Automatic Tuning of Data-Intensive Analytical Workloads

Name: Automatic Tuning of Data-Intensive Analytical Workloads
Brand: LAP Lambert Academic Publishing
SKU: 9783330001404
Price: 306.55 RON
Availability: InStock

Autor: Herodotos Herodotou

Limbă:

Legare: Carte broșată

Editura: LAP Lambert Academic Publishing

Disponibilitate: În depozitul extern

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Modern industrial, government, and academic organizations are collecting massive amounts of data at...

Informații despre carte

Autor

Herodotos Herodotou

Limbă

engleză

Legare

Carte - Carte broșată

Publicat

2016

Pagini

328

EAN

9783330001404

Enbook ID

15575721

Editura

LAP Lambert Academic Publishing

Greutate

506

Dimensiuni

150 x 220 x 20

Descriere completă

Modern industrial, government, and academic organizations are collecting massive amounts of data at an unprecedented scale and pace. The ability to perform timely and cost-effective analytical processing of such large datasets in order to extract deep insights is now a key ingredient for success. Existing database systems are adapting to the new status quo while large-scale dataflow systems like MapReduce are becoming popular for executing analytical workloads on Big Data. In order to ensure good and robust performance automatically on such systems, a novel dynamic optimization approach has been developed that works across different tuning scenarios and systems. The solution is based on (i) collecting monitoring information in order to learn the run-time behavior of workloads, (ii) deploying appropriate models to predict the impact of hypothetical tuning choices on workload behavior, and (iii) using efficient search strategies to find tuning choices that give good workload performance. The dynamic nature enables this solution to overcome the new challenges posed by Big Data, and also makes it applicable to both MapReduce and Database systems.

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Automatic Tuning of Data-Intensive Analytical Workloads

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