Cassandra.Data.Modeling.and.Analysis

Title: Cassandra Data Modeling and Analysis Author: C.Y. Kan Length: 171 pages Edition: 1 Language: English Publisher: Packt Publishing Publication Date: 2014-12-24 ISBN-10: 1783988886 ISBN-13: 9781783988884 Design, build, and analyze your data intricately using Cassandra 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. 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. Table of Contents Chapter 1: Bird's Eye View of Cassandra Chapter 2: Cassandra Data Modeling Chapter 3: CQL Data Types Chapter 4: Indexes Chapter 5: First-cut Design and Implementation Chapter 6: Enhancing a Version Chapter 7: Deployment and Monitoring Chapter 8: Final Thoughts 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. 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. Table of Contents Chapter 1: Bird's Eye View of Cassandra Chapter 2: Cassandra Data Modeling Chapter 3: CQL Data Types Chapter 4: Indexes Chapter 5: First-cut Design and Implementation Chapter 6: Enhancing a Version Chapter 7: Deployment and Monitoring Chapter 8: Final Thoughts