Book Image

Spark for Data Science

By : Srinivas Duvvuri, Bikramaditya Singhal
Book Image

Spark for Data Science

By: Srinivas Duvvuri, Bikramaditya Singhal

Overview of this book

This is the era of Big Data. The words ‘Big Data’ implies big innovation and enables a competitive advantage for businesses. Apache Spark was designed to perform Big Data analytics at scale, and so Spark is equipped with the necessary algorithms and supports multiple programming languages. Whether you are a technologist, a data scientist, or a beginner to Big Data analytics, this book will provide you with all the skills necessary to perform statistical data analysis, data visualization, predictive modeling, and build scalable data products or solutions using Python, Scala, and R. With ample case studies and real-world examples, Spark for Data Science will help you ensure the successful execution of your data science projects.
Table of Contents (18 chapters)
Spark for Data Science
Credits
Foreword
About the Authors
About the Reviewers
www.PacktPub.com
Preface

MLlib and the Pipeline API


Let us first learn some Spark fundamentals to be able to perform the machine learning operations on it. We will discuss the MLlib and the pipeline API in this section.

MLlib

MLlib is the machine learning library built on top of Apache Spark which homes most of the algorithms that can be implemented at scale. The seamless integration of MLlib with other components such as GraphX, SQL, and Streaming provides developers with an opportunity to assemble complex, scalable, and efficient workflows relatively easily. The MLlib library consists of common learning algorithms and utilities including classification, regression, clustering, collaborative filtering, and dimensionality reduction.

MLlib works in conjunction with the spark.ml package which provides a high level Pipeline API. The fundamental difference between these two packages is that MLlib (spark.mllib) works on top of RDDs whereas the ML (spark.ml) package works on top of DataFrames and supports ML Pipeline. Currently...