Fast Data Processing with Spark 2 - Third Edition (PDF)

Learn how to use Spark to process big data at speed and scale for sharper analytics. Put the principles into practice for faster, slicker big data projects.About This BookA quick way to get started with Spark - and reap the rewardsFrom analytics to engineering your big data architecture, we've got it coveredBring your Scala and Java knowledge - and put it to work on new and exciting problemsWho This Book Is ForThis book is for developers with little to no knowledge of Spark, but with a background in Scala/Java programming. It's recommended that you have experience in dealing and working with big data and a strong interest in data science.What You Will LearnInstall and set up Spark in your clusterPrototype distributed applications with Spark's interactive shellPerform data wrangling using the new DataFrame APIsGet to know the different ways to interact with Spark's distributed representation of data (RDDs)Query Spark with a SQL-like query syntaxSee how Spark works with big dataImplement machine learning systems with highly scalable algorithmsUse R, the popular statistical language, to work with SparkApply interesting graph algorithms and graph processing with GraphXIn DetailWhen 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.Style and approachThis book is a basic, step-by-step tutorial that will help you take advantage of all that Spark has to offer.