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Cassandra Design Patterns - Second Edition电子书

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作       者:Rajanarayanan Thottuvaikkatumana

出  版  社:Packt Publishing

出版时间:2015-11-04

字       数:81.4万

所属分类: 进口书 > 外文原版书 > 电脑/网络

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Build real-world, industry-strength data storage solutions with time-tested design methodologies using CassandraAbout This BookExplore design patterns which co-exist with legacy data stores, migration from RDBMS, and caching technologies with CassandraLearn about design patterns and use Cassandra to provide consistency, availability, and partition tolerance guarantees for applicationsHandle 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 LearnEnable Cassandra to co-exist with RDBMS and other legacy data storesExplore various design patterns to build effective and robust storage solutionsMigrate from RDBMS-based data stores and caching solutions to CassandraUnderstand the behaviour of Cassandra when trying to balance the needs of consistency, availability, and partition toleranceDeal with time stamps related to data effectivelySee how Cassandra can be used in analytical use casesApply 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.
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Cassandra Design Patterns Second Edition

Table of Contents

Cassandra Design Patterns Second Edition

Credits

About the Author

Acknowledgements

About the Reviewers

www.PacktPub.com

Support files, eBooks, discount offers, and more

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

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