Caching Data with Pivotal GemFire

This guide walks through the process of using the Apache Geode's data management system to cache certain calls from your application code.

For more general knowledge of Apache Geode concepts and accessing data from Apache Geode, read through the guide, Accessing Data with Apache Geode.

What you’ll build

You’ll build a service that requests quotes from a CloudFoundry hosted Quote service and caches them in Apache Geode.

Then, you’ll see that fetching the same quote again eliminates the expensive call to the Quote service since Spring’s Cache Abstraction, backed by Apache Geode, will be used to cache the results, given the same request.

The Quote service is located at…​

The Quote service has the following API…​

GET /api         - get all quotes
GET /api/random  - get random quote
GET /api/{id}    - get specific quote

What you’ll need

How to complete this guide

Like most Spring Getting Started guides, you can start from scratch and complete each step or you can bypass basic setup steps that are already familiar to you. Either way, you end up with working code.

To start from scratch, move on to Starting with Spring Initializr.

To skip the basics, do the following:

When you finish, you can check your results against the code in gs-caching-gemfire/complete.

Starting with Spring Initializr

For all Spring applications, you should start with the Spring Initializr. Spring Initializr offers a fast way to pull in all the dependencies you need for an application and does a lot of the set up for you. This example needs "Spring for Apache Geode" dependency.

The following listing shows an example pom.xml file when using Maven:

<?xml version="1.0" encoding="UTF-8"?>
<project xmlns=""








The following listing shows an example build.gradle file when using Gradle:

plugins {
    id 'org.springframework.boot' version '2.7.0'
    id 'io.spring.dependency-management' version '1.0.11.RELEASE'
    id 'io.freefair.lombok' version '6.3.0'
    id 'java'

apply plugin: 'eclipse'
apply plugin: 'idea'

group = "org.springframework"
version = "0.1.0"
sourceCompatibility = '1.8'

repositories {

dependencies {
    implementation "org.springframework.boot:spring-boot-starter"
    implementation ""
    implementation "com.fasterxml.jackson.core:jackson-databind"
    implementation "org.projectlombok:lombok"
    runtimeOnly "javax.cache:cache-api"
    runtimeOnly ""

Create a bindable object for fetching data

Now that you’ve set up the project and build system, you can focus on defining the domain objects necessary to capture the bits you need to pull quotes (the data) from the Quote service.


package hello;

import com.fasterxml.jackson.annotation.JsonIgnoreProperties;

import org.springframework.util.ObjectUtils;

import lombok.Data;

@JsonIgnoreProperties(ignoreUnknown = true)
public class Quote {

  private Long id;

  private String quote;

  public boolean equals(Object obj) {

    if (this == obj) {
      return true;

    if (!(obj instanceof Quote)) {
      return false;

    Quote that = (Quote) obj;

    return ObjectUtils.nullSafeEquals(this.getId(), that.getId());

  public int hashCode() {

    int hashValue = 17;

    hashValue = 37 * hashValue + ObjectUtils.nullSafeHashCode(getId());

    return hashValue;

  public String toString() {
    return getQuote();

The Quote domain class has id and quote properties. These are the two primary attributes you will gather further along in this guide. The implementation of the Quote class has been simplified by the use of Project Lombok.

In addition to Quote, the QuoteResponse captures the entire payload of the response sent by the Quote service sent in the quote request. It includes the status (a.k.a. type) of the request along with the quote. This class also uses Project Lombok to simplify the implementation.


package hello;

import com.fasterxml.jackson.annotation.JsonIgnoreProperties;
import com.fasterxml.jackson.annotation.JsonProperty;

import lombok.Data;

@JsonIgnoreProperties(ignoreUnknown = true)
public class QuoteResponse {

  private Quote quote;

  private String status;

  public String toString() {
    return String.format("{ @type = %1$s, quote = '%2$s', status = %3$s }",
      getClass().getName(), getQuote(), getStatus());

A typical response from the Quote service appears as follows:

  "value": {
    "quote":"Working with Spring Boot is like pair-programming with the Spring developers."

Both classes are marked with @JsonIgnoreProperties(ignoreUnknown=true). This means even though other JSON attributes may be retrieved, they’ll be ignored.

