July 2017
Intermediate to advanced
796 pages
18h 55m
English
Content preview from Scala and Spark for Big Data Analytics
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Spark GraphX
GraphX is a distributed graph processing framework on top of Spark. Graphs are data structures comprising vertices and the edges connecting them. GraphX provides functions for building graphs, represented as Graph RDDs. It provides an API for expressing graph computation that can model user-defined graphs by using the Pregel abstraction API. It also provides an optimized runtime for this abstraction. GraphX also contains implementations of the most important algorithms of graph theory, such as page rank, connected components, shortest paths, SVD++, and others.
We cover Spark Graphx in detail in Chapter 10, Everything is Connected - GraphX.
A newer module known as GraphFrames is in development, which makes it easier to do Graph ...
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I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.