sponsors
usenix conference policies
You are here
PIKACHU: How to Rebalance Load in Optimizing MapReduce On Heterogeneous Clusters
Rohan Gandhi, Di Xie, and Y. Charlie Hu, Purdue University
For power, cost, and pricing reasons, datacenters are evolving towards heterogeneous hardware. However, MapReduce implementations, which power a representative class of datacenter applications, were originally designed for homogeneous clusters and performed poorly on heterogeneous clusters. The natural solution, rebalancing load among the reducers running on heterogeneous nodes has been explored in Tarazu, but shown to be only mildly effective.
In this paper, we revisit the key design challenge in this important optimization for MapReduce on heterogeneous clusters and make three contributions. (1) We show that Tarazu estimates the target load distribution too early into MapReduce job execution, which results in the rebalanced load far from the optimal. (2) We articulate the delicate tradeoff between the estimation accuracy versus wasted work from delayed load adjustment, and propose a load rebalancing scheme that strikes a balance between the tradeoff. (3) We implement our design in the PIKACHU task scheduler, which outperforms Hadoop by up to 42% and Tarazu by up to 23%.
Open Access Media
USENIX is committed to Open Access to the research presented at our events. Papers and proceedings are freely available to everyone once the event begins. Any video, audio, and/or slides that are posted after the event are also free and open to everyone. Support USENIX and our commitment to Open Access.
author = {Rohan Gandhi and Di Xie and Y. Charlie Hu},
title = {{PIKACHU}: How to Rebalance Load in Optimizing {MapReduce} On Heterogeneous Clusters},
booktitle = {2013 USENIX Annual Technical Conference (USENIX ATC 13)},
year = {2013},
isbn = {978-1-931971-01-0},
address = {San Jose, CA},
pages = {61--66},
url = {https://www.usenix.org/conference/atc13/technical-sessions/presentation/gandhi},
publisher = {USENIX Association},
month = jun
}
connect with us