Self-adaptive Executors for Big Data Processing

Dataset

Description

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.
Date made available6 Sep 2019
PublisherTU Delft - 4TU Centre for research data
Date of data production2018 - 2019

Cite this

Omranian Khorasani, S. (Creator), Epema, D. (Contributor), Rellermeyer, J. S. (Contributor) (6 Sep 2019). Self-adaptive Executors for Big Data Processing. TU Delft - 4TU Centre for research data. 10.4121/uuid:38529ffe-00d0-42b0-9b3c-29d192262686