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Self-adaptive Executors for Big Data Processing

dataset
posted on 06.09.2019 by S. (Sobhan) Omranian Khorasani
This dataset contains the measurements obtained with Apache Spark using different strategies for adapting the number of executor threads to reduce I/O contention. The two main strategies explored are a static solution (number of executor threads for I/O intensive tasks pre-determined) and a dynamic solution that employs an active control loop to measure epoll_wait time.

History

Contributors

Epema, D.H.J. (Dick) [orcid:0000-0002-1015-0075]; Rellermeyer, J.S. (Jan) [orcid:0000-0003-3791-7114]; TU Delft, Faculty of Electrical Engineering, Mathematics and Computer Science, Department of Software Technology

Publisher

4TU.Centre for Research Data

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