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Volumn 6, Issue 14, 2013, Pages 1750-1761

Understanding insights into the basic structure and essential issues of table placement methods in clusters

Author keywords

[No Author keywords available]

Indexed keywords

ADVANCED ANALYTICS; BENCHMARKING; BIG DATA; DATA ANALYTICS; DISTRIBUTED COMPUTER SYSTEMS; DISTRIBUTED DATABASE SYSTEMS;

EID: 84891051134     PISSN: None     EISSN: 21508097     Source Type: Journal    
DOI: 10.14778/2556549.2556559     Document Type: Article
Times cited : (19)

References (27)
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    • http://docs.hortonworks.com/HDPDocuments/HDP1/ HDP-1.3.0/bk cluster-planning-guide/content/ hardware-for-slave.html.
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    • https://issues.apache.org/jira/browse/HIVE-600.
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    • https://issues.apache.org/jira/browse/HIVE-4246.
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    • http://www.slideshare.net/oom65/ orc-andvectorizationhadoopsummit.
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    • SS-DB: A Standard Science DBMS Benchmark
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    • Cheetah: A High Performance, Custom Data Warehouse on Top of MapReduce
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    • Mastiff: A Mapreduce-based System for Time-Based Big Data Analytics
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    • Guo, S.1    Xiong, J.2    Wang, W.3    Lee, R.4
  • 22
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    • RCFile: A Fast and Space-efficient Data Placement Structure in MapReduce-based Warehouse Systems
    • Y. He, R. Lee, Y. Huai, Z. Shao, N. Jain, X. Zhang, and Z. Xu. RCFile: A Fast and Space-efficient Data Placement Structure in MapReduce-based Warehouse Systems. In ICDE, 2011.
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    • He, Y.1    Lee, R.2    Huai, Y.3    Shao, Z.4    Jain, N.5    Zhang, X.6    Xu, Z.7
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    • Trojan Data Layouts: Right Shoes for a Running Elephant
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    • Llama: Leveraging Columnar Storage for Scalable Join Processing in the Mapreduce Framework
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.