Domino 8.5.3 64位中HTTPJVMMaxHeapSize的最佳设置 [英] Best setting for HTTPJVMMaxHeapSize in Domino 8.5.3 64 Bit

问题描述

我正在尝试找到有关Domino 8.5.3 FP4(对于Windows的64位)中JVM堆大小的最佳设置的最佳答案.

I am trying to find a definitive answer as to what the best setting is for the JVM Heap Size in Domino 8.5.3 FP4 - 64 Bit for Windows.

我知道默认情况下它设置为1024M.一些网站建议将其设置为1G/1024M-但这是默认设置，因此效果会很好吗?

I know that by default it's set to 1024M. Some web sites have suggested that it's recommended to be 1G / 1024M - but that's the default setting so it that as good as it gets?

其他站点表示可用RAM的25％.

Other sites have said 25% of available RAM.

我的Domino服务器有12GB可用内存.当前它的HTTPJVMMaxHeapSize = 1024M，任务管理器告诉我正在使用大约7GB的RAM，而nhttp.exe正在使用大约1.1GB的内存.如果可能，我想将此堆增加到2GB或3GB-这样做有什么问题吗?

My Domino server has 12GB RAM available. It's currently got HTTPJVMMaxHeapSize = 1024M and Task Manager tells me that around 7GB of RAM is in use and nhttp.exe is using around 1.1GB. I want to increase this Heap to 2GB or 3GB if possible - will there be any issues doing to?

我正在运行Windows Server 2008 R2标准版.

I'm running Windows Server 2008 R2 Standard Edition.

推荐答案

从XPages角度讲:

Speaking from an XPages perspective:

也就是说，了解在处理给定的工作集(即服务器内的XPages应用程序)时，应用程序代码，服务器运行时和硬件配置文件在做什么.就生命周期执行和内存使用而言，应用程序是否以非最佳方式编码?应用程序是否利用内存或磁盘持久性来进行组件树序列化?服务器是否分配了足够的JVM内存?硬件是否提供了足够的CPU和内存?

That is, understand what the application code, server runtime, and hardware profile is doing when processing a given working set (ie: the XPages application(s) within the server). Is the application coded in a non-optimal manner in terms of lifecycle execution and memory usage? Is the application making use of memory or disk persistence for component tree serialization? Is the server assigned an adequate amount of JVM memory? Is the hardware providing enough CPU and memory?

要完全回答#1中的某些问题，必须使用XPages Toolbox和Eclipse Memory Analyzer之类的工具来进行详细的性能和可伸缩性分析.此外，使用Rational Performance Tester(或某些其他性能测试工具)测试工作集，以模拟测试环境中的实际并发工作负载.这样，您就可以建立一个测试环境，在其中可以使用自动化使(n)个并发用户访问您的应用程序，并收集所有有关健康状况的宝贵数据.

To fully answer some of the questions in #1, detailed performance and scalability profiling must be carried out using tools like the XPages Toolbox and Eclipse Memory Analyzer. Furthermore, test the working set using Rational Performance Tester (or some other performance testing tool) to mimic real life concurrent workloads in a test environment. This allows you to set up a test environment where you can hit your application with (n) number of concurrent users using automation and collect that all invaluable data on health etc.

请记住您的工作集可以是一个或多个应用程序.每个都做不同的事情，并且有不同的负载要求.要具体说明手头的任务-您要针对所有应用程序更一般地调整系统(以平均规模进行调整)还是要针对特定​​应用程序针对服务器进行完全优化(以目标规模进行调整)?

Remember your working set can be one or more applications. Each doing something different, and having different load requirements. Be specific about the task at hand - do you want to tune the system more generally for all applications (for an average scale) or do you want the server to be fully optimized for a specific application (for a targeted scale)?

在适用的情况下进入XSP/Java/ServerSide JavaScript代码并进行更改-使用您对XPages Request Processing Lifecycle的了解，并在高端负载情况下寻找那些饥饿的JVM内存使用者.始终支持磁盘持久性(磁盘存储比RAM便宜！)，并相应地编写自定义Java对象和托管Bean，以应对序列化和还原.在这种情况下，要在功能和速度之间进行权衡，在这种情况下，高可伸缩性最终会消耗CPU ...具有目标功能/动作等的更智能的UX.

Get in and make changes to the XSP / Java / ServerSide JavaScript code where applicable - use your knowledge of the XPages Request Processing Lifecycle and also look out for those hungry JVM memory consumers under high end load scenarios. Always favor disk persistence (disk storage is cheaper than RAM!) and code your custom Java objects and Managed Beans accordingly to cope with serialization and restoration. And make the trade-offs between function and speed in these scenario's where high scalability ends up burning CPU... a smarter UX with targetted functions / actions etc.

根据工作集的需求准备增加内核，时钟速度，RAM和磁盘存储-概要分析，监视和优化工作集的循环方法将为硬件的适用性提供越来越多的机会随着这个过程的发展.

Be prepared to increase cores, clock speeds, RAM, disk storage based on the needs of the working set - a cyclic approach to profiling, monitoring, and optimizing the working set will shed more and more light on the suitability of the hardware as this process evolves.

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