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Java Data Analysis

You're reading from   Java Data Analysis Data mining, big data analysis, NoSQL, and data visualization

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Product type Paperback
Published in Sep 2017
Publisher Packt
ISBN-13 9781787285651
Length 412 pages
Edition 1st Edition
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Author (1):
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John R. Hubbard John R. Hubbard
Author Profile Icon John R. Hubbard
John R. Hubbard
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Table of Contents (14) Chapters Close

Preface 1. Introduction to Data Analysis 2. Data Preprocessing FREE CHAPTER 3. Data Visualization 4. Statistics 5. Relational Databases 6. Regression Analysis 7. Classification Analysis 8. Cluster Analysis 9. Recommender Systems 10. NoSQL Databases 11. Big Data Analysis with Java A. Java Tools Index

Why NoSQL and why MongoDB?

In the past decade, dataset sizes, especially for web-based enterprises, have been growing incredibly fast. Storage demands are now in the terabyte range. As this demand increases, developers have to choose between expanding their machine size (scaling up) or distributing their data among many independent machines (scaling out). A growing database is easier to manage, scaling up, but that option is more expensive and eventually limited in size. Scaling out is clearly a better option, but standard Rdbs do not distribute easily or cheaply.

MongoDB is a document-based system that easily scales out. It automatically balances its databases across a cluster, redistributing documents transparently, making it easy to add machines when needed.

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