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Apache spark graph processing : build, process, and analyze large-scale graphs with Spark /
Chapter 2: Building and Exploring Graphs; Network datasets; The communication network; Flavor networks; Social ego networks; Graph builders; The Graph factory method; edgeListFile; fromEdges; fromEdgeTuples; Building graphs; Building directed graphs; Building a bipartite graph; Building a weighted s...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Otros Autores: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Birmingham, UK :
Packt Publishing,
[2015]
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| Colección: | Community experience distilled.
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| Temas: | |
| Acceso en línea: | Texto completo Texto completo |
MARC
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| 100 | 1 | |a Ramamonjison, Rindra, |e author. | |
| 245 | 1 | 0 | |a Apache spark graph processing : |b build, process, and analyze large-scale graphs with Spark / |c Rindra Ramamonjison ; foreword by Denny Lee. |
| 246 | 3 | 0 | |a Build, process, and analyze large-scale graphs with Spark |
| 264 | 1 | |a Birmingham, UK : |b Packt Publishing, |c [2015] | |
| 264 | 4 | |c ©2015 | |
| 300 | |a 1 online resource (1 volume) : |b illustrations | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 347 | |a text file | ||
| 490 | 1 | |a Community experience distilled | |
| 504 | |a Includes bibliographical references and index. | ||
| 588 | 0 | |a Online resource; title from cover page (Safari, viewed September 28, 2015). | |
| 505 | 0 | |a Cover; Copyright; Credits; Foreword; About the Author; About the Reviewer; www.PacktPub.com; Table of Contents; Preface; Chapter 1: Getting Started with Spark and GraphX; Downloading and installing Spark 1.4.1; Experimenting with the Spark shell; Getting started with GraphX; Building a tiny social network; Loading the data; The property graph; Transforming RDDs to VertexRDD and EdgeRDD; Introducing graph operations; Building and submitting a standalone application; Writing and configuring a Spark program; Building the program with the Scala Build Tool; Deploying and running with spark-submit. | |
| 505 | 8 | |a The graph visualizationInstalling the GraphStream and BreezeViz libraries; Visualizing the graph data; Plotting the degree distribution; The analysis of network connectedness; Finding the connected components; Counting triangles and computing clustering coefficients; The network centrality and PageRank; How PageRank works; Ranking web pages; Scala Build Tool revisited; Organizing build definitions; Managing library dependencies; A preview of the steps; Running tasks with SBT commands; Summary; Chapter 4: Transforming and Shaping Up Graphs to Your Needs. | |
| 505 | 8 | |a Transforming the vertex and edge attributesmapVertices; mapEdges; mapTriplets; Modifying graph structures; The reverse operator; The subgraph operator; The mask operator; The groupEdges operator; Joining graph datasets; joinVertices; outerJoinVertices; Example -- Hollywood movie graph; Data operations on VertexRDD and EdgeRDD; Mapping VertexRDD and EdgeRDD; Filtering VertexRDDs; Joining VertexRDDs; Joining EdgeRDDs; Reversing edge directions; Collecting neighboring information; Example -- from food network to flavor pairing; Summary; Chapter 5: Creating Custom Graph Aggregation Operators. | |
| 505 | 8 | |a NCAA College Basketball datasetsThe aggregateMessages operator; EdgeContext; Abstracting out the aggregation; Keeping things DRY; Coach wants more numbers; Calculating average points per game; Defense stats -- D matters as in direction; Joining average stats into a graph; Performance optimization; The MapReduceTriplets operator; Summary; Chapter 6: Iterative Graph-Parallel Processing with Pregel; The Pregel computational model; Example -- iterating towards the social equality; The Pregel API in GraphX; Community detection through label propagation; The Pregel implementation of PageRank; Summary. | |
| 520 | |a Chapter 2: Building and Exploring Graphs; Network datasets; The communication network; Flavor networks; Social ego networks; Graph builders; The Graph factory method; edgeListFile; fromEdges; fromEdgeTuples; Building graphs; Building directed graphs; Building a bipartite graph; Building a weighted social ego network; Computing the degrees of the network nodes; In-degree and out-degree of the Enron email network; Degrees in the bipartite food network; Degree histogram of the social ego networks; Summary; Chapter 3: Graph Analysis and Visualization; Network datasets. | ||
| 546 | |a English. | ||
| 590 | |a eBooks on EBSCOhost |b EBSCO eBook Subscription Academic Collection - Worldwide | ||
| 590 | |a O'Reilly |b O'Reilly Online Learning: Academic/Public Library Edition | ||
| 630 | 0 | 0 | |a Spark (Electronic resource : Apache Software Foundation) |
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| 700 | 1 | |a Lee, Denny, |e author of introduction, etc. | |
| 776 | 0 | 8 | |i Print version: |a Ramamonjison, Rindra. |t Apache Spark Graph Processing. |d Birmingham : Packt Publishing Ltd, ©2015 |z 9781784391805 |
| 830 | 0 | |a Community experience distilled. | |
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