Big Data Processing with Apache Spark
Franco Galeano, Manuel Ignacio
Sold by GreatBookPricesUK, Woodford Green, United Kingdom
AbeBooks Seller since January 28, 2020
New - Soft cover
Condition: New
Quantity: Over 20 available
Add to basketSold by GreatBookPricesUK, Woodford Green, United Kingdom
AbeBooks Seller since January 28, 2020
Condition: New
Quantity: Over 20 available
Add to basketNo need to spend hours ploughing through endless data - let Spark, one of the fastest big data processing engines available, do the hard work for you.
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.
Data Processing with Apache Spark is for you if you are a software engineer, architect, or IT professional who wants to explore distributed systems and big data analytics. Although you don't need any knowledge of Spark, prior experience of working with Python is recommended.
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.
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