Franklin

Cassandra design patterns : build industry-strength data storage solutions with time-tested design methodologies using Cassandra / Rajanarayanan Thottuvaikkatumana.

Author/Creator:
Thottuvaikkatumana, Rajanarayanan, author.
Edition:
Second edition.
Publication:
Birmingham : Packt Publishing, 2015.
Series:
Community experience distilled.
Community experience distilled
Format/Description:
Book
1 online resource (169 p.)
Subjects:
Apache Cassandra.
Apache (Computer file : Apache Group)
Software patterns.
Database management.
Architecture -- Data processing.
Database management -- Computer programs.
Form/Genre:
Electronic books.
Language:
English
System Details:
text file
Summary:
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...
Contents:
Cover; Copyright; Credits; About the Author; Acknowledgements; About the Reviewers; www.PacktPub.com; Table of Contents; Preface; Chapter 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; Chapter 2: RDBMS Migration Patterns; A brief overview; List pattern; Motivations/solutions; Best practices; Example; Set pattern; Motivations/solutions; Best practices
ExampleMap pattern; Motivations/solutions; Best Practices; Example; Distributed Counter pattern; Motivations/solutions; Best practices; Example; Purge pattern; Motivations/solutions; Best Practices; Example; References; Summary; Chapter 3: Cache Migration Pattern; A brief overview; Cache to NoSQL pattern; Motivations/solutions; Best practices; Example; References; Summary; Chapter 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/solutionsBest practices; Example; References; Summary; Chapter 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; Chapter 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
ReferencesSummary; Chapter 7: Designing Applications; A brief overview; Application design and use cases; Service management and use cases; References; Summary; Index
Notes:
Includes index.
Description based on online resource; title from PDF title page (ebrary, viewed January 4, 2016).
ISBN:
1-78398-848-7
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