Query Quote service for data

Your next step is to create a service class that queries for quotes.


package hello;

import java.util.Collections;
import java.util.Map;
import java.util.Optional;

import org.springframework.cache.annotation.CachePut;
import org.springframework.cache.annotation.Cacheable;
import org.springframework.stereotype.Service;
import org.springframework.web.client.RestTemplate;

public class QuoteService {

  protected static final String ID_BASED_QUOTE_SERVICE_URL = "{id}";
  protected static final String RANDOM_QUOTE_SERVICE_URL = "";

  private volatile boolean cacheMiss = false;

  private final RestTemplate quoteServiceTemplate = new RestTemplate();

   * Determines whether the previous service method invocation resulted in a cache miss.
   * @return a boolean value indicating whether the previous service method invocation resulted in a cache miss.
  public boolean isCacheMiss() {
    boolean cacheMiss = this.cacheMiss;
    this.cacheMiss = false;
    return cacheMiss;

  protected void setCacheMiss() {
    this.cacheMiss = true;

   * Requests a quote with the given identifier.
   * @param id the identifier of the {@link Quote} to request.
   * @return a {@link Quote} with the given ID.
  public Quote requestQuote(Long id) {
    return requestQuote(ID_BASED_QUOTE_SERVICE_URL, Collections.singletonMap("id", id));

   * Requests a random quote.
   * @return a random {@link Quote}.
  @CachePut(cacheNames = "Quotes", key = "")
  public Quote requestRandomQuote() {
    return requestQuote(RANDOM_QUOTE_SERVICE_URL);

  protected Quote requestQuote(String URL) {
    return requestQuote(URL, Collections.emptyMap());

  protected Quote requestQuote(String URL, Map<String, Object> urlVariables) {

    return Optional.ofNullable(this.quoteServiceTemplate.getForObject(URL, QuoteResponse.class, urlVariables))

The QuoteService uses Spring’s RestTemplate to query the Quote service’s API. The Quote service returns a JSON object, but Spring uses Jackson to bind the data to a QuoteResponse and ultimately, a Quote object.

The key piece of this service class is how requestQuote has been annotated with @Cacheable("Quotes"). Spring’s Caching Abstraction intercepts the call to requestQuote to check whether the service method has already been called. If so, Spring’s Caching Abstraction just returns the cached copy. Otherwise, Spring proceeds to invoke the method, store the response in the cache, and then return the results to the caller.

We also used the @CachePut annotation on the requestRandomQuote service method. Since the quote returned from this service method invocation will be random, we don’t know which quote we will receive. Therefore, we cannot consult the cache (i.e. Quotes) prior to the call, but we can cache the result of the call, which will have a positive affect on subsequent requestQuote(id) calls, assuming the quote of interest was randomly selected and cached previously.

The @CachePut uses a SpEL expression (“”) to access the result of the service method invocation and retrieve the ID of the Quote to use as the cache key. You can learn more about Spring’s Cache Abstraction SpEL context here.

You must supply the name of the cache. We named it "Quotes" for demonstration purposes, but in production, it is recommended to pick an appropriately descriptive name. This also means different methods can be associated with different caches. This is useful if you have different configuration settings for each cache, such as different expiration or eviction policies, etc.

Later on when you run the code, you will see the time it takes to run each call and be able to discern the impact that caching has on service response times. This demonstrates the value of caching certain calls. If your application is constantly looking up the same data, caching the results can improve your performance dramatically.

Make the application executable

Although Apache Geode caching can be embedded in web apps and WAR files, the simpler approach demonstrated below creates a standalone application. You package everything in a single, executable JAR file, driven by a good old Java main() method.


package hello;

import java.util.Optional;

import org.apache.geode.cache.client.ClientRegionShortcut;

import org.springframework.boot.ApplicationRunner;
import org.springframework.boot.SpringApplication;
import org.springframework.boot.autoconfigure.SpringBootApplication;
import org.springframework.context.annotation.Bean;

@ClientCacheApplication(name = "CachingGemFireApplication")
@EnableCachingDefinedRegions(clientRegionShortcut = ClientRegionShortcut.LOCAL)
public class Application {

  public static void main(String[] args) {, args);

  ApplicationRunner runner(QuoteService quoteService) {

    return args -> {
      Quote quote = requestQuote(quoteService, 12L);
      requestQuote(quoteService, quote.getId());
      requestQuote(quoteService, 10L);

  private Quote requestQuote(QuoteService quoteService, Long id) {

    long startTime = System.currentTimeMillis();

    Quote quote = Optional.ofNullable(id)

    long elapsedTime = System.currentTimeMillis();

    System.out.printf("\"%1$s\"%nCache Miss [%2$s] - Elapsed Time [%3$s ms]%n", quote,
      quoteService.isCacheMiss(), (elapsedTime - startTime));

    return quote;

@SpringBootApplication is a convenience annotation that adds all of the following:

  • @Configuration: Tags the class as a source of bean definitions for the application context.

