March 2019
Beginner to intermediate
182 pages
4h 6m
English
Overview
Dive into the exciting world of big data analytics with 'Hands-On Big Data Analytics with PySpark'. This practical guide offers you the tools and knowledge to tackle massive datasets using PySpark. By exploring real-world examples, you'll learn to unleash the power of distributed systems to analyze and manipulate data at scale.
What this Book will help me do
- Master using PySpark to handle large and complex datasets efficiently and effectively.
- Develop skills to optimize Spark programs using best practices like reducing shuffle operations.
- Learn to set up a PySpark environment, process data from platforms like HDFS, Hive, and S3.
- Enhance your data analytics capabilities by implementing powerful SQL queries and data visualizations.
- Understand testing and debugging techniques to build reliable, production-quality data pipelines.
Author(s)
Authored by Rudy Lai and Bartłomiej Potaczek, both seasoned data engineers and authors in the big data field. Rudy and Bartłomiej bring their extensive experience working with distributed systems and scalable data architectures into this book. Their approach is hands-on, focusing on real-world applications and best practices.
Who is it for?
This book is tailored for data scientists, engineers, and developers eager to advance their big data analytics capabilities. Whether you're new to big data or experienced with other analytics frameworks, this book will equip you with practical knowledge to utilize PySpark for scalable data solutions.
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