Book Image

Learning Data Mining with Python

Book Image

Learning Data Mining with Python

Overview of this book

Table of Contents (20 chapters)
Learning Data Mining with Python
About the Author
About the Reviewers

Chapter 12. Working with Big Data

The amount of data is increasing at exponential rates. Today's systems are generating and recording information on customer behavior, distributed systems, network analysis, sensors and many, many more sources. While the current big trend of mobile data is pushing the current growth, the next big thing—the Internet of Things (IoT)—is going to further increase the rate of growth.

What this means for data mining is a new way of thinking. The complex algorithms with high run times need to be improved or discarded, while simpler algorithms that can deal with more samples are becoming more popular to use. As an example, while support vector machines are great classifiers, some variants are difficult to use on very large datasets. In contrast, simpler algorithms such as logistic regression can manage more easily in these scenarios.

In this chapter, we will investigate the following:

  • Big data challenges and applications

  • The MapReduce paradigm

  • Hadoop MapReduce

  • mrjob, a...