Mastering Caching in Spring Boot: A Comprehensive Guide

Understanding Caching in Spring Boot

Caching, in the context of software development, involves storing frequently used data in a faster and easily accessible location. In Spring Boot, caching is a first-class citizen, and it offers seamless integration with various caching providers. The @Cacheable annotation is a fundamental building block for implementing caching strategies.

Spring Boot Cache Providers

Cache providers allow us to transparently and clearly configure the cache in the application. Use the following steps to configure any given cache provider:

1. Add the @EnableCaching annotation to the configuration file.
2. Add the required cache library to the classpath.
3. Add the cache provider configuration file to the root classpath.

The following are the cache providers supported by the Spring Boot framework :

1. JCache
2. EhCache
3. Hazelcast
4. Infinispan
5. Couchbase
6. Redis
7. Caffeine
8. Simple

Redis is a NoSQL database, so it doesn’t have any tables, rows, or columns. Also, it doesn’t allow statements like select, insert, update, or delete. Instead, Redis uses data structures to store data. As a result, it can serve frequently requested items with sub-millisecond response times and allow easy scaling for larger workloads without increasing the cost of a more expensive back-end system.

Redis can also be used with streaming solutions to consume, process, and analyze real-time data with sub-millisecond latency. Hence, we advocate implementing caching in spring boot using Redis.

What is Redis?

Remote Dictionary Server, aka Redis, an in-memory data store, is one of the many options for implementing caching in Spring Boot applications due to its speed, versatility, and simplicity of use. It is a versatile key-value store that supports several data structures, such as Strings, Sorted Sets, Hashes, Lists, Streams, Bitmaps, Sets, etc., because it is a NoSQL database and doesn’t need a predetermined schema.

Redis can be used in various ways, including:

1) In-Memory Database: In today’s data-driven world, handling vast amounts of real-time data is a common challenge for businesses. A real-time database is a type of data repository designed to acquire, analyze, and/or augment an incoming stream of data points in real time, often immediately after the data is produced. Redis may be used to build data infrastructure for real-time applications that need high throughput and low latency.

2) Cache: Many applications struggle with the need to store and retrieve data quickly, especially in systems with high latency. Due to its speed, Redis is the ideal choice for caching API calls, session states, complex computations, and database queries.

3) Message Broker (MQ): It has always been difficult to stream data around the organization and make it accessible for various system components. Redis supports messaging, event sources, alerts, and high-speed data intake using its stream data type.

How Does Redis Caching Work?

Redis Cache effectively stores the results of database retrieval operations, allowing subsequent requests to retrieve the data directly from the cache. This significantly enhances application performance by reducing unnecessary database calls.

Implementing caching in Spring Boot using Redis involves a few key steps. Here’s a basic guide on how to set up caching with Redis in a Spring Boot application:

Step 1: Add Dependencies

Add the necessary dependencies to your pom.xml or build.gradle file.

For Maven, in your pom.xml:

<dependencies>
    <!-- Other dependencies -->
    <dependency>
        <groupId>org.springframework.boot</groupId>
        <artifactId>spring-boot-starter-data-redis</artifactId>
    </dependency>
</dependencies>

For Gradle, in your build.gradle:

dependencies {
    // Other dependencies
    implementation 'org.springframework.boot:spring-boot-starter-data-redis'
}

Step 2: Configure Redis Configure

Redis connection properties in your application.properties or application.yml file:

# Redis server properties
spring.redis.host=localhost
spring.redis.port=6379

You can customize these properties based on your Redis server configuration.

Step 3: Enable Caching in Your Application

Before diving into caching, it’s crucial to enable caching support in your Spring Boot application. This is achieved by adding the @EnableCaching annotation to your main application class or a configuration class. Additionally, you need to configure the caching provider, such as Redis, in your application properties.

import org.springframework.cache.annotation.EnableCaching;
import org.springframework.boot.SpringApplication;
import org.springframework.boot.autoconfigure.SpringBootApplication;

@SpringBootApplication
@EnableCaching
public class YourApplication {
    public static void main(String[] args) {
        SpringApplication.run(YourApplication.class, args);
    }
}

Step 4: Use Cacheable Annotation

Now, you can use the @Cacheable annotation in your service methods to enable caching.

Example 1: Caching Method Results

import org.springframework.cache.annotation.Cacheable;
import org.springframework.stereotype.Service;

@Service
public class YourService {

    @Cacheable(value = "yourCacheName", key = "#param")
    public String getCachedData(String param) {
        // This method will be cached based on the provided cache name and key
        // Actual logic to fetch data goes here
        return fetchDataFromDatabase(param);
    }

    private String fetchDataFromDatabase(String param) {
        // Simulated data fetching from the database
        return "Data for " + param;
    }
}

In the example above:

• @Cacheable: Indicates that the result of invoking the method should be cached with the specified name ("yourCacheName") for a given key ("#param").
• fetchDataFromDatabase: Simulates fetching data from a database.

Now, when you invoke getCachedData multiple times with the same parameter, the method will be executed only once, and subsequent calls with the same parameter will be served from the cache.

Ensure that your Redis server is running while testing this setup. You can use the default redis-server command to start a Redis server on your machine.

Example 2: Caching Method Results

import org.springframework.cache.annotation.Cacheable;
import org.springframework.stereotype.Service;

@Service
public class ProductService {

    @Cacheable(value = "productsCache", key = "#productId")
    public Product getProductById(String productId) {
        // Simulate fetching product from a data source (e.g., database)
        return productService.fetchProductById(productId);
    }

    private Product fetchProductById(String productId) {
        // Actual logic to fetch product data from a data source
        // ...
        return new Product(productId, "Product Name", 29.99);
    }
}

In this example, the getProductById method will be cached based on the productsCache cache name and the productId key.

Example 3: Caching Entire Method Result Set

import org.springframework.cache.annotation.Cacheable;
import org.springframework.stereotype.Service;
import java.util.List;

@Service
public class CategoryService {

    @Cacheable(value = "categoriesCache")
    public List<Category> getAllCategories() {
        // Simulate fetching all categories from a data source
        return categoryService.fetchAllCategories();
    }

    private List<Category> fetchAllCategories() {
        // Actual logic to fetch all category data from a data source
        // ...
        return List.of(new Category("1", "Category 1"), new Category("2", "Category 2"));
    }
}

In this example, the getAllCategories method will be cached with the categoriesCache cache name. As a result, subsequent calls to this method will be served from the cache.

Example 4: Using Multiple Parameters for Key Generation

import org.springframework.cache.annotation.Cacheable;
import org.springframework.stereotype.Service;

@Service
public class UserService {

    @Cacheable(value = "usersCache", key = "#username.concat('-').concat(#page)")
    public User getUserByUsernameAndPage(String username, int page) {
        // Simulate fetching user data based on username and page from a data source
        return userService.fetchUserByUsernameAndPage(username, page);
    }

    private User fetchUserByUsernameAndPage(String username, int page) {
        // Actual logic to fetch user data from a data source based on username and page
        // ...
        return new User(username, page);
    }
}

Here, the getUserByUsernameAndPage method will be cached based on the combination of username and page parameters.

These examples showcase different scenarios where caching can be applied using the @Cacheable annotation. Remember to adjust cache names, key generation, and caching strategies based on your specific application requirements.

Keep in mind that this is a basic setup, and you can customize caching further based on your application's requirements. Additionally, you may want to handle cache evictions, TTL (time-to-live), and other advanced caching features based on your use case