How to Optimize API calls with spring batch

by | Oct 4, 2024 | Backend Development

spring batch

API Calls with Spring Batch

Introduction

Spring Batch is a framework designed for batch processing in Java applications. It provides reusable functions for handling large volumes of data efficiently. Whether processing large datasets, automating repetitive tasks, or managing jobs with complex workflows,it is built to handle high-performance scenarios. Its integration with the Spring Framework offers advanced features like chunk-based processing, transaction management, and parallel execution, making it ideal for scalable batch processing.

Why Choose Spring Batch for High-Volume API Calls?

In modern applications, managing large volumes of API requests can be a daunting task. When dealing with tens of thousands of API calls, inefficient handling can lead to serious issues like performance bottlenecks, memory overflows, or even application crashes. Spring Batch, a powerful framework designed for batch processing, provides an efficient solution to address these challenges.

Handling Large API Volumes Efficiently

It offers a robust framework to process high volumes of API calls in a controlled, scalable manner. It provides features like chunk-based processing, multi-threading, and retry mechanisms. Therefore, it becomes an ideal choice for making asynchronous API calls, especially when handling large datasets. In particular, Spring Batch helps:

Scalability and Resource Management

It ensures that API requests are handled in a scalable way. This prevents the application from being overloaded, even when handling high volumes. For example, if you need to make over 100,000 API calls, it helps distribute the workload evenly, avoiding resource exhaustion. Additionally, by controlling the number of calls made in parallel, the system remains responsive even under heavy loads.

It provides a structured way to process large datasets effectively. Its key features like chunk-based processing, multi-threading, and retry mechanisms make it ideal for high-volume, asynchronous API calls. With it, you can:

  • Scale API Requests: By processing large numbers of API calls without exhausting system resources, the framework ensures efficient resource management.
  • Handle Failures Gracefully: Built-in retry mechanisms allow the system to recover from transient errors without crashing.
  • Optimize Performance: Chunk-based processing and multi-threading allow parallel execution, improving the overall performance.

Dependency

To implement Spring Batch in your project, confirm that you had included this dependency in your build.gradle or pom.xml file

implementation 'org.springframework.boot:spring-boot-starter-batch'

@Configuration
public class BatchConfig {
      @Bean
    public ItemReader reader() {
        return new ItemReader<>() {
            private int counter = 0;
            @Override
            public RandomNumberEntity read() throws Exception {
                if (counter < 100000) {
                    counter++;
                    RandomNumberResponse response = adviceApiService.fetchRandomNumber();
                    RandomNumberEntity entity = new RandomNumberEntity();
                    entity.setNumber(response.getNumber());
                    entity.setMessage(response.getMessage());
                    return entity;
                }
                return null;
            }
        };
    }

Explanation

In this snippet, we define an ItemReader that reads RandomNumberEntity objects. The reader calls a third-party API to fetch random numbers. The counter tracks the number of API calls made, ensuring that no more than 100,000 calls are executed. When a response is received, a new RandomNumberEntity is created with the data from the API. Once the limit is reached, the reader returns null, indicating the end of the process.

This code shows how you can call your own API. You can customize it to handle third-party APIs, with other services like job creation and step configuration remaining the same.

@RestController
@RequestMapping("/api/random")
public class RandomNumberResponseController {
    @GetMapping("/test")
    public ResponseEntity test() {
        return ResponseEntity.ok("Test endpoint is working");
    }
    @GetMapping("/with-message")
    public ResponseEntity getRandomNumberWithMessage() {
        //Add your random number generator and assign it to rNumber
        RandomNumberResponse response = new RandomNumberResponse();
        response.setNumber(rNumber );
        response.setMessage("hello");
        return ResponseEntity.ok(response);
    }
}

Explanation

This RandomNumberResponseController defines two endpoints. The /test endpoint serves as a simple health check, while /with-message generates a random number and returns a response object containing both the number and a message. The RandomNumberResponse class can be easily customized to include fields that match your specific needs.

Integrating with Your Batch Job

With the reader() method in place, other parts of the Spring Batch job—like step creation, job creation, and processors—can remain largely unchanged. This allows you to easily integrate the reader with your existing batch configuration, facilitating large-scale, asynchronous API calls.

Key Components

  • BatchConfig: Defines a batch job where each step processes 1000 API calls asynchronously using a TaskExecutor. It reads random numbers from the third-party API via AdviceApiService, processes them, and stores the results in the database.
  • AdviceApiService: Makes the API calls to fetch random numbers.
  • BatchControllers: Manages and starts the job via its endpoints.
  • RandomNumberResponseController: Generates random numbers and returns them with a text message.

 

Conclusion

Leveraging Spring Batch for high-volume API calls boosts efficiency and scalability. Its asynchronous processing, chunk-based execution, and error handling optimize performance while ensuring system resilience, making it ideal for managing large-scale API requests in modern applications.