When people want a way to process big data at speed, Spark is invariably the solution. With its ease of development (in comparison to the relative complexity of Hadoop), it’s unsurprising that it’s becoming popular with data analysts and engineers everywhere.
Beginning with the fundamentals, we’ll show you how to get set up with Spark with minimum fuss. You’ll then get to grips with some simple APIs before investigating machine learning and graph processing – throughout we’ll make sure you know exactly how to apply your knowledge.
You will also learn how to use the Spark shell, how to load data before finding out how to build and run your own Spark applications. Discover how to manipulate your RDD and get stuck into a range of DataFrame APIs. As if that’s not enough, you’ll also learn some useful Machine Learning algorithms with the help of Spark MLlib and integrating Spark with R. We’ll also make sure you’re confident and prepared for graph processing, as you learn more about the GraphX API.

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Spis treści

Fast Data Processing with Spark 2. Accelerate your data for rapid insight - Third Edition eBook -- spis treści

• 1. Installing Spark and Setting Up Your Cluster
• 2. Using the Spark Shell
• 3. Building and Running a Spark Application
• 4. Creating a SparkSession
• 5. Loading and Saving Data in Spark
• 6. Manipulating Your RDD
• 7. Spark 2.0 Concepts
• 8. Spark SQL
• 9. Foundations of Da-tasets/DataFrames - The pro-verbial workhorse for DataSci-entists
• 10. Spark with Big Data
• 11. Machine Learning with Spark ML Pipelines
• 12. Graphx