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Scala Data Analysis Cookbook (new)

You're reading from Scala Data Analysis Cookbook (new) Navigate the world of data analysis, visualization, and machine learning with over 100 hands-on Scala recipes

Product type Paperback

Published in Oct 2015

Publisher

ISBN-13 9781784396749

Length 254 pages

Edition 1st Edition

Languages

Scala

Tools

Apache Spark

Concepts

Data Analysis

Author (1):

Arun Manivannan

View More author details

Table of Contents (9) Chapters

Preface

1. Getting Started with Breeze

2. Getting Started with Apache Spark DataFrames FREE CHAPTER

3. Loading and Preparing Data – DataFrame

4. Data Visualization

5. Learning from Data

6. Scaling Up

7. Going Further

Index

Introduction

In previous chapters, we saw how to import data from a CSV file to Breeze and Spark DataFrames. However, almost all the time, the source data that is to be analyzed is available in a variety of source formats. Spark, with its DataFrame API, provides a uniform API that can be used to represent any source (or multiple sources). In this chapter, we'll focus on the various input formats that we can load from in Spark. Towards the end of this chapter, we'll also briefly see some data preparation recipes.

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Authors (1)

Manivannan

Manivannan

Arun Manivannan has been an engineer in various multinational companies, tier-1 financial institutions, and start-ups, primarily focusing on developing distributed applications that manage and mine data. His languages of choice are Scala and Java, but he also meddles around with various others for kicks. He blogs at http://rerun.me. Arun holds a master's degree in software engineering from the National University of Singapore. He also holds degrees in commerce, computer applications, and HR management. His interests and education could probably be a good dataset for clustering.

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