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1
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Massively parallel data analysis with pacts on nephele
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[ABE+10] Alexander Alexandrov, Dominic Battré, Stephan Ewen, Max Heimel, Fabian Hueske, Odej Kao, Volker Markl, Erik Nijkamp, and Daniel Warneke. Massively Parallel Data Analysis with PACTs on Nephele. PVLDB, 3(2), 2010.
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2
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79957809015
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HadoopDB: An architectural hybrid of mapreduce and DBMS technologies for analytical workloads
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[ABPA+09] Azza Abouzeid, Kamil Bajda-Pawlikowski, Daniel J. Abadi, Alexander Rasin, and Avi Silberschatz. HadoopDB: An Architectural Hybrid of MapReduce and DBMS Technologies for Analytical Workloads. PVLDB, 2(1):922-933, 2009.
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3
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79958269648
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ASTERIX:towards a scalable, semistructured data platform for evolvingworld models
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[BBC+11]
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[BBC+11] Alexander Behm, Vinayak R. Borkar, Michael J. Carey, Raman Grover, Chen Li, Nicola Onose, Rares Vernica, Alin Deutsch, Yannis Papakonstantinou, and Vassilis J. Tsotras. ASTERIX: Towards a scalable, semistructured data platform for evolvingworld models. Distributed and Parallel Databases, 29(3):185-216, 2011.
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HaLoop: Efficient iterative data processing on large clusters
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[BHBE10] Yingyi Bu, Bill Howe, Magdalena Balazinska, and Michael D. Ernst. HaLoop: Efficient Iterative Data Processing on Large Clusters. PVLDB, 3(1), 2010.
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Efficient processing of data warehousing queries in a split execution environment
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[BPASP11] Kamil Bajda-Pawlikowski, Daniel J. Abadi, Avi Silberschatz, and Erik Paulson. Efficient processing of data warehousing queries in a split execution environment. In SIGMOD, pages 1165-1176, 2011.
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FunSQL: It is time to make SQL functional
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[BRFR12] Carsten Binnig, Robin Rehrmann, Franz Faerber, and Rudolf Riewe. FunSQL: it is time to make SQL functional. In EDBT/ICDT Workshops, pages 41-46, 2012.
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MapReduce: Simplified data processing on large clusters
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[DG08] Jeffrey Dean and Sanjay Ghemawat. MapReduce: Simplified data processing on large clusters. Commun. ACM, 51(1):107-113, 2008.
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Dean, J.1
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8
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Hadoop++: Making a yellow elephant run like a cheetah (Without It Even Noticing)
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[DQRJ+10] Jens Dittrich, Jorge-Arnulfo Quiané-Ruiz, Alekh Jindal, Yagiz Kargin, Vinay Setty, and Jörg Schad. Hadoop++: Making a Yellow Elephant Run Like a Cheetah (Without It Even Noticing). PVLDB, 3(1):518-529, 2010.
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[HAD12] Apache Hadoop. http://hadoop.apache.org, 2012.
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10
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[KST12] Tim Kaldewey, Eugene J. Shekita, and Sandeep Tata. Clydesdale: Structured data processing on MapReduce. In EDBT, pages 15-25, 2012.
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[Ord05] Carlos Ordonez. Optimizing recursive queries in SQL. In SIGMOD Conference, pages 834-839, 2005.
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Pig latin: A not-so-foreign language for data processing
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[ORS+08] Christopher Olston, Benjamin Reed, Utkarsh Srivastava, Ravi Kumar, and Andrew Tomkins. Pig latin: A not-so-foreign language for data processing. In SIGMOD, pages 1099-1110, 2008.
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[SQL12] SAP HANASQLScript Reference. http://help.sap.com/hana/hana dev sqlscript en.pdf, 2012.
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[TPC12] TPC-H. http://www.tpc.org/tpch/, 2012.
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16
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Hive -A petabyte scale data warehouse using Hadoop
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[TSJ+10]
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[TSJ+10] Ashish Thusoo, Joydeep Sen Sarma, Namit Jain, Zheng Shao, Prasad Chakka, Ning Zhang, Suresh Anthony, Hao Liu, and Raghotham Murthy. Hive -A petabyte scale data warehouse using Hadoop. In ICDE, pages 996-1005, 2010.
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