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Apache Spark 2: Data Processing and Real-Time Analytics

You're reading from   Apache Spark 2: Data Processing and Real-Time Analytics Master complex big data processing, stream analytics, and machine learning with Apache Spark

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Product type Course
Published in Dec 2018
Publisher Packt
ISBN-13 9781789959208
Length 616 pages
Edition 1st Edition
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Authors (7):
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Sridhar Alla Sridhar Alla
Author Profile Icon Sridhar Alla
Sridhar Alla
Romeo Kienzler Romeo Kienzler
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Romeo Kienzler
Siamak Amirghodsi Siamak Amirghodsi
Author Profile Icon Siamak Amirghodsi
Siamak Amirghodsi
Broderick Hall Broderick Hall
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Broderick Hall
Md. Rezaul Karim Md. Rezaul Karim
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Md. Rezaul Karim
Meenakshi Rajendran Meenakshi Rajendran
Author Profile Icon Meenakshi Rajendran
Meenakshi Rajendran
Shuen Mei Shuen Mei
Author Profile Icon Shuen Mei
Shuen Mei
+3 more Show less
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Table of Contents (23) Chapters Close

Title Page
Copyright
About Packt
Contributors
Preface
1. A First Taste and What's New in Apache Spark V2 FREE CHAPTER 2. Apache Spark Streaming 3. Structured Streaming 4. Apache Spark MLlib 5. Apache SparkML 6. Apache SystemML 7. Apache Spark GraphX 8. Spark Tuning 9. Testing and Debugging Spark 10. Practical Machine Learning with Spark Using Scala 11. Spark's Three Data Musketeers for Machine Learning - Perfect Together 12. Common Recipes for Implementing a Robust Machine Learning System 13. Recommendation Engine that Scales with Spark 14. Unsupervised Clustering with Apache Spark 2.0 15. Implementing Text Analytics with Spark 2.0 ML Library 16. Spark Streaming and Machine Learning Library 1. Other Books You May Enjoy Index

Graph analytics/processing with GraphX


This section will examine Apache Spark GraphX programming in Scala using the family relationship graph data sample shown in the last section. This data will be accessed as a list of vertices and edges. Although this data set is small, the graphs that you build in this way could be very large. For example, we've been able to analyze 30 TB of financial transaction data of a large bank using only four Apache Spark workers.

The raw data

We are working with two data files. They contain the data that will be used for this section in terms of the vertices and edges that make up a graph:

graph1_edges.csv
graph1_vertex.csv

The vertex file contains just six lines representing the graph used in the last section. Each vertex represents a person and has a vertex ID number, a name, and an age value:

1,Mike,48
2,Sarah,45
3,John,25
4,Jim,53
5,Kate,22
6,Flo,52

The edge file contains a set of directed edge values in the form source vertex ID, destination vertex ID, and relationship...

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