这就避免了前面提到的内存限制。
WPAR总内存限制资源控制。
聚合超过内存限制时将会写入临时文件。
Temporary files are written when aggregations exceed memory limits.
每个进程的限制本身受到总内存限制的限制。
Per-process limits are themselves limited by the total memory limit.
注意：由于内存限制，这个步骤可能难以在单个系统上执行。
Note: This step may be difficult to carry out on a single system because of memory constraints.
前面命令中指定的内存限制是指系统中可用的“物理”内存。
The memory limits specified in the previous commands refer to the "physical" memory available in the system.
再次，低带宽常会掩盖CPU或内存限制的算法中的速度差异。
Then again, the slowness of bandwidth will very often swamp speed differences in CPU or memory-bound algorithms.
这种水平的内存使用量远低于64位应用服务器的4GB内存限制。
This rate of memory usage is much less than the 4 GB memory limit for a 64-bit application server.
因此，我们将焦点放在影响32位系统的内存限制，并对之进行详细的讨论。
Therefore we will focus on and discuss in detail the memory limitations affecting 32-bit systems.
将行写入临时文件的速率。聚合超过内存限制时将会写入临时文件。
Rate of writing rows to a temporary file. Temporary files are written when aggregations exceed memory limits.
总内存限制资源控制是一个新的资源控制特性，允许以绝对值的形式设置总内存限制。
The total memory limit resource control is a new resource control that lets you set a total memory limit as an absolute value.
每隔两分钟，缓存实现应将当前内存负载与基于百分比的绝对内存限制进行比较。
The cache implementation should compare the current memory load against the absolute and percentage-based memory limits every two minutes.
问题：数据库共享内存是1.66GB。这个数小于3.35 GB的数据库共享内存限制。
Problem: the database Shared memory is 1.66gb; it is less then the 3.35gb database Shared memory limit.
注意：在32位Solaris中，我们通常将DB 2数据库共享内存限制在大约3.5GB。
Note: On 32-bit Solaris, we normally limit the DB2 database Shared memory to around 3.5gb.
这低于1.75GB的共享内存限制，并且每个数据库共享内存段可以安全地连续映射到一个象限。
This is well under the 1.75gb Shared memory limit, and each database Shared memory segment can safely map contiguously to a quadrant.
该团队还监视系统资源以确保没有系统瓶颈，例如磁盘限制或内存限制以及CPU使用量逼近100%。
The team also monitored system resources to ensure that there were no system bottlenecks, such as disk or memory constraints, and that the CPU was driven to 100%.
内存限制——64位所提供的额外内存可以支持更好的缓冲策略，使得应用程序可以避免开销很高的查询，等等。
Memory constrained -- The extra memory provided by 64-bit supports a better caching strategy, enabling the application to avoid expensive queries, and so on.
可以使用清单1中的命令行选项控制缓存的最大大小，但是请注意，这个最大大小可能受到操作系统共享内存限制的约束
You can control the maximum size of the cache by using the command line option in Listing 1, but note that this maximum size may be constrained by operating system restrictions on shared memory
基准测试机器运行32位版本的Informix并拥有2GB的内存限制(64位版本的Informix没有此限制)。
The benchmark machine was running a 32-bit version of Informix and was limited to 2 GB of memory (the 64-bit version of Informix does not have this limit).
通过使用这种新的资源控制特性，WPAR的总内存限制可以设置为1MB到8,796,093,022,207 MB(大约8388608TB或8192PB (Petabyte)或8EB (Exabyte))之间的任何值。
With this new resource control the total memory limit of a WPAR can be set to any value between 1 MB and 8,796,093,022,207 MB (about 8388608 TB or 8192 PB (Petabyte) or 8 EB (Exabyte)).
一个无限序列可以拥有任意多个元素，只会受到平台内存大小的限制。
An unbounded sequence can hold any number of elements, constrained only by the limits of your platform memory.
数据库共享内存的限制大约是 3.5GB。
该应用程序的服务器容量要求在内存和CPU限制到达处定义。
The server capacity requirements of this application are defined by where memory and CPU limits are reached.
限制本机内存使用。
请确保jvm堆大小设置与同一台服务器上的任何其他应用程序不超出机器的物理内存的限制。
Make sure that the JVM heap size Settings are within the physical memory limits of the machine, along with any other applications on the same server.
我将首先解释一下操作系统和底层硬件给本机内存带来的限制。
I'll start by explaining the limitations on native memory imposed by the OS and the underlying hardware.
限制：在此配置中，对于数据库共享内存的限制是2gb或8个段。
Limit: In this configuration, the limit for database Shared memory is 2gb, or 8 segments.
将导致更小的JVM大小的物理内存的限制常常使您看到在负载下更高的收集率。
Physical memory restrictions leading to smaller JVM sizes typically see higher rates of collection under load.
这么做可以限制内存中 “脏”页面的数量，从而进一步减少I/O开销和磁盘碎片。
The reason for this is to limit the amount of dirty pages in memory, which further reduces I/O overhead and disk fragmentation.
这么做可以限制内存中 “脏”页面的数量，从而进一步减少I/O开销和磁盘碎片。
The reason for this is to limit the amount of dirty pages in memory, which further reduces I/O overhead and disk fragmentation.
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