  • @EnableAutoConfiguration: Tells Spring Boot to start adding beans based on classpath settings, other beans, and various property settings. For example, if spring-webmvc is on the classpath, this annotation flags the application as a web application and activates key behaviors, such as setting up a DispatcherServlet.

  • @ComponentScan: Tells Spring to look for other components, configurations, and services in the hello package, letting it find the controllers.

The main() method uses Spring Boot’s method to launch an application. Did you notice that there was not a single line of XML? There is no web.xml file, either. This web application is 100% pure Java and you did not have to deal with configuring any plumbing or infrastructure.

At the top of the configuration is a single, vital annotation: @EnableGemfireCaching. This turns on caching (i.e. is meta-annotated with Spring’s @EnableCaching annotation) and declares additional, important beans in the background to support caching using Apache Geode as the caching provider.

The first bean is an instance of QuoteService used to access the Quotes REST-ful Web service.

The other two are needed to cache Quotes and perform the actions of the application.

  • quotesRegion defines a Apache Geode LOCAL client Region inside the cache to store quotes. It is specifically named "Quotes" to match the usage of @Cacheable("Quotes") on our QuoteService method.

  • runner is an instance of the Spring Boot ApplicationRunner interface used to run our application.

The first time a quote is requested (using requestQuote(id)), a cache miss occurs and the service method will be invoked, incurring a noticeable delay that is no where close to zero ms. In this case, caching is linked by the input parameters (i.e. id) of the service method, requestQuote. In other words, the id method parameter is the cache key. Subsequent requests for the same quote identified by ID, will result in a cache hit, thereby avoiding the expensive service call.

For demonstration purposes, the call to the QuoteService is wrapped in a separate method (requestQuote inside the Application class) to capture the time to make the service call. This lets you see exactly how long any one request is taking.

Build an executable JAR

You can run the application from the command line with Gradle or Maven. You can also build a single executable JAR file that contains all the necessary dependencies, classes, and resources and run that. Building an executable jar makes it easy to ship, version, and deploy the service as an application throughout the development lifecycle, across different environments, and so forth.

If you use Gradle, you can run the application by using ./gradlew bootRun. Alternatively, you can build the JAR file by using ./gradlew build and then run the JAR file, as follows:

java -jar build/libs/gs-caching-gemfire-0.1.0.jar

If you use Maven, you can run the application by using ./mvnw spring-boot:run. Alternatively, you can build the JAR file with ./mvnw clean package and then run the JAR file, as follows:

java -jar target/gs-caching-gemfire-0.1.0.jar
The steps described here create a runnable JAR. You can also build a classic WAR file.

Logging output is displayed. The service should be up and running within a few seconds.

"@springboot with @springframework is pure productivity! Who said in #java one has to write double the code than in other langs? #newFavLib"
Cache Miss [true] - Elapsed Time [776 ms]
"@springboot with @springframework is pure productivity! Who said in #java one has to write double the code than in other langs? #newFavLib"
Cache Miss [false] - Elapsed Time [0 ms]
"Really loving Spring Boot, makes stand alone Spring apps easy."
Cache Miss [true] - Elapsed Time [96 ms]

From this you can see that the first call to the Quote service for a quote took 776 ms and resulted in a cache miss. However, the second call requesting the same quote took 0 ms and resulted in a cache hit. This clearly shows that the second call was cached and never actually hit the Quote service. However, when a final service call for a specific, non-cached quote request is made, it took 96 ms and resulted in a cache miss since this new quote was not previously in the cache before the call.


Congratulations! You’ve just built a service that performed an expensive operation and tagged it so that it will cache results.

See Also

The following guides may also be helpful:

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