Getting Started with Kudu Perform Fast Analytics on Fast Data Jean-Marc Spaggiari, Mladen Kovacevic, Brock Noland, and Ryan Bosshart Getting Started with Kudu by Jean-Marc Spaggiari, Mladen Kovacevic, Brock Noland, and Ryan Bosshart Copyright ©2018 Jean-Marc Spaggiari, Mladen Kovacevic, Brock Noland, Ryan Bosshart. All rights reserved. Printed in the United States of America. Published by O’Reilly Media, Inc., 1005 Gravenstein Highway North, Sebastopol, CA 95472. O’Reilly books may be purchased for educational, business, or sales promotional use. Online editions are also available for most titles (http://oreilly.com/safari). For more information, contact our corporate/institutional sales department: 800- 998-9938 or [email protected]. Editor: Nicole Tache Production Editor: Colleen Cole Copyeditor: Dwight Ramsey Proofreaders: Charles Roumeliotis and Octal Publishing, Inc. Indexer: Judy McConville Interior Designer: David Futato Cover Designer: Randy Comer Illustrator: Melanie Yarbrough Technical Reviewers: David Yahalom, Andy Stadtler, Attila Bukor, and Peter Paton July 2018: First Edition Revision History for the First Edition 2018-07-09: First Release See http://oreilly.com/catalog/errata.csp?isbn=9781491980255 for release details. The O’Reilly logo is a registered trademark of O’Reilly Media, Inc. Getting Started with Kudu, the cover image, and related trade dress are trademarks of O’Reilly Media, Inc. While the publisher and the authors have used good faith efforts to ensure that the information and instructions contained in this work are accurate, the publisher and the authors disclaim all responsibility for errors or omissions, including without limitation responsibility for damages resulting from the use of or reliance on this work. Use of the information and instructions contained in this work is at your own risk. If any code samples or other technology this work contains or describes is subject to open source licenses or the intellectual property rights of others, it is your responsibility to ensure that your use thereof complies with such licenses and/or rights. 978-1-49198025-5 [LSI] Dedication To all those data people who day-in and day-out lead hair-pulling, brain-teasing, late-night lives architecting, developing, or consulting on software that appears to have gone rogue and deliberately misbehaves. To our families, who may not even care about technology, yet still allowed us to give up time and energy to dedicate to this project with an enormous amount of patience and support, without which none of this was possible. We love you! Preface Choosing a storage engine is one of the most important decisions anyone embarking on a big data project makes and is one of the most expensive to change. Apache Kudu is an entirely new storage manager for the Hadoop ecosystem. Its flexibility makes applications faster to build and easier to maintain. As a Hadoop developer, Kudu is a critical skill in your big data toolbox. It addresses common problems in big data that are difficult or impossible to implement on current generation Hadoop storage technologies. In this book, you will learn key concepts of Kudu’s design and how to architect applications against it, resulting in Kudu applications that are fast, scalable, and reliable. Through hands-on examples, you will learn how Kudu integrates with other Hadoop ecosystem components like Apache Spark, SparkSQL, and Impala. This book assumes some limited experience with Hadoop ecosystem components like HDFS, Hive, Spark, or Impala. Basic programming experience using Java and/or Scala, experience with SQL and traditional RDBMS systems, and familiarity with the Linux shell is also assumed. Conventions Used in This Book The following typographical conventions are used in this book: Italic Indicates new terms, URLs, email addresses, filenames, and file extensions. Constant width Used for program listings, as well as within paragraphs to refer to program elements such as variable or function names, databases, data types, environment variables, statements, and keywords. Constant width bold Shows commands or other text that should be typed literally by the user. Shows commands or other text that should be typed literally by the user. Constant width italic Shows text that should be replaced with user-supplied values or by values determined by context. TIP This element signifies a tip or suggestion. NOTE This element signifies a general note. WARNING This element indicates a warning or caution. Using Code Examples Supplemental material (code examples, exercises, etc.) is available for download at https://github.com/kudu-book/getting-started-kudu. This book is here to help you get your job done. In general, if example code is offered with this book, you may use it in your programs and documentation. You do not need to contact us for permission unless you’re reproducing a significant portion of the code. For example, writing a program that uses several chunks of code from this book does not require permission. Selling or distributing a CD- ROM of examples from O’Reilly books does require permission. Answering