MapReduce is a parallel processing framework for large scale data. In the reduce phase, MapReduce employs the hash scheme in order to distribute data sharing the same key across cluster nodes. However, this approach is not robust for the skewed data distribution. In this paper, we propose a skew-tolerant key distribution method for MapReduce. The proposed method assigns keys to cluster nodes balancing their workloads. We implemented our proposed method on Hadoop. Through experiments, we evaluate the performance of the proposed method in comparison with the conventional method.
- Key distribution
- Load balance
ASJC Scopus subject areas
- Hardware and Architecture
- Computer Vision and Pattern Recognition
- Electrical and Electronic Engineering
- Artificial Intelligence