如何显示虚拟内存统计数据？
要想显示自引导以来的虚拟内存统计数据汇总，输入。
To display a summary of the virtual memory statistics since boot, type.
要想显示所有工作负载分区可用的所有虚拟内存统计数据，输入。
To display all of the virtual memory statistics available for all of the workload partitions, type.
没有设置最短的时间间隔，而是通过可用内存统计信息的变化得出。
The period of time for the shortest intervals is not set but is derived by the variance of the free memory statistics.
通过在粗略/概要性的可用内存统计信息中查找下降趋势来分析周期。
Periods are analyzed by looking for downward trends in the approximated/summarized free memory statistics.
svmon的另一个有用特性是，可以显示给定进程的内存统计信息。
Another useful feature of svmon is that you can display memory statistics for a given process.
通过使用分析可用内存统计信息变化的算法，我们可粗略计算垃圾收集周期之后的可用内存。
We approximate the free memory after a garbage collection cycle by using algorithms that analyze the variance of free memory statistics.
然而，可用内存统计可能是不可靠的，因为操作系统使用了很多动态缓冲区和缓存。
However, the free memory statistic is likely to be unreliable since the OS USES a lot of dynamic buffers and caches.
链接包括：跟踪内存分配、启用内存诊断、获取内存快照、查看内存统计信息和对象转储。
Links include: tracking memory allocations, enabling memory diagnostics, taking memory snapshots, viewing memory statistics, and object dumps.
详细的垃圾收集在垃圾收集周期之后直接提供了可用内存统计信息，而 PMI数据不能提供。
Verbose GC gives free memory statistics directly after a GC cycle, PMI data does not.
所有unix系统都提供了ps和vmstat之类的工具，通过它们提供进程和虚拟内存统计信息。
All UNIX systems provide tools such as ps and vmstat to provide process and virtual memory statistics.
它提供了有关JVM的详细信息，包括总的运行时间、线程信息、装载的类、内存统计信息、垃圾收集和操作系统信息。
It provides detailed information about the JVM, including total uptime, threading information, classes loaded, memory statistics, garbage collection, and operating-system information.
这些统计信息涉及诸如即时 (JIT)编译、类加载、内存分配以及最有趣的垃圾收集之类基本的JVM特性。
These statistics dispense data on the basic JVM features, such as Just-In-Time (JIT) compilation, class loading, memory allocation, and most interestingly, garbage collection.
它将计算用户指定的采样时间内的内存、分页和CPU活动的统计平均值。
It calculates statistic averages for memory, paging, and CPU activity on a sampling period of a length specified by the user.
原因在于，内存是“真实的”(或者说非虚拟的)实体，关于内存消耗的统计数据由内核维护，总是最新的。
The reason for this is that memory is a "real" (or let's say non-virtual) entity, the statistics about memory consumed is maintained by the kernel and is always current.
IDLE的调试器支持设置断点、单步执行和观察变量；但是不能获得内存位置和变量的内容，也不能进行执行的计时和其他统计。
IDLE's debugger provides breakpoints, stepping and variable watches; but nothing so fancy as poking at memory locations and variable contents, or performing timings and other analyses.
随着数据库快速不断地增长，通过访问所有数据收集统计信息的能力可能会受到固定的批量窗口、内存和CPU约束的阻碍。
With databases growing at an unrelenting pace, the ability to collect statistics by accessing all of the data may be hampered by fixed batch Windows or memory and CPU constraints.
这些统计信息存储在表示声明的临时表的目录信息的内存结构中。
These statistics are stored in memory structures that represent the catalog information for declared temporary tables.
这个值包含调整内存堆大小花费的时间和收集调优决策所需的统计数据花费的时间。
This value includes the time spent resizing the memory heaps and the time spent collecting statistics to make the tuning decision.
对象从堆中分配；因此，使用的和空闲的堆内存数量是两个非常重要的统计信息。
Objects are allocated from the heap; thus the amount of heap memory both used and free are two very important statistics.
提高分布统计信息的精确度将导致更大的CPU和内存消耗，并占用更多的目录空间。
Increasing the precision of distribution statistics leads to greater CPU and memory consumption, as well as increased catalog space.
指定应用程序域并不能防止管理软件轮询设备级指标，如设备加载、CPU利用、内存指标以及环境统计数据。
Specifying an application domain does not prevent management software from polling device-level metrics such as device load, CPU utilization, memory metrics, and environmental statistics.
日志结尾部分显示统计信息，包括泄漏了多少内存，使用了多少内存，以及总共分配了多少内存。
The section at the end of the log displays statistics, including how much memory was leaked, how much was used, and the total amount allocated.
这显示了有关用于生成建模统计数据的扩展内存大小的具体信息。
This displays details about the size of expanded memory that is used to produce the modeled statistics.
除了CPU统计数据之外，这个工具还可以提供关于内存分配以及LPAR配置和状态变化历史的数据。
Aside from CPU statistics, the tool can also provide data relating to memory allocation and LPAR configuration and state change history.
它将报告关于内核线程、虚拟内存、磁盘、自陷和CPU活动的统计信息。
It reports statistics about kernel threads, virtual memory, disks, traps, and CPU activity.
基准不应该仅仅捕获性能类型的统计数据，还应该记录系统的实际配置(内存大小、CPU数量以及硬盘容量)。
This baseline should not only capture performance-type statistics, but it should also document the actual configuration of your system (amount of memory, CPU, and disk).
统计信息中包括总的内存利用百分比；全部、已使用的和空闲的内存字节数；以及一些不太重要的监控数据，包括请求、XG4和占用内存。
Statistics include a percentage of total memory utilized; bytes of total, used, and free memory; and of lesser interest in typical monitoring, request, XG4, and held memory.
统计信息中包括总的内存利用百分比；全部、已使用的和空闲的内存字节数；以及一些不太重要的监控数据，包括请求、XG4和占用内存。
Statistics include a percentage of total memory utilized; bytes of total, used, and free memory; and of lesser interest in typical monitoring, request, XG4, and held memory.
应用推荐