TY - GEN
T1 - IDP
T2 - International Computer Symposium, ICS 2014
AU - Lee, Chia Wei
AU - Huang, Horng Chyau
AU - Hsieh, Sun Yuan
PY - 2015/1/1
Y1 - 2015/1/1
N2 - In this paper, we propose a data placement strategy to deal with the imbalanced workload problem on DataNodes. Basing on computing capability of each node in a heterogeneous Hadoop cluster, the proposed strategy can balance the data that was stored in the DataNode such that the cost of data transfer time can be tremendously reduced. As a result, the Hadoop overall performance can be greatly improved. Experimental results demonstrate that the proposed data placement strategy can highly decrease the execution time and thus improves Hadoop performance in a heterogeneous cluster.
AB - In this paper, we propose a data placement strategy to deal with the imbalanced workload problem on DataNodes. Basing on computing capability of each node in a heterogeneous Hadoop cluster, the proposed strategy can balance the data that was stored in the DataNode such that the cost of data transfer time can be tremendously reduced. As a result, the Hadoop overall performance can be greatly improved. Experimental results demonstrate that the proposed data placement strategy can highly decrease the execution time and thus improves Hadoop performance in a heterogeneous cluster.
UR - http://www.scopus.com/inward/record.url?scp=84926456290&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84926456290&partnerID=8YFLogxK
U2 - 10.3233/978-1-61499-484-8-49
DO - 10.3233/978-1-61499-484-8-49
M3 - Conference contribution
AN - SCOPUS:84926456290
T3 - Frontiers in Artificial Intelligence and Applications
SP - 49
EP - 58
BT - Intelligent Systems and Applications - Proceedings of the International Computer Symposium, ICS 2014
A2 - Chu, William Cheng-Chung
A2 - Yang, Stephen Jenn-Hwa
A2 - Chao, Han-Chieh
PB - IOS Press
Y2 - 12 December 2014 through 14 December 2014
ER -