Cassandra Design Patterns - Second Edition

Rajanarayanan Thottuvaikkatumana

• Publisher: Packt Publishing
• Year: 2015
• ISBN:
  9781785285707
• Edition: 2
• Topic: Computer Science
• Subtopic: Databases
• Index: Computer Science

Build real-world, industry-strength data storage solutions with time-tested design methodologies using Cassandra

About This Book

• Explore design patterns which co-exist with legacy data stores, migration from RDBMS, and caching technologies with Cassandra
• Learn about design patterns and use Cassandra to provide consistency, availability, and partition tolerance guarantees for applications
• Handle temporal data for analytical purposes

Who This Book Is For

This book is intended for big data developers who are familiar with the basics of Cassandra and wish to understand and utilize Cassandra design patterns to develop real-world big data solutions. Prior knowledge of RDBMS solutions is assumed.

What You Will Learn

• Enable Cassandra to co-exist with RDBMS and other legacy data stores
• Explore various design patterns to build effective and robust storage solutions
• Migrate from RDBMS-based data stores and caching solutions to Cassandra
• Understand the behaviour of Cassandra when trying to balance the needs of consistency, availability, and partition tolerance
• Deal with time stamps related to data effectively
• See how Cassandra can be used in analytical use cases
• Apply the design patterns covered in this book in real-world use cases

In Detail

There are many NoSQL data stores used by big data applications. Cassandra is one of the most widely used NoSQL data stores that is frequently used by a huge number of heavy duty Internet-scale applications. Unlike the RDBMS world, the NoSQL landscape is very diverse and there is no one way to model data stores. This mandates the need to have good solutions to commonly seen data store design problems. Cassandra addresses such common problems simply.

If you are new to Cassandra but well-versed in RDBMS modeling and design, then it is natural to model data in the same way in Cassandra, resulting in poorly performing applications and losing the real purpose of Cassandra. If you want to learn to make the most of Cassandra, this book is for you.

This book starts with strategies to integrate Cassandra with other legacy data stores and progresses to the ways in which a migration from RDBMS to Cassandra can be accomplished. The journey continues with ideas to migrate data from cache solutions to Cassandra. With this, the stage is set and the book moves on to some of the most commonly seen problems in applications when dealing with consistency, availability, and partition tolerance guarantees.

Cassandra is exceptionally good at dealing with temporal data and patterns such as the time-series pattern and log pattern, which are covered next. Many NoSQL data stores fail miserably when a huge amount of data is read for analytical purposes, but Cassandra is different in this regard. Keeping analytical needs in mind, you'll walk through different and interesting design patterns.

No theoretical discussions are complete without a good set of use cases to which the knowledge gained can be applied, so the book concludes with a set of use cases you can apply the patterns you've learned.

Style and approach

This book is written in very simple language and an engaging style complete with examples in every chapter and real-world use cases at the end of the book.

Cassandra Design Patterns Second Edition

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Table of Contents

Cassandra Design Patterns Second Edition

Credits

About the Author

Acknowledgements

About the Reviewers

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Why subscribe?

Free access for Packt account holders

Preface

What this book covers

What you need for this book

Who this book is for

Conventions

Reader feedback

Customer support

Downloading the example code

Errata

Piracy

Questions

1. Co-existence Patterns

A brief overview of Cassandra

Denormalization pattern

Motivations/solutions

Best practices

Example

Reporting pattern

Motivations/solutions

Best practices

Example

Aggregation pattern

Motivations/solutions

Best practices

Example

References

Summary

2. RDBMS Migration Patterns

A brief overview

List pattern

Motivations/solutions

Best practices

Example

Set pattern

Motivations/solutions

Best practices

Example

Map pattern

Motivations/solutions

Best practices

Example

Distributed Counter pattern

Motivations/solutions

Best practices

Example

Purge pattern

Motivations/solutions

Best practices

Example

References

Summary

3. Cache Migration Patterns

A brief overview

Cache to NoSQL pattern

Motivations/solutions

Best practices

Example

References

Summary

4. CAP Patterns

A brief overview

Write-heavy pattern

Motivations/solutions

Best practices

Example

Read-heavy pattern

Motivations/solutions

Best practices

Example

Read-write balanced pattern

Motivations/solutions

Best practices

Example

References

Summary

5. Temporal Patterns

A brief overview

Time series pattern

Motivations/solutions

Best practices

Example

Log pattern

Motivations/solutions

Best practices

Example

Conversation pattern

Motivations/solutions

Best practices

Example

References

Summary

6. Analytics Patterns

Processing big data

Apache Hadoop

Apache Spark

Transforming data

A brief overview

Map/Reduce pattern

Motivations/solutions

Best practices

Example

Transformation pattern

Motivations/solutions

Best practices

Example

References

Summary

7. Designing Applications

A brief overview

Application design and use cases

Service management and use cases

References

Summary

Index

Cassandra Design Patterns Second Edition

Copyright © 2015 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 author, 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: January 2014

Second edition: October 2015

Production reference: 1261015

Published by Packt Publishing Ltd.

