Book Image

Apache Spark Machine Learning Blueprints

By : Alex Liu
Book Image

Apache Spark Machine Learning Blueprints

By: Alex Liu

Overview of this book

There's a reason why Apache Spark has become one of the most popular tools in Machine Learning – its ability to handle huge datasets at an impressive speed means you can be much more responsive to the data at your disposal. This book shows you Spark at its very best, demonstrating how to connect it with R and unlock maximum value not only from the tool but also from your data. Packed with a range of project "blueprints" that demonstrate some of the most interesting challenges that Spark can help you tackle, you'll find out how to use Spark notebooks and access, clean, and join different datasets before putting your knowledge into practice with some real-world projects, in which you will see how Spark Machine Learning can help you with everything from fraud detection to analyzing customer attrition. You'll also find out how to build a recommendation engine using Spark's parallel computing powers.
Table of Contents (18 chapters)
Apache Spark Machine Learning Blueprints
Credits
About the Author
About the Reviewer
www.PacktPub.com
Preface
Index

Feature preparation


In section, Feature extraction, of Chapter 2, Data Preparation for Spark ML, we reviewed a few methods for feature extraction and discussed their implementation on Apache Spark. All the techniques discussed there can be applied to our data here, especially the ones utilizing time series and feature comparison to create new features.

For this project, feature extraction is one of the most important tasks because all the fraud happens online and the web log is the most important and most recent data to predict frauds, which needs extraction to produce features ready for modeling.

Also, as we have features for transactions, users, bank accounts, and computer devices, a lot of work is needed to merge all these features together to form a complete data file ready for machine learning.

Feature extraction from LogFile

Log files are always unstructured, similarly to a collection of random symbols and numbers. One example of this is as follows:

May 23 12:19:11 elcap siu: 'siu root...