Experiences with MapReduce, an Abstraction for Large-Scale Computation Jeff Dean Google, Inc. 2 Outline • Overview of our computing environment • MapReduce – overview, examples – implementation details – usage stats • Implications for paralle
Experiences with MapReduce, an Abstraction for Large-Scale Computation Jeff Dean Google, Inc. 2 Outline • Overview of our computing environment • MapReduce – overview, examples – implementation details – usage stats • Implications for parallel program development 3 Problem: lots of data • Example: 20+ billion web pages x 20KB = 400+ terabytes • One computer can read 30-35 MB/sec from disk – ~four
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http://www.gustavus.edu/%20max/concrete-abstractions-pdfs/list.cfm
日本ソフトウェア科å¦ä¼šç¬¬ 23 回大会（2006 年度）論文集 1 アスペクト指å‘プãƒã‚°ãƒ©ãƒŸãƒ³ã‚°ã«ãŠã‘ã‚‹ テストã«åŸºã¥ã„ãŸãƒã‚¤ãƒ³ãƒˆã‚«ãƒƒãƒˆã®æ案 櫻井 åå¹³ 増原 英彦 Kouhei Sakurai Hidehiko Masuhara æ±ï¿½ï¿½
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http://www4.informatik.uni-erlangen.de/~wasif/pubs/DAW04_PDF.pdf
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https://people.csail.mit.edu/gregs/ivme03.pdf
Higher-Order and Symbolic Computation 12, 381–391 (1999) c 2000 Kluwer Academic Publishers. Manufactured in The Netherlands. Partial Evaluation of Computation Process— An Approach to a Compiler-Compiler YOSHIHIKO FUTAMURA Central Research Laboratory
http://www.cs.iastate.edu/~leavens/FOAL/papers-2002/masuhara-kiczales-dutchyn.pdf
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Continuation Join Points Yusuke Endoh Department of Computer Science, University of Tokyo 
Hidehiko Masuhara: Publications
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