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Fast data processing with Spark 2 : 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 / Krishna Sankar.

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Format:
Book
Author/Creator:
Sankar, Krishna, author.
Language:
English
Subjects (All):
Spark (Electronic resource : Apache Software Foundation).
Real-time data processing.
Physical Description:
1 online resource (269 pages) : illustrations, tables
Edition:
Third edition.
Other Title:
Fast data processing with Spark two
Place of Publication:
Birmingham, England : Packt Publishing, 2016.
System Details:
text file
Biography/History:
Sankar Krishna: Krishna Sankar is an AI data scientist with Volvo Cars focusing on autonomous vehicles. Previously, he was the chief data scientist at blackarrow, where he was focusing on optimizing user experience via inference, intelligence, and interfaces. He was the director of a data science/bioinformatics startup and also worked as a distinguished engineer at Cisco. He has been speaking at various conferences as well as guest lecturing at the Naval Postgraduate School. His other passion is Lego Robotics. You'll find him at the St. Louis FLL World Competition as the robot design judge. Karau Holden: Holden Karau is a software development engineer and is active in the open source. She has worked on a variety of search, classification, and distributed systems problems at IBM, Alpine, Databricks, Google, Foursquare, and Amazon. She graduated from the University of Waterloo with a bachelor's of mathematics degree in computer science. Other than software, she enjoys playing with fire and hula hoops, and welding.
Summary:
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 Book A quick way to get started with Spark ? and reap the rewards From analytics to engineering your big data architecture, we've got it covered Bring your Scala and Java knowledge ? and put it to work on new and exciting problems Who This Book Is For This 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 Learn Install and set up Spark in your cluster Prototype distributed applications with Spark's interactive shell Perform data wrangling using the new DataFrame APIs Get to know the different ways to interact with Spark's distributed representation of data (RDDs) Query Spark with a SQL-like query syntax See how Spark works with big data Implement machine learning systems with highly scalable algorithms Use R, the popular statistical language, to work with Spark Apply interesting graph algorithms and graph processing with GraphX In Detail 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. Style and approach This book is a basic, step-by-step tutorial that will help you take advantage of all that Spark has to offer.
Contents:
Fast Data Processing with Spark 2: Accelerate your data for rapid insight
Notes:
Includes bibliographical references at the end of each chapters and index.
Description based on online resource; title from PDF title page (ebrary, viewed March 1, 2017).
ISBN:
9781785882968
1785882961
OCLC:
962192230

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