Query throughput scaled with concurrent users.
查询吞吐量随并发用户数量伸缩。
How many concurrent users can access your software system?
您的软件系统可供多少用户同时访问？
The average request response time for 200 concurrent users is 1,381 ms.
对于200个并发用户的平均请求响应时间是1,381ms。
The average request response time for 200 concurrent users is 1,321 ms.
个并发用户的平均响应时间是1,321ms。
Tests were conducted with 25, 50, 75, 100, 125, and 150 concurrent users.
测试分别采用25、50、75、100、125和150个并发用户。
When calculating system load, only Concurrent users need to be considered.
在计算系统负载时，只有Concurrent用户需要被考虑。
For example, to emulate 5 concurrent users, 5 Thread Groups were specified.
例如，模拟5个并发用户，需要指定5个Thread Group。
One hundred concurrent users are used at each of the stages shown in Table 4.
在每个阶段使用100个并发用户，见表4。
This parameter should be set to 50 if you are expecting 1000 concurrent users.
如果期望1000个并发用户，将该参数设置为50。
The classic discussion application database scaled up to 200 concurrent users.
这个经典的讨论应用程序数据库可扩展至 200个并发用户。
The maximum thread pool limit is your theoretical maximum number of concurrent users.
最大的线程池限制是并发用户的最大理论数量。
Number of concurrent users accessing WHO classifications within your organization.
你的组织中同时进入世卫组织分类的用户数量。
The 4 GB Web servers, 4xcpu, with consistent response time for 100 + concurrent users.
GBWeb服务器，4xcpu，为超过100个并发用户提供了稳定的响应时间。
An infrastructure that can scale to support the anticipated number of concurrent users.
可以评价的基础以支持并发用户的预期数量。
A good starting value for Maximum connections for a load of 100-500 concurrent users is 30.
对于负载量为100- 500个并发用户来说，比较适宜的Maximumconnections初始值为30。
Club 2000 is for those customers who are seeing at least 2000 concurrent users with Domino R5.
Club 2000是为在Dominor5中包含超过2000个并发用户的客户准备的。
Mixed transaction throughput also scaled with concurrent users and flattened at about 2000 TPS.
混合事务吞吐量也随并发用户数量伸缩，直到大约2000 tps。
The initial published performance data shows a configuration that supports 200 concurrent users.
最初发布的性能数据显示一个支持200位并发用户的配置。
This component was repeated as required in a test plan to emulate a specific number of concurrent users.
该组件按照测试计划的要求进行重复，以模拟一个特定数目的并发用户。
Each interval shows the average of the one-hour steady state of each incremental set of concurrent users.
每个区间显示的是增加一组并发用户后一小时内状态稳定后的平均水平。
The number of concurrent users the system can support, showing how response times vary as users are added.
系统能够支持的并发的用户数，显示了当用户数增加时应答次数是怎样变化的。
Given maximum transaction throughput, determine how many concurrent users can be served by the system.
已知最大事务吞吐量，确定系统可以为多少当前用户提供服务。
The best performance with a mixed workload was also achieved with 150 concurrent users, as shown in Figure 4.
混合工作负载最好的性能也出现在有150个并发用户时，见图4。
It's efficient and proven to scale to millions of concurrent users on a single service (such as Google's GTalk).
它很高效，并且被证明可以在一个单独的服务上扩展到数百万的并发用户(比如Google的GTalk)。
Supporting the same number of Concurrent users in these types of application will require larger system capacity.
在这些类型的应用程序中支持相同数量的Concurrent用户将需要更大的系统容量。
The nature of the performance impact of concurrent users proved to be quite different from that of large databases.
测试证明，并发用户对性能的影响在本质上与大型数据库对性能的影响存在很大的差异。
Another key aspect was the potential to ramp up the scalability as the number of concurrent users started to increase.
另一个关键因素是，随着并发用户数量的增加，可能需要很高的可伸缩性。
These test runs show the effect of scaling the number of concurrent users and the number of resources in the repository.
这些测试运行显示了评价储存库中并发用户的数量与资源数量的效果。
The number of concurrent users (with its impact on the number of DB2 agents) determines how much more memory is required.
并发用户的数目(它影响DB 2代理程序的数量)决定需要多少内存。
Assuming a large number of concurrent users (for example, 2000), a good starting value for the maximum thread count is 100.
假定有大量并发用户(例如，2000个)，比较适宜的Maximumthread coun t初始值为100。
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