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Scala and Spark for Big Data Analytics

You're reading from  Scala and Spark for Big Data Analytics

Product type Book
Published in Jul 2017
Publisher Packt
ISBN-13 9781785280849
Pages 796 pages
Edition 1st Edition
Languages
Concepts
Authors (2):
Md. Rezaul Karim Md. Rezaul Karim
Profile icon Md. Rezaul Karim
Sridhar Alla Sridhar Alla
Profile icon Sridhar Alla
View More author details
Toc

Table of Contents (19) Chapters close

Preface 1. Introduction to Scala 2. Object-Oriented Scala 3. Functional Programming Concepts 4. Collection APIs 5. Tackle Big Data – Spark Comes to the Party 6. Start Working with Spark – REPL and RDDs 7. Special RDD Operations 8. Introduce a Little Structure - Spark SQL 9. Stream Me Up, Scotty - Spark Streaming 10. Everything is Connected - GraphX 11. Learning Machine Learning - Spark MLlib and Spark ML 12. My Name is Bayes, Naive Bayes 13. Time to Put Some Order - Cluster Your Data with Spark MLlib 14. Text Analytics Using Spark ML 15. Spark Tuning 16. Time to Go to ClusterLand - Deploying Spark on a Cluster 17. Testing and Debugging Spark 18. PySpark and SparkR

A brief introduction to graph theory

To better understand graphs, let's look at Facebook and how you typically use Facebook. Every day you use your smart phone to post messages on your friend's wall or update your status. Your friends are all posting messages and photos and videos of their own.

You have friends, your friends have friends, who have friends, and so on. Facebook has settings that let you make new friends or remove friends from your friend list. Facebook also has permissions, which allow granular control on who sees what and who can communicate with who.

Now, when you consider that there are a billion Facebook users, the friends and friend's friends list for all users gets quite large and complicated. It is hard to even comprehend and manage all the different relationships or friendships.

So, if someone wants to find out if you and another person X...

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