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Fast Data Processing with Spark 2 Third Edition.pdf
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Fast_Data_Processing_with_Spark_2_-_Third_Edition.pdf, Spark快速数据处理,第三版
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Fast Data Processing with
Spark 2
Third Edition
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
BIRMINGHAM - MUMBAI
Fast Data Processing with Spark 2
Third Edition
Copyright © 2016 Packt Publishing
All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or
transmitted in any form or by any means, without the prior written permission of the
publisher, except in the case of brief quotations embedded in critical articles or reviews.
Every effort has been made in the preparation of this book to ensure the accuracy of the
information presented. However, the information contained in this book is sold without
warranty, either express or implied. Neither the authors, nor Packt Publishing, and its
dealers and distributors will be held liable for any damages caused or alleged to be caused
directly or indirectly by this book.
Packt Publishing has endeavored to provide trademark information about all of the
companies and products mentioned in this book by the appropriate use of capitals.
However, Packt Publishing cannot guarantee the accuracy of this information.
First published: October 2013
Second edition: March 2015
Third edition: October 2016
Production reference: 1141016
Published by Packt Publishing Ltd.
Livery Place
35 Livery Street
Birmingham B3 2PB, UK.
ISBN 978-1-78588-927-1
www.packtpub.com
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
Krishna Sankar is a Senior Specialist—AI Data Scientist with Volvo Cars focusing on
Autonomous Vehicles. His earlier stints include Chief Data Scientist at h t t p : / / c a d e n t t e c h
. t v /, Principal Architect/Data Scientist at Tata America Intl. Corp., Director of Data Science
at a bioinformatics startup, and as a Distinguished Engineer at Cisco. He has been speaking
at various conferences including ML tutorials at Strata SJC and London 2016, Spark Summit
[goo.gl/ab30lD], Strata-Spark Camp, OSCON, PyCon, and PyData, writes about Robots
Rules of Order [goo.gl/5yyRv6], Big Data Analytics—Best of the Worst [goo.gl/ImWCaz],
predicting NFL, Spark [ h t t p : / / g o o . g l / E 4 k q M D], Data Science [ h t t p : / / g o o . g l / 9 p y J M H],
Machine Learning [ h t t p : / / g o o . g l / S X F 5 3 n], Social Media Analysis [ h t t p : / / g o o . g l / D 9 Y p V
Q] as well as has been a guest lecturer at the Naval Postgraduate School. His occasional
blogs can be found at h t t p s : / / d o u b l e c l i x . w o r d p r e s s . c o m /. His other passion is flying
drones (working towards Drone Pilot License (FAA UAS Pilot) and Lego Robotics—you
will find him at the St.Louis FLL World Competition as Robots Design Judge.
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 Usha’s father Mr.Natarajan, whose
wisdom we all rely upon, and my late mom for her kindness.
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