Getting Started with Kudu

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.

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Using Code Examples

Supplemental material (code examples, exercises, etc.) is available for download at https://github.com/kudu-book/getting-started-kudu.

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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.”

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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.