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Table of Contents
Converting a Mono Object to Another Mono Object in Spring WebFlux
Efficiently Transforming a Mono Object
Best Practices for Handling Potential Errors
Built-in Spring WebFlux Operators for Conversion
Home Java javaTutorial Convert Mono Object to Another Mono Object in Spring WebFlux

Convert Mono Object to Another Mono Object in Spring WebFlux

Mar 07, 2025 pm 06:13 PM

Converting a Mono Object to Another Mono Object in Spring WebFlux

This question addresses how to transform the data encapsulated within one Mono object into a different type of object, still within a Mono, within a Spring WebFlux application. There are several ways to achieve this, each with its own advantages and disadvantages. The core principle involves using reactive operators to map the original Mono's data to a new type.

Efficiently Transforming a Mono Object

The most efficient and idiomatic way to transform a Mono<T> to a Mono<U> in Spring WebFlux is to use the map operator. The map operator applies a function to the value emitted by the Mono, transforming it into a new value. This happens only if the original Mono emits a value; if it's empty (completes without emitting), the resulting Mono will also be empty.

Here's an example: Let's say you have a Mono<User> and you want to convert it to a Mono<UserDto>. Assuming you have a User and UserDto class:

class User {
    String name;
    int age;
    // ... constructors, getters, setters
}

class UserDto {
    String fullName;
    // ... constructors, getters, setters
}

// ... within your handler method ...

Mono<User> userMono = Mono.just(new User("John Doe", 30));

Mono<UserDto> userDtoMono = userMono.map(user -> {
    UserDto userDto = new UserDto();
    userDto.fullName = user.name;
    return userDto;
});

This code uses a lambda expression within the map operator to create a new UserDto from a User object. The map operation happens only when the userMono emits a value. If userMono is empty, userDtoMono will also be empty. This is highly efficient because the transformation is performed only when necessary.

Best Practices for Handling Potential Errors

During the conversion, errors can occur. For example, the mapping function might throw an exception if the input data is invalid or if a necessary resource is unavailable. Robust error handling is crucial. The best practice is to use the flatMap operator in conjunction with error handling mechanisms like onErrorResume or onErrorReturn.

Here's an example incorporating error handling:

Mono<UserDto> userDtoMono = userMono.flatMap(user -> {
    try {
        UserDto userDto = new UserDto();
        userDto.fullName = user.name; // Potential exception if user.name is null
        return Mono.just(userDto);
    } catch (Exception e) {
        return Mono.error(e); // Propagate the exception
    }
}).onErrorResume(Exception.class, e -> {
    // Log the error or return a default value
    log.error("Error during conversion: {}", e.getMessage());
    return Mono.just(new UserDto()); // Return a default UserDto
});

This code uses flatMap to handle potential exceptions within the mapping function. If an exception occurs, Mono.error(e) propagates the error downstream. The onErrorResume operator then catches this error, logs it, and returns a default UserDto to prevent the entire request from failing. Alternatively, onErrorReturn could be used to return a specific default value.

Built-in Spring WebFlux Operators for Conversion

Yes, Spring WebFlux provides several built-in operators that simplify the conversion of one Mono object to another. The most prominent is the map operator, as discussed earlier. Other operators, such as flatMap, transformDeferred, and transformMany (for converting to Flux), offer more advanced functionalities, especially for handling asynchronous operations or complex transformations. However, for simple data transformations, map is the most efficient and recommended approach. Choosing the right operator depends on the complexity of the transformation and the need for asynchronous operations or error handling. For simple data mapping, map is sufficient; for more complex scenarios involving potential exceptions or asynchronous operations within the transformation, flatMap along with error handling operators is the preferred choice.

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