June 2017
Beginner to intermediate
296 pages
7h 4m
English
Overview
This book introduces you to the world of Big Data processing using Apache Spark and Python. You will learn to set up and run Spark on different systems, process massive datasets, and create solutions to real-world Big Data challenges with over 15 hands-on examples included.
What this Book will help me do
- Understand the basics of Apache Spark and its ecosystem.
- Learn how to process large datasets with Spark RDDs using Python.
- Implement machine learning models with Spark's MLlib library.
- Master real-time data processing with Spark Streaming modules.
- Deploy and run Spark jobs on cloud clusters using AWS EMR.
Author(s)
Frank Kane spent 9 years working at Amazon and IMDb, handling and solving real-world machine learning and Big Data problems. Today, as an instructional designer and educator, he brings his wealth of experience to learners around the globe by creating accessible, practical learning resources. His teaching is clear, engaging, and designed to prepare students for real-world applications.
Who is it for?
This book is ideal for data scientists or data analysts seeking to delve into Big Data processing with Apache Spark. Readers who have foundational knowledge of Python, as well as some understanding of data processing principles, will find this book useful to sharpen their skills further. It is designed for those eager to learn the practical applications of Big Data tools in today's industry environments. By the end of this book, you should feel confident tackling Big Data challenges using Spark and Python.
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