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.

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Spis treści

Big Data Processing with Apache Spark. Efficiently tackle large datasets and big data analysis with Spark and Python eBook -- spis treści

• 1. Introduction to Spark Distributed Processing
• 2. Introduction to Spark Streaming
• 3. Spark Streaming Integration with AWS
• 4. Spark Streaming, ML, and Windowing Operations