Java 21 Record and Pattern Matching: Master Data-Oriented Programming[Video]

In the ever-evolving world of software development, data plays a central role. Handling and processing data efficiently is a paramount concern for developers. As one of the most widely used programming languages, Java acknowledges the significance of data-oriented programming with its latest enhancements in Java 21. Two significant Java Enhancement Proposals (JEPs) stand out: JEP 440 and JEP 441.

JEP 440: Record Patterns

JEP 440 is all about record patterns, a feature that significantly enhances the Java programming language’s capabilities regarding data manipulation. Record patterns introduce a new way of deconstructing record values, making data navigation and processing more declarative and composable.

Understanding Record Patterns

Consider a scenario with a user entity and two records: UserCreatedEvent and UserDeletedEvent. These records represent events that are associated with user activities.

@Test
public void shouldGetEventDeleted(){
    User otaviojava = new User("otaviojava");
    Supplier<User> userSupplier = new UserDeletedEvent(otaviojava, Instant.now(), "nope reason");
    var log = log(userSupplier);
    Assertions.assertEquals(otaviojava, log.get());
}

In this example, the UserDeletedEvent record is created with specific attributes, including the user affected, the timestamp, and the reason for the event. Using record patterns, you can efficiently deconstruct the UserDeletedEvent and access its attributes without tedious if-else checks.

Deconstructing Records With Record Patterns

Let’s dive into the log method, which demonstrates the power of record patterns for data navigation:

private Optional<User> log(Supplier<User> supplier){
    if(supplier instanceof UserCreatedEvent(User user, Instant instant) ){
        System.out.println("User created at " + instant + " with username " + user.username());
        return Optional of(user);
    } else if (supplier instanceof UserDeletedEvent(User user, Instant instant, String reason)) {
        System.out.println("User deleted at " + instant + " with username " + user.username() + " because " + reason);
        return Optional of(user);
    }
    return Optional.empty();
}

In this code, UserCreatedEvent(User user, Instant instant) and UserDeletedEvent(User user, Instant instant, String reason) are record patterns that allow you to directly access the user, instant, and reason attributes from the respective events. This approach is more concise and ensures that you work with data in a type-safe manner.

Reference:

JEP 441: Pattern Matching for Switch Expressions and Statements

While JEP 440 focuses on enhancing record patterns, JEP 441 extends pattern-matching capabilities by bringing it to switch expressions and statements. In this context, pattern matching enables concise and safe handling of complex data-oriented queries.

Pattern Matching With Switch Expressions

The fireEvent method demonstrates how pattern matching for switch expressions can be used effectively:

String fireEvent(Supplier<User> supplier) {
    return switch (supplier){
        case UserCreatedEvent(var user, var instant) -> "User created at " + instant + " with username " + user.username();
        case UserDeletedEvent(var user, var instant, var reason) -> "User delete at " + instant +
                " with username " + user.username() + " because " + reason;
        default -> "No event";
    };
}

This code shows pattern matching in an switch expression. Each case in the switch expression specifies a pattern and a corresponding action. The patterns destructure the supplier object, allowing you to access the user event records’ attributes directly. This approach enhances the readability and maintainability of the code, making it easier to work with complex data structures.

Exploring Further

To delve deeper into the concepts and code samples discussed in this article, visit the GitHub repository at the following link: Java 21 Code Samples.

Embracing Data-Oriented Programming

With Java 21 and the introduction of JEPs 440 and 441, data-oriented programming in Java has reached a new level of sophistication. These features empower developers to work with data more effectively, enhancing code clarity, safety, and maintainability.

In a world where data is at the core of software development, mastering these data-oriented programming features in Java 21 is essential for staying at the forefront of the industry. Whether you are building applications that involve extensive data processing or simply striving for cleaner and more readable code, JEP 440 and JEP 441 are tools that every Java developer should add to their toolkit.

Embrace the power of record patterns and pattern matching in Java 21 to unlock the full potential of your Java applications. It’s a step towards more elegant and efficient data-oriented programming, making your codebase more robust and easier to manage. Java 21 sets the stage for a brighter and more data-centric future in Java development.