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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
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
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 approachThis 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.
- Sales Rank: #1148379 in eBooks
- Published on: 2015-11-04
- Released on: 2015-11-04
- Format: Kindle eBook
About the Author
Rajanarayanan Thottuvaikkatumana
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.
Most helpful customer reviews
0 of 0 people found the following review helpful.
A superb introduction to Cassandra for anyone approaching the subject from a traditional RDBMS background
By Frank
[Disclosure: I am the Technical Reviewer of this book]
Cassandra Design Patterns is a superb introduction to Cassandra, for anyone approaching the subject from a traditional RDBMS background. All the important fundamental concepts are explained clearly and concisely, and in RDBMS terms.
The book provides historical context surrounding the application design, which helps the reader to grasp the reasons behind Cassandra design decisions. I think this results in a more complete understanding of the subject for the reader. The author does this without getting bogged down or including irrelevant details.
Particular attention is paid throughout the book to use cases where the application is deployed as a replacement for, or in operation with, existing non-distributed storage systems. The author methodically works over a number of categories of real-world uses, and works out each example completely. The task of applying these examples is discussed in each case.
My favourite aspect of the book is the approach to the use cases: the author begins by discussing the relevant practical application, and then carefully deconstructs it down into a Cassandra setup. He makes sure to mention any obscure 'gotchas' or tweaks to the setup that may be necessary in certain circumstances.
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