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Volumn , Issue , 2012, Pages

Nobody ever got fired for using Hadoop on a cluster

Author keywords

Analytics; Big data; Hadoop; Mapreduce; Scalability

Indexed keywords

ANALYTICS; BIG DATUM; COMMODITY CLUSTERS; DATA ANALYTICS; GENERAL PURPOSE; HADOOP; INPUT DATAS; MAP-REDUCE; POSITION PAPERS; SMALL INPUTS;

EID: 84860587224     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2169090.2169092     Document Type: Conference Paper
Times cited : (55)

References (9)
  • 1
    • 84860570287 scopus 로고    scopus 로고
    • Apache Hadoop. http://hadoop.apache.org/.
  • 2
    • 0002221136 scopus 로고
    • Fast algorithms for mining association rules
    • R. Agrawal and R. Srikant. Fast algorithms for mining association rules. In VLDB, pages 487-499, 1994.
    • (1994) VLDB , pp. 487-499
    • Agrawal, R.1    Srikant, R.2
  • 5
    • 85018467832 scopus 로고    scopus 로고
    • Camdoop: Exploiting in-network aggregation for big data applications
    • Apr.
    • P. Costa, A. Donnelly, A. Rowstron, and G. O'Shea. Camdoop: Exploiting in-network aggregation for big data applications. In NSDI, Apr. 2012.
    • (2012) NSDI
    • Costa, P.1    Donnelly, A.2    Rowstron, A.3    O'Shea, G.4
  • 6
    • 85030321143 scopus 로고    scopus 로고
    • MapReduce: Simplified data processing on large clusters
    • J. Dean and S. Ghemawat. MapReduce: Simplified Data Processing on Large Clusters. In OSDI, 2004.
    • (2004) OSDI
    • Dean, J.1    Ghemawat, S.2
  • 8
    • 77956543367 scopus 로고    scopus 로고
    • Web-scale Bayesian click-through rate prediction for sponsored search advertising in microsofts bing search engine
    • June
    • T. Graepel, J. Q. Candela, T. Borchert, and R. Herbrich. Web-scale bayesian click-through rate prediction for sponsored search advertising in Microsofts Bing search engine. In 27th ICML, June 2010.
    • (2010) 27th ICML
    • Graepel, T.1    Candela, J.Q.2    Borchert, T.3    Herbrich, R.4
  • 9
    • 0002082858 scopus 로고
    • An efficient algorithm for mining association rules in large databases
    • A. Savasere, E. Omiecinski, and S. B. Navathe. An efficient algorithm for mining association rules in large databases. In VLDB, pages 432-444, 1995.
    • (1995) VLDB , pp. 432-444
    • Savasere, A.1    Omiecinski, E.2    Navathe, S.B.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.