数据处理基准
我们使用 ORM 与 Microsoft SQL Server 数据库和 Oracle 数据库交互,我们进行大量记录处理和更新。我正在研究如何对我的数据处理能力进行基准测试。应该是时间与处理的数据?
目标:
- 处理所需的时间 无效记录变为有效记录 记录。(我猜是跟踪/计时器记录 在代码中。)
- 处理消耗的内存量 最大记录集(我该怎么做?)
欢迎任何建议或指南。
We are using a ORM to interact with Microsoft SQL Server database and Oracle database, we do a lot of record processing and updations. I am looking into how I should benchmark my data processing capabilities.Should it be time versus data processed ?
GOALS:
- Amount of time it takes to process
invalid records to valid
records.(trace/timer logging I guess
in code.) - Amount of memory consumed to process
a max record set (How can I do this?)
Any suggestions or guidelines welcome.
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基准的设计取决于您关心的问题。一般来说,您首先需要非常清楚自己想要衡量的内容,然后再努力制定基准。想必您对系统一开始的行为方式以及您关注的瓶颈在哪里有所了解。如果您没有,请从分析开始,而不是基准测试。
接下来,您需要根据您担心的特定瓶颈进行设计。建立基准并测量所关注的特定场景的吞吐量。
我之前已经建立过基准。通常遵循以下原则(有些原则并不严格正确,但无论如何它们都是有用的):
如果您遵循这些,您将获得至少提供有用的东西的基准。
The design of a benchmark depends on what your concern is. In general, you want to be very clear about what you are trying to measure first and then work towards benchmarks after that. Presumably you have some idea of how your system behaves at the start and where your bottlenecks of concern are. If you don't have that, start by profiling, not benchmarking.
Next you want to design based on what you are worried about regarding specific bottlenecks. Build your benchmark and measure the throughput of the specific scenarios of concern.
I have built benchmarks before. Usually following these principles (some are not strictly correct but they are useful anyway):
If you follow these you will get a benchmark that at least delivers something useful.