Performance Concepts: Difference between revisions
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==Throughput== | ==Throughput== | ||
Throughput is the rate at which something can be produced, consumed or processed, in a time unit. Throughput is usually relevant in case of [[System_Design#Batch_Processing|batch processing systems]], such as Hadoop, where it describes the number of records that can be processed per second. | Throughput is the rate at which something can be produced, consumed or processed, in a time unit. Throughput is usually relevant in case of [[System_Design#Batch_Processing|batch processing systems]], such as Hadoop, where it describes the number of records that can be processed per second. | ||
=Queueing Theory= | =Queueing Theory= |
Revision as of 18:47, 8 November 2021
Internal
Load
Load Parameters
Performance Metrics
Response Time
The response time is the time between a client sending a request and receiving a response. The response time is relevant for on-line system, such as a web site or a mobile application backend.
Throughput
Throughput is the rate at which something can be produced, consumed or processed, in a time unit. Throughput is usually relevant in case of batch processing systems, such as Hadoop, where it describes the number of records that can be processed per second.
Queueing Theory
https://en.wikipedia.org/wiki/Queueing_theory
- Response Time in Queueing Theory.
- Service Time in Queueing Theory.
Response time and service time diverge as saturation becomes worse.
Organizatorium
- Don't censor bad data, don't throw away data selectively.
- Never average percentiles.
- Coordinated omission. Coordinate omission usually makes something that you think is a response time metric only represent a service time component.
- Response Time in Queueing Theory.
- Service Time in Queueing Theory.
- xth percentile (quantiles) - the value of the performance parameter at which x% of the request are better; https://www.vividcortex.com/blog/why-percentiles-dont-work-the-way-you-think