The performance evaluation of k-means by two MapReduce frameworks, Hadoop vs. Twister

International Conference on Information Networking

Volumn 2015-January, Issue , 2015, Pages 405-406

  Kang, Yunhee ^a   Park, Young B ^b  

^a Baekseok University   (South Korea)

^b Dankook University   (South Korea)

Author keywords

BLAST; Emulab; MapReduce; mr mpi

Indexed keywords

AGRICULTURAL ROBOTS; BLASTING; CLUSTER ANALYSIS; DATA MINING; ITERATIVE METHODS;

EMULAB; GEO-STATISTICS; HADOOP FRAMEWORKS; MAP-REDUCE; MAPREDUCE FRAMEWORKS; MAPREDUCE MODELS; MARKET SEGMENTATION; MR-MPI;

K-MEANS CLUSTERING;

EID: 84940555732     PISSN: 19767684     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICOIN.2015.7057927     Document Type: Conference Paper

References (7)

1. Paul Zikopoulos, Chris Eaton. " Understanding Big Data: Analytics for Enterprise Class Hadoop and Streaming Data (1st ed.)," in McGraw-Hill Osborne Media, 2011.
2. Dean, J., Ghemawat, S.: Mapreduce: Simplified data processing on large clusters. CACM 51,107-113(2008)
3. J. Ekanayake, et al., "Twister: A Runtime for Itera tive MapReduce," presented at the First International Workshop on MapReduce and its Applications (MAPREDUCE'10)-HPDC2010, 2010.
4. http://en.wikipedia.org/wiki/K-means-clustering
5. MPI. MPI(Message Passing Interface). Available: http://wwwunix. mcs.anl.gov/mpi/
6. PVM. PVM(Parallel Virtual Machine). Available: http://www.csm.ornl.gov/pvm
7. Hadoo p, http://hadoop.apache.org/