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Big Data Analytics with Java

You're reading from Big Data Analytics with Java Data analysis, visualization & machine learning techniques

Product type Paperback

Published in Jul 2017

Publisher Packt

ISBN-13 9781787288980

Length 418 pages

Edition 1st Edition

Languages

Java

Tools

Apache Spark

Concepts

Big Data

Author (1):

RAJAT MEHTA

View More author details

Table of Contents (15) Chapters

Preface

1. Big Data Analytics with Java FREE CHAPTER

2. First Steps in Data Analysis

3. Data Visualization

4. Basics of Machine Learning

5. Regression on Big Data

6. Naive Bayes and Sentiment Analysis

7. Decision Trees

8. Ensembling on Big Data

9. Recommendation Systems

10. Clustering and Customer Segmentation on Big Data

11. Massive Graphs on Big Data

12. Real-Time Analytics on Big Data

13. Deep Learning Using Big Data

Index

Chapter 11. Massive Graphs on Big Data

Graph theory is one of the most important and interesting concepts in computer science. Graphs have been implemented in real life in a lot of use cases. If you use a GPS on your phone or a GPS device and it shows you driving directions to a place, behind the scenes, there is an efficient graph that is working for you to give you the best possible directions. In a social network, you are connected to your friends and your friends are connected to other friends, and so on. This is a massive graph running in production in all the social networks that you use. You can send messages to your friends, follow them, or get followed, all in this graph. Social networks or a database storing driving directions all involve massive amounts of data, and this is not data that can be stored on a single machine; instead, this is distributed across a cluster of thousands of nodes or machines. This massive data is nothing but big data and, in this chapter, we...

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Authors (1)

RAJAT MEHTA

RAJAT MEHTA

The author is a VP (Technical Architect) in technology in JP Morgan Chase in New York. The author is a sun certified java developer and has worked on java related technologies for more than 16 years. Current role for the past few years heavily involves the usage of bid data stack and running analytics on it. Author is also a contributor in various open source projects that are available on his GitHub repository and is also a frequent write on dev magazines.

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