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Apache Spark 2.x Cookbook

You're reading from Apache Spark 2.x Cookbook Over 70 cloud-ready recipes for distributed Big Data processing and analytics

Product type Paperback

Published in May 2017

Publisher

ISBN-13 9781787127265

Length 294 pages

Edition 1st Edition

Languages

Scala

Tools

Apache Spark

Concepts

Big Data

Author (1):

Rishi Yadav

View More author details

Table of Contents (13) Chapters

Preface

1. Getting Started with Apache Spark FREE CHAPTER

2. Developing Applications with Spark

3. Spark SQL

4. Working with External Data Sources

5. Spark Streaming

6. Getting Started with Machine Learning

7. Supervised Learning with MLlib — Regression

8. Supervised Learning with MLlib — Classification

9. Unsupervised Learning

10. Recommendations Using Collaborative Filtering

11. Graph Processing Using GraphX and GraphFrames

12. Optimizations and Performance Tuning

Understanding feature engineering

When working on a data pipeline, there are two activities that take up most of the time: data cleaning/data preparation and feature extraction. We already covered data cleaning in the previous chapters. In this recipe, we are going to discuss different aspects of feature engineering.

Feature selection

When it comes to feature selection, there are two primary aspects:

Quality of features
Number of features

Quality of features

Every feature is created different from others. Consider the house pricing problem again. Let's look at some of the features of a house:

House size
Lot size
Number of rooms
Number of bathrooms
Type of parking garage (carport versus covered)
School district
Number of dogs barking in the house
Number of birds chirping in backyard trees

The last two features may look ridiculous to you, and you might wonder what that has got to do with the house price, and you are right. At the same time, if these features are given to the machine learning algorithm,...

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Authors (1)

Yadav

Yadav

Rishi Yadav has 19 years of experience in designing and developing enterprise applications. He is an open source software expert and advises American companies on big data and public cloud trends. Rishi was honored as one of Silicon Valley's 40 under 40 in 2014. He earned his bachelor's degree from the prestigious Indian Institute of Technology, Delhi, in 1998. About 12 years ago, Rishi started InfoObjects, a company that helps data-driven businesses gain new insights into data. InfoObjects combines the power of open source and big data to solve business challenges for its clients and has a special focus on Apache Spark. The company has been on the Inc. 5000 list of the fastest growing companies for 6 years in a row. InfoObjects has also been named the best place to work in the Bay Area in 2014 and 2015. Rishi is an open source contributor and active blogger. This book is dedicated to my parents, Ganesh and Bhagwati Yadav; I would not be where I am without their unconditional support, trust, and providing me the freedom to choose a path of my own. Special thanks go to my life partner, Anjali, for providing immense support and putting up with my long, arduous hours (yet again).Our 9-year-old son, Vedant, and niece, Kashmira, were the unrelenting force behind keeping me and the book on track. Big thanks to InfoObjects' CTO and my business partner, Sudhir Jangir, for providing valuable feedback and also contributing with recipes on enterprise security, a topic he is passionate about; to our SVP, Bart Hickenlooper, for taking the charge in leading the company to the next level; to Tanmoy Chowdhury and Neeraj Gupta for their valuable advice; to Yogesh Chandani, Animesh Chauhan, and Katie Nelson for running operations skillfully so that I could focus on this book; and to our internal review team (especially Rakesh Chandran) for ironing out the kinks. I would also like to thank Marcel Izumi for, as always, providing creative visuals. I cannot miss thanking our dog, Sparky, for giving me company on my long nights out. Last but not least, special thanks to our valuable clients, partners, and employees, who have made InfoObjects the best place to work at and, needless to say, an immensely successful organization.

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