Livery Place

35 Livery Street

Birmingham B3 2PB, UK.

ISBN 978-1-78528-570-7

www.packtpub.com

This book is an update to Cassandra Design Patterns by Sanjay Sharma.

Credits

Author

Rajanarayanan Thottuvaikkatumana

Reviewers

William Berg

Mark Kerzner

Alex Shvid

Commissioning Editor

Priya Singh

Acquisition Editor

Tushar Gupta

Content Development Editor

Samantha Gonsalves

Technical Editor

Anushree Arun Tendulkar

Copy Editor

Vatsal Surti

Project Coordinator

Kinjal Bari

Proofreader

Safis Editing

Indexer

Tejal Daruwale Soni

Production Coordinator

Aparna Bhagat

Cover Work

Aparna Bhagat

About the Author

Rajanarayanan Thottuvaikkatumana, "Raj", is a seasoned technologist with more than 23 years of software development experience at various multinational companies. He has lived and worked in India, Singapore, and the USA, and is presently based out of the UK. His experience includes architecting, designing, and developing software applications. He has worked on various technologies including major databases, application development platforms, web technologies, and big data technologies. Since 2000 onwards, he has been working mainly in Java-based technologies, and has been doing heavy-duty server-side programming in Java and Scala. He has worked on very highly concurrent, highly distributed, and high-transaction-volume systems with NoSQL data stores such as Cassandra and Riak and caching technologies such as Redis, Ehcache, and Chronicle Map. Raj has a lot of experience in integrating Cassandra with Spark and has shared the Scala code repository on GitHub.

Raj holds one master's degree in Mathematics and one master's degree in Computer Information Systems, and has many certifications in ITIL and Cloud Computing to his credit.

Apart from all this, Raj is a prolific corporate trainer on various technical subjects and has contributed to the Apache Cassandra project.

When not working with computers, Raj watches a lot of tennis and he is an avid listener of classical music.

Even though Raj has worked on many white papers and training materials, this is his first publication in the form of a book.

Acknowledgements

I would like to thank my father for showing me that there is no age barrier for embarking upon something totally new. I would like to thank my mother for showing me that relentless work will be fruitful one day. I would like to thank my wife for showing me that working towards perfection culminates in something beyond comparison. I would like to thank my teachers who have helped me to see learning as a continuous process. I would like to thank my geeky friends who collectively have solutions for almost any technical problem. Last but not the least, I would like to thank my present employer for gracefully giving me official permission to work on this project.

About the Reviewers

William Berg has been engineering software for the last several years, and has worked with Cassandra all that time. He works mainly with Java. He has also reviewed Cassandra Design Patterns, another Packt Publishing title. He also plays the bass guitar and produces electronic music.

Mark Kerzner holds degrees in law, math, and computer science. He is a software architect and has been working with Big Data for the last 7 years. He is a cofounder of Elephant Scale, a Big Data training and implementation company, and is the author of FreeEed, an open-source platform for eDiscovery based on Apache Hadoop. He has many authored books and patents to his credit. He loves learning languages, and is currently perfecting his Hebrew and Chinese.

I would like to acknowledge the help of my colleagues, in particular Sujee Maniyam and, last but not least, of my multitalented family.

Alex Shvid is a Data Grid architect with more than 10 years of software experience in Fortune 500 companies with the focus on financial institutions. He has worked in the USA, Argentina, and Russia and has many architect and developer certifications, including those from Pivotal/Spring Source and Oracle. He is a regular speaker at user groups and conferences around the world such as the Java One and Cassandra meet ups. Alex works for PayPal in Silicon Valley, developing low-latency big data real-time solutions. His major specialization is in big data and fast data framework adoption for enterprise environments. He has participated in an open-source project Spring Data Cassandra module and developed a Dell Crowbar automation barclamp for Cassandra. Among his recent projects in Fast data are: integration of Gemfire from Pivotal as an event processing middleware solution and caching system for Gire (Buenos Aires, Argentina), Visa (Foster City, CA, USA), VMWare (Palo Alto, CA, USA) as well as the Coherence from Oracle for Analog (Boston, MA, USA), RCI (Parsippany, NJ, USA), and a custom data grid solution for Deutsche Bank (New York, NY, USA). When he is not working, Alex can usually be found hiking with his wife along the Coastal Trail in the San Francisco Bay Area

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• Cassandra Design Patterns Second Edition