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Jean-Marc Spaggiari - Getting Started with Kudu: Perform Fast Analytics on Fast Data

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Jean-Marc Spaggiari Getting Started with Kudu: Perform Fast Analytics on Fast Data
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Fast data ingestion, serving, and analytics in the Hadoop ecosystem have forced developers and architects to choose solutions using the least common denominator--either fast analytics at the cost of slow data ingestion or fast data ingestion at the cost of slow analytics. There is an answer to this problem. With the Apache Kudu column-oriented data store, you can easily perform fast analytics on fast data. This practical guide shows you how.
Begun as an internal project at Cloudera, Kudu is an open source solution compatible with many data processing frameworks in the Hadoop environment. In this book, current and former solutions professionals from Cloudera provide use cases, examples, best practices, and sample code to help you get up to speed with Kudu.
Explore Kudus high-level design, including how it spreads data across servers
Fully administer a Kudu cluster, enable security, and add or remove nodes
Learn Kudus client-side APIs, including how to integrate Apache Impala, Spark, and other frameworks for data manipulation
Examine Kudus schema design, including basic concepts and primitives necessary to make your project successful
Explore case studies for using Kudu for real-time IoT analytics, predictive modeling, and in combination with another storage engine

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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 OReilly Media, Inc. , 1005 Gravenstein Highway North, Sebastopol, CA 95472.

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  • 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 OReilly logo is a registered trademark of OReilly Media, Inc. Getting Started with Kudu, the cover image, and related trade dress are trademarks of OReilly 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.

978-1-491-98025-5

[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 Kudus 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

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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.

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 youre 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 OReilly 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 products 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 (OReilly). 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 .

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