Fast Data Processing with Spark 2 - Third Edition
Krishna Sankar
- 274 pages
- English
- ePUB (mobile friendly)
- Available on iOS & Android
Fast Data Processing with Spark 2 - Third Edition
Krishna Sankar
About This Book
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 Bookâą A quick way to get started with Spark â and reap the rewardsâą From analytics to engineering your big data architecture, we've got it coveredâą Bring your Scala and Java knowledge â 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 Learnâą Install and set up Spark in your clusterâą Prototype distributed applications with Spark's interactive shellâą Perform data wrangling using the new DataFrame APIsâą Get to know the different ways to interact with Spark's distributed representation of data (RDDs)âą Query Spark with a SQL-like query syntaxâą See how Spark works with big dataâą Implement machine learning systems with highly scalable algorithmsâą Use R, the popular statistical language, to work with Sparkâą Apply 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 â 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.
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Fast Data Processing with Spark 2 Third Edition
Fast Data Processing with Spark 2 Third Edition
Credits
| Author Krishna Sankar | Copy Editor Safis Editing |
| Reviewers Sumit Pal Alexis Roos | Project Coordinator Suzzane Coutinho |
| Commissioning Editor Akram Hussain | Proofreader Safis Editing |
| Acquisition Editor Tushar Gupta | Indexer Tejal Daruwale Soni |
| Content Development Editor Nikhil Borkar | Graphics Kirk D'Penha |
| Technical Editor Madhunikita Sunil Chindarkar | Production Coordinator Melwyn D'sa |
About the Author
My first thanks goes to you, the reader, who is taking time to understand the technologies that Apache Spark brings to computation and to the developers of the Spark platform. The book reviewers Sumit and Alexis did a wonderful and thorough job morphing my rough materials into correct readable prose. This book is the result of dedicated work by many at Packt, notably Nikhil Borkar, the Content Development Editor, who deserves all the credit. Madhunikita, as always, has been the guiding force behind the hard work to bring the materials together, in more than one way. On a personal note, my bosses at Volvo viz. Petter Horling, Vedad Cajic, Andreas Wallin, and Mats Gustafsson are a constant source of guidance and insights. And of course, my spouse Usha and son Kaushik always have an encouraging word; special thanks to Ushaâs father Mr.Natarajan, whose wisdom we all rely upon, and my late mom for her kindness.