If allowed, the queue manager segments a message into a number of smaller messages when it is too large to be sent.
如果允许，队列管理器会将由于太长而难以发送的消息分成大量更小的消息。
A user population that sends large mail messages or messages with large attachments is more costly to support than the same population sending smaller messages.
发送大邮件消息的用户或具有大附件的消息的用户所需的支持邮件的开销要比发送较小消息的相同用户所需的开销大。
It's not uncommon for an ESB to handle millions of messages each day in a large organization.
在大型组织中，ESB每天处理数百万条消息的情况并不少见。
Tuning for consistently large or consistently small messages is not difficult, but tuning for extreme variability is.
为始终如一地大或始终如一地小的消息进行优化并不困难，但是为极端的变异性而进行优化则非常困难。
When you're signing a large number of small messages with asymmetric encryption, most of your processing time is spent on the signature step.
当使用非对称加密对很多消息签名时，大多数处理时间花在签名上。
Transformation Extender can also support advanced transformation requirements, such as efficient processing of large data records or messages, and advanced data validation without complex coding.
Transformation Extender还支持高级的转换需求，例如大型数据记录或消息的高效处理，以及无需复杂编码的高级数据验证。
This approach offers good performance for message exchanges - nearly as good as WS-SecureConversation - when the messages are relatively large.
当消息相对较大时，这个方法在实现消息交换时有很好的性能—几乎与WS -SecureConversation一样好。
If there are multiple clients (large number) connecting to the gateway, the number of messages sent per second through to WebSphere MQ decreases.
如果有多个客户端(数量很大)连接到网关，那么每秒发送到WebSphereMQ的消息数量将会减少。
It is worth noting that code_recognizer.py sends its (large) test result file to STDOUT, but puts some friendly messages on STDERR.
值得注意的是，code_recognizer . py将它的(大的)测试结果文件发送到STDOUT，而将一些友好的消息放在STDERR里。
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