A mobile app backend uses Java streams to process user data. The code snippet filters users who are active and older than 18, then collects them into a list:
List<User> result = users.stream() .filter(u -> u.isActive()) .filter(u -> u.getAge() > 18) .collect(Collectors.toList());
Performance metrics show that this stream operation is slow when the user list has millions of entries. The team wants to improve performance without changing the business logic. Which change would most likely improve performance?

