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This guide walks you through the process of building an application with GemFire’s data fabric.
You will use the powerful Spring Data GemFire library to store and retrieve POJOs.
build.gradle
link:initial/build.gradle[role=include]If you have Spring Tool Suite, then you can simply import this guide directly.
GemFire is a data fabric. It maps data into regions, and it’s possible to configure distributed regions across multiple nodes. However, for this guide you use a local region so you don’t have to set up anything extra.
In this example, you store Person objects with a few annotations.
src/main/java/hello/Person.java
link:complete/src/main/java/hello/Person.java[role=include]Here you have a Person class with two attributes, the name and the age. You also have a single constructor to populate the entities when creating a new instance.
Notice that this class is annotated @Region("hello"). When GemFire stores the class, a new entry is created inside that specific region. This class also has name marked with @Id. This is for internal usage to help GemFire track the data.
The next important piece is the person’s age. Later in this guide, you will use it to fashion some queries.
The convenient toString() method will print out the person’s name and age.
Spring Data GemFire focuses on storing data in GemFire. It also inherits powerful functionality from the Spring Data Commons project, such as the ability to derive queries. Essentially, you don’t have to learn the query language of GemFire; you can simply write a handful of methods and the queries are written for you.
To see how this works, create an interface that queries Person nodes.
src/main/java/hello/PersonRepository.java
link:complete/src/main/java/hello/PersonRepository.java[role=include]PersonRepository extends the CrudRepository interface and plugs in the type of values and keys it works with: Person and String. Out-of-the-box, this interface comes with many operations, including standard CRUD (create-read-update-delete).
You can define other queries as needed by simply declaring their method signature. In this case, you add findByName, which essentially seeks nodes of type Person and find the one that matches on name.
You also have:
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findByAgeGreaterThanto find people above a certain age -
findByAgeLessThanto find people below a certain age -
findByAgeGreaterThanAndAgeLessThanto find people in a certain range
Let’s wire this up and see what it looks like!
Here you create an Application class with all the components.
src/main/java/hello/Application.java
link:complete/src/main/java/hello/Application.java[role=include]In the configuration, you need to add the @EnableGemFireRepositories annotation.
A GemFire cache is required, to store all data. For that, you have Spring Data GemFire’s convenient CacheFactoryBean.
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Note
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In this guide, the cache is created locally using built-in components and an evaluation license. For a production solution, Spring recommends the production version of GemFire, where you can create distributed caches and regions across multiple nodes. |
Remember how you tagged Person to be stored in @Region("hello")? You define that region here with LocalRegionFactoryBean<String, Person>. You need to inject an instance of the cache you just defined while also naming it hello.
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Note
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The types are <String, Person>, matching the key type (String) with the value type (Person).
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The public static void main uses Spring Boot’s SpringApplication.run() to launch the application and invoke the CommandLineRunner that builds the relationships.
The application autowires an instance of PersonRepository that you just defined. Spring Data GemFire will dynamically create a concrete class that implements that interface and will plug in the needed query code to meet the interface’s obligations. This repository instance is the used by the run() method to demonstrate the functionality.
In this guide, you are creating three local Person s, Alice, Baby Bob, and Teen Carol. Initially, they only exist in memory. After creating them, you have to save them to GemFire.
Now you run several queries. The first looks up everyone by name. Then you execute a handful of queries to find adults, babies, and teens, all using the age attribute. With the logging turned up, you can see the queries Spring Data GemFire writes on your behalf.
You should see something like this (with other stuff like queries as well):
Before linking up with GemFire... Alice is 40 years old. Baby Bob is 1 years old. Teen Carol is 13 years old. Lookup each person by name... Alice is 40 years old. Baby Bob is 1 years old. Teen Carol is 13 years old. Adults (over 18): Alice is 40 years old. Babies (less than 5): Baby Bob is 1 years old. Teens (between 12 and 20): Teen Carol is 13 years old.
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