DIAMetrics
| Autor: | Hiro Naito, Anja Gruenheid, Kruthi Nagaraj, Stratis D. Viglas, Jeffrey F. Naughton, Shaleen Deep |
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| Rok vydání: | 2020 |
| Předmět: |
General Computer Science
Data anonymization Computer science business.industry General Engineering 02 engineering and technology Benchmarking Modular design Automatic summarization Identification (information) Software deployment 020204 information systems 0202 electrical engineering electronic engineering information engineering Benchmark (computing) 020201 artificial intelligence & image processing Use case Software engineering business Software Information Systems |
| Zdroj: | Proceedings of the VLDB Endowment. 13:3285-3298 |
| ISSN: | 2150-8097 |
| DOI: | 10.14778/3415478.3415551 |
| Popis: | This paper introduces DIAMetrics: a novel framework for end-to-end benchmarking and performance monitoring of query engines. DIAMetrics consists of a number of components supporting tasks such as automated workload summarization, data anonymization, benchmark execution, monitoring, regression identification, and alerting. The architecture of DIAMetrics is highly modular and supports multiple systems by abstracting their implementation details and relying on common canonical formats and pluggable software drivers. The end result is a powerful unified framework that is capable of supporting every aspect of benchmarking production systems and workloads. DIAMetrics has been developed in Google and is being used to benchmark a number of internal query engines. In this paper, we give an overview of DIAMetrics and discuss its design and implementation. Furthermore, we provide details about its deployment and example use cases. Given the variety of supported systems and use cases within Google, we argue that its core concepts can be used more widely to enable comparative end-to-end benchmarking in other industrial environments. |
| Databáze: | OpenAIRE |
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