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Self-adaptive Executors for Big Data Processing

dataset
posted on 06.09.2019, 00:00 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

Format

media types: application/zip, text/csv, text/plain

Licence

Exports

Delft University of Technology

Licence

Exports