Jeffrey Aven - Data Analytics with Spark Using Python

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Jeffrey Aven

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ISBN-13: 978-0-13-484601-9
ISBN-10: 0-13-484601-X

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codemantra

Spark is at the heart of the disruptive Big Data and open source software revolution. The interest in and use of Spark have grown exponentially, with no signs of abating. This book will prepare you, step by step, for a prosperous career in the Big Data analytics field.

This book focuses on the fundamentals of the Spark project, starting from the core and working outward into Sparks various extensions, related or subprojects, and the broader ecosystem of open source technologies such as Hadoop, Kafka, Cassandra, and more.

Although the foundational understanding of Spark concepts covered in this bookincluding the runtime, cluster and application architectureare language independent and agnostic, the majority of the programming examples and exercises in this book are written in Python. The Python API for Spark (PySpark) provides an intuitive programming environment for data analysts, data engineers, and data scientists alike, offering developers the flexibility and extensibility of Python with the distributed processing power and scalability of Spark.

The scope of this book is quite broad, covering aspects of Spark from core Spark programming to Spark SQL, Spark Streaming, machine learning, and more. This book provides a good introduction and overview for each topicenough of a platform for you to build upon any particular area or discipline within the Spark project.

This book is intended for data analysts and engineers looking to enter the Big Data space or consolidate their knowledge in this area. The demand for engineers with skills in Big Data and its preeminent processing framework, Spark, is exceptionally high at present. This book aims to prepare readers for this growing employment market and arm them with the skills employers are looking for.

Python experience is useful but not strictly necessary for readers of this book as Python is quite intuitive for anyone with any programming experience whatsoever. A good working knowledge of data analysis and manipulation would also be helpful. This book is especially well suited to data warehouse professionals interested in expanding their careers into the Big Data area.