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You're reading from  Fast Data Processing with Spark 2 - Third Edition

Product typeBook
Published inOct 2016
Reading LevelBeginner
PublisherPackt
ISBN-139781785889271
Edition3rd Edition
Languages
Scala
Tools
Apache Spark
Concepts
Data Processing
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Author (1)
Holden Karau
Holden Karau
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Holden Karau

Holden Karau is a software development engineer and is active in the open source. She has worked on a variety of search, classification, and distributed systems problems at IBM, Alpine, Databricks, Google, Foursquare, and Amazon. She graduated from the University of Waterloo with a bachelor's of mathematics degree in computer science. Other than software, she enjoys playing with fire and hula hoops, and welding.
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Algorithms

Now we dive into the most interesting part of GraphX: algorithms and the graph parallel computation APIs to implement more algorithms. The following table shows a bird's eye view of the algorithms:

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Fast Data Processing with Spark 2 - Third Edition
Published in: Oct 2016Publisher: PacktISBN-13: 9781785889271
© 2016 Packt Publishing Limited All Rights Reserved

Author (1)

author image
Holden Karau

Holden Karau is a software development engineer and is active in the open source. She has worked on a variety of search, classification, and distributed systems problems at IBM, Alpine, Databricks, Google, Foursquare, and Amazon. She graduated from the University of Waterloo with a bachelor's of mathematics degree in computer science. Other than software, she enjoys playing with fire and hula hoops, and welding.
Read more about Holden Karau

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Type

GraphX method/example

Graph-Parallel Computation

The method is aggregateMessages(), Function

Pregel(). Refer to https://issues.apache.org/jira/browse/SPARK-5062 for examples.

PageRank

The method is PageRank(). As an example, refer to the influential papers in a citation network, Influencer in retweet. You can specifically check out the following:

staticPageRank(): This provides a static no of iterations and dynamic tolerance; see the parameters (tol versus numIter)

personalizedPageRank(): This is a variation of PageRank that gives a rank relative to a specified "source" vertex in the graph-People

You May Know ShortestPaths and SVD++

The methods are ShortestPaths() and SVD++. As an example, consider the fact that SDV++ takes an RDD of edges.

LabelPropagation (LPA...