Big Data Processing with Apache Spark: Efficiently tackle large datasets and big data analysis with Spark and Python
Authors: Manuel Ignacio Franco Galeano
ISBN-10: 1789808812
ISBN-13: 9781789808810
Released: 2018-10-31
Print Length 页数: 142 pages
Book Description
Processing big data in real time is challenging due to scalability,information consistency,and fault-tolerance. This book teaches you how to use Spark to make your overall analytical workflow faster and more efficient. You’ll explore all core concepts and tools within the Spark ecosystem,such as Spark Streaming,the Spark Streaming API,machine learning extension,and structured streaming.
You’ll begin by learning data processing fundamentals using Resilient Distributed Datasets (RDDs),SQL,Datasets,and Dataframes APIs. After grasping these fundamentals,you’ll move on to using Spark Streaming APIs to consume data in real time from TCP sockets,and integrate Amazon Web Services (AWS) for stream consumption.
By the end of this book,you’ll not only have understood how to use machine learning extensions and structured streams but you’ll also be able to apply Spark in your own upcoming big data projects.
Contents
What You Will Learn
Write your own Python programs that can interact with Spark
Implement data stream consumption using Apache Spark
Recognize common operations in Spark to process known data streams
Integrate Spark streaming with Amazon Web Services (AWS)
Create a collaborative filtering model with the movielens dataset
Apply processed data streams to Spark machine learning APIs
Authors
Manuel Ignacio Franco Galeano
Manuel Ignacio Franco Galeano is a computer scientist from Colombia. He works for Fender Musical Instruments as a lead engineer in Dublin,Ireland. He holds a master’s degree in computer science from University College,Dublin UCD. His areas of interest and research are music information retrieval,data analytics,distributed systems,and Blockchain technologies.