a question by citing this book and quoting example code does not require permission. Incorporating a significant amount of example code from this book into your product’s documentation does require permission. We appreciate, but do not require, attribution. An attribution usually includes the title, author, publisher, and ISBN. For example: “Getting Started with Kudu by Jean-Marc Spaggiari, Mladen Kovacevic, Brock Noland, Ryan Bosshart (O’Reilly). Copyright 2018 Jean-Marc Spaggiari, Mladen Kovacevic, Brock Noland, Ryan Bosshart, 978-1-491-98025-5.” If you feel your use of code examples falls outside fair use or the permission given above, feel free to contact us at [email protected]. O’Reilly Safari Safari (formerly Safari Books Online) is a membership-based training and reference platform for enterprise, government, educators, and individuals. Members have access to thousands of books, training videos, Learning Paths, interactive tutorials, and curated playlists from over 250 publishers, including O’Reilly Media, Harvard Business Review, Prentice Hall Professional, Addison- Wesley Professional, Microsoft Press, Sams, Que, Peachpit Press, Adobe, Focal Press, Cisco Press, John Wiley & Sons, Syngress, Morgan Kaufmann, IBM Redbooks, Packt, Adobe Press, FT Press, Apress, Manning, New Riders, McGraw-Hill, Jones & Bartlett, and Course Technology, among others. For more information, please visit http://oreilly.com/safari. How to Contact Us Please address comments and questions concerning this book to the publisher: O’Reilly Media, Inc. 1005 Gravenstein Highway North Sebastopol, CA 95472 800-998-9938 (in the United States or Canada) 707-829-0515 (international or local) 707-829-0104 (fax) We have a web page for this book, where we list errata, examples, and any additional information. You can access this page at http://bit.ly/getting-started- with-kudu. To comment or ask technical questions about this book, send email to [email protected]. For more information about our books, courses, conferences, and news, see our website at http://www.oreilly.com. Find us on Facebook: http://facebook.com/oreilly Follow us on Twitter: http://twitter.com/oreillymedia Watch us on YouTube: http://www.youtube.com/oreillymedia Acknowledgments We would like to thank the people of the Apache Kudu community for their help. This includes the creators, committers, contributors, early adopters, and users of Apache Kudu. Thank you to our technical reviewers David Yahalom, Andy Stadtler, and Attila Bukor for their careful attention to detail and feedback. Thank you to the unofficial technical reviewers as well, including Nipun Parasrampuria, Mac Noland, Sandish Kumar, Tony Foerster, Mike Rasmussen, Jordan Birdsell, and Gunaranjan Sundararajan. Ryan Bosshart and Brock Noland would like to thank their colleagues at phData and Cloudera for their support and input in this book. Mladen Kovacevic would like to thank his Cloudera colleagues who include solutions architects, engineers, support, product management, and others for the enthusiasm and support. Mladen is likewise grateful to his family for their patience, support, and encouragement while writing—it could not have been done without them! Jean-Marc Spaggiari would like to thank everyone who supported him over this experience. Chapter 1. Why Kudu? Why Does Kudu Matter? As big data platforms continue to innovate and evolve, whether on-premises or in the cloud, it’s no surprise that many are feeling some fatigue at the pace of new open source big data project releases. After working with Kudu for the past year with large companies and real-world use cases, we’re more convinced than ever that Kudu matters and that it’s very much worthwhile to add yet another project to the open source big data world. Our reasoning boils down to three essential points: 1. Big data is still too difficult—as the audience and appetite for data grows, Hadoop and big data platforms are still too difficult, and much of this complexity is driven from limitations in storage. At our office, long-winded architecture discussions are now being cut short with the common refrain, “Just use Kudu and be done with it.” 2. New use cases need Kudu—the use cases Hadoop is being called upon to serve are changing—this includes an increasing focus on machine- generated data and realtime analytics. To demonstrate this complexity, we walk through some architectures for realtime analytics using existing big data storage technologies and discuss how Kudu simplifies these architectures. 3. The hardware landscape is changing—many of the fundamental assumptions about hardware upon which Hadoop was built are changing. There are fresh opportunities to create a storage manager with improved performance and workload flexibility. In this chapter we discuss the aforementioned motivations in detail. If you’re already familiar with the motivation for Kudu, you can skip to the latter part of this chapter where we discuss some of Kudu’s goals and how Kudu compares to other big data storage systems. We finish up by summarizing why the world needs another big data storage system.