Book Image

Spring Data

By : Petri Kainulainen
Book Image

Spring Data

By: Petri Kainulainen

Overview of this book

Spring Framework has always had a good support for different data access technologies. However, developers had to use technology-specific APIs, which often led to a situation where a lot of boilerplate code had to be written in order to implement even the simplest operations. Spring Data changed all this. Spring Data makes it easier to implement Spring-powered applications that use cloud-based storage services, NoSQL databases, map-reduce frameworks or relational databases. "Spring Data" is a practical guide that is full of step-by-step instructions and examples which ensure that you can start using the Java Persistence API and Redis in your applications without extra hassle. This book provides a brief introduction to the underlying data storage technologies, gives step-by-step instructions that will help you utilize the discussed technologies in your applications, and provides a solid foundation for expanding your knowledge beyond the concepts described in this book. You will learn an easier way to manage your entities and to create database queries with Spring Data JPA. This book also demonstrates how you can add custom functions to your repositories. You will also learn how to use the Redis key-value store as data storage and to use its other features for enhancing your applications. "Spring Data" includes all the practical instructions and examples that provide you with all the information you need to create JPA repositories with Spring Data JPA and to utilize the performance of Redis in your applications by using Spring Data Redis.
Table of Contents (13 chapters)

Designing a Redis data model

The most important rules of designing a Redis data model are: Redis does not support ad hoc queries and it does not support relations in the same way than relational databases. Thus, designing a Redis data model is a total different ballgame than designing the data model of a relational database. The basic guidelines of a Redis data model design are given as follows:

  • Instead of simply modeling the information stored in our data model, we have to also think how we want to search information from it. This often leads to a situation where we have to duplicate data in order to fulfill the requirements given to us. Don't be afraid to do this.

  • We should not concentrate on normalizing our data model. Instead, we should combine the data that we need to handle as an unit into an aggregate.

  • Since Redis does not support relations, we have to design and implement these relations by using the supported data structures. This means that we have to maintain these relations manually...