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CS 49995 & CS 63016 ST: Big Data Analytics

CS 49995 & CS 63016 ST: Big Data Analytics

CS 49995 & CS 63016 ST: Big Data Analytics. Chapter 4: MapReduce. Xiang Lian Department of Computer Science Kent State University Email: xlian@kent.edu Homepage: http ://www.cs.kent.edu/~xlian/. Objectives. In this chapter, you will: Learn the background of MapReduce

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765 views • 76 slides
CS 63016 & CS 73016 Big Data Analytics

CS 63016 & CS 73016 Big Data Analytics

CS 63016 & CS 73016 Big Data Analytics. Chapter 4: MapReduce. Xiang Lian Department of Computer Science Kent State University Email: xlian@kent.edu Homepage: http ://www.cs.kent.edu/~xlian/. Objectives. In this chapter, you will: Learn the background of MapReduce

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767 views • 76 slides
CS 61C: Great Ideas in Computer Architecture (Machine Structures) Map Reduce

CS 61C: Great Ideas in Computer Architecture (Machine Structures) Map Reduce

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591 views • 59 slides

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440 views • 43 slides
MapReduce : Simplified Data Processing on Large Clusters

MapReduce : Simplified Data Processing on Large Clusters

MapReduce : Simplified Data Processing on Large Clusters. Jeffrey Dean & Sanjay Ghemawat. Presented by: Hemanth Makkapati (makka@vt.edu). Appeared in: OSDI '04: Sixth Symposium on Operating System Design and Implementation, San Francisco, CA, December, 2004. Mom told Sam.

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416 views • 39 slides

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411 views • 34 slides
Scott Beamer, Instructor

Scott Beamer, Instructor

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343 views • 34 slides
Distributed Computing Seminar

Distributed Computing Seminar

Distributed Computing Seminar. MapReduce Theory and Implementation. Christophe Bisciglia, Aaron Kimball, & Sierra Michels-Slettvet Summer 2007. Except as otherwise noted, the content of this presentation is (c) 2007 Google Inc. and licensed under the Creative Commons Attribution 3.0 License.

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429 views • 30 slides
MapReduce

MapReduce

MapReduce. Costin Raiciu Advanced Topics in Distributed Systems, 2010. Functional Programming Review. Functional operations do not modify data structures: They always create new ones Original data still exists in unmodified form Data flows are implicit in program design

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456 views • 29 slides
MapReduce Programming Model

MapReduce Programming Model

MapReduce Programming Model. HP Cluster Computing Challenges. Programmability: need to parallelize algorithms manually Must look at problems from parallel standpoint Tightly coupled problems require frequent communication (more of the slow part!) We want to decouple the problem

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271 views • 25 slides
MAP REDUCE PROGRAMMING

MAP REDUCE PROGRAMMING

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398 views • 21 slides

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