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Introduction to Categorical Programming (Revised)
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MAP REDUCE BASICS CHAPTER 2. Basics Divide and conquer – Partition large problem into smaller subproblems – Worker work on subproblems in parallel Threads
Documents MAP REDUCE BASICS CHAPTER 2. Basics Divide and conquer – Partition large problem into smaller subproblems – Worker work on subproblems in parallel Threads

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MapReduce: Simplified Data Processing on Large Clusters Cloud Computing Seminar SEECS, NUST By Dr. Zahid Anwar
Documents MapReduce: Simplified Data Processing on Large Clusters Cloud Computing Seminar SEECS, NUST By Dr. Zahid Anwar

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Cloud Computing Lecture #2 Introduction to MapReduce Jimmy Lin The iSchool University of Maryland Monday, September 8, 2008 This work is licensed under
Documents Cloud Computing Lecture #2 Introduction to MapReduce Jimmy Lin The iSchool University of Maryland Monday, September 8, 2008 This work is licensed under

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Sixteen lists and compound data. Recap Names: constants and variables When evaluated, return a specific data objects Can make new names with: [define
Documents Sixteen lists and compound data. Recap Names: constants and variables When evaluated, return a specific data objects Can make new names with: [define

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Fifteen high-level operations on pictures. Recap: vector graphics constructors [box width height] Creates a picture with a box [group pictures …] Makes
Documents Fifteen high-level operations on pictures. Recap: vector graphics constructors [box width height] Creates a picture with a box [group pictures …] Makes

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Cloud Computing Lecture #2 From Lisp to MapReduce and GFS Jimmy Lin The iSchool University of Maryland Wednesday, January 30, 2008 This work is licensed
Documents Cloud Computing Lecture #2 From Lisp to MapReduce and GFS Jimmy Lin The iSchool University of Maryland Wednesday, January 30, 2008 This work is licensed

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Lecture 2 – MapReduce: Theory and Implementation CSE 490H This presentation incorporates content licensed under the Creative Commons Attribution 2.5 License
Documents Lecture 2 – MapReduce: Theory and Implementation CSE 490H This presentation incorporates content licensed under the Creative Commons Attribution 2.5 License

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Lecture 2 – MapReduce: Theory and Implementation CSE 490h – Introduction to Distributed Computing, Spring 2007 Except as otherwise noted, the content of
Documents Lecture 2 – MapReduce: Theory and Implementation CSE 490h – Introduction to Distributed Computing, Spring 2007 Except as otherwise noted, the content of

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