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Cassandra Data Modeling and Analysis

C.Y. Kan

Design, build, and analyze your data intricately using Cassandra
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Book Details

ISBN 139781783988884
Paperback196 pages

About This Book

  • Build professional data models in Cassandra using CQL and appropriate indexes
  • Grasp the Model-By-Query techniques through working examples
  • Step-by-step tutorial of a stock market technical analysis application

Who This Book Is For

If you are interested in Cassandra and want to develop real-world analysis applications, then this book is perfect for you. It would be helpful to have prior knowledge of NoSQL database.

Table of Contents

Chapter 1: Bird's Eye View of Cassandra
What is NoSQL?
What is Cassandra?
Cassandra's high-level architecture
Features of Cassandra
Chapter 2: Cassandra Data Modeling
What is unique to the Cassandra data model?
Modeling by query
Data modeling considerations
Cassandra Query Language
Chapter 3: CQL Data Types
Introduction to CQL
User-defined type and tuple type
Chapter 4: Indexes
Primary index
Compound primary key and composite partition key
Secondary indexes
Chapter 5: First-cut Design and Implementation
Stock Screener Application
System design
Code design and development
Test run
Chapter 6: Enhancing a Version
Evolving the data model
Enhancing the code
Implementing system changes
Chapter 7: Deployment and Monitoring
Replication strategies
Performance tuning
Chapter 8: Final Thoughts
Supplementary information
Useful websites

What You Will Learn

  • Discover the unique way of query-driven data modeling in Cassandra
  • Explore the differences between a data model of a relational database and that of Cassandra
  • Master the correct uses of the primary index, composite key, compound key, and secondary index
  • Design a high-performance Cassandra data model
  • Develop a complete, real-world technical-analysis application for the stock market
  • Grasp the techniques of evolving a data model in production
  • Determine effective performance tuning, replication, and system-monitoring strategies

In Detail

Starting with a quick introduction to Cassandra, this book flows through various aspects such as fundamental data modeling approaches, selection of data types, designing a data model, choosing suitable keys and indexes through to a real-world application, all the while applying the best practices covered in this book.

Although the application is small, you will be involved in the full development life cycle. You will go through the design considerations of coming up with a flexible and sustainable data model for a stock market technical-analysis application written in Python. As business changes continually and so does a data model, you will also learn the techniques of evolving a data model to address new business requirements. Running a web-scale Cassandra cluster requires many careful considerations such as evolving a data model, performance tuning, and system monitoring. This book is an invaluable tutorial for anyone who wants to adopt Cassandra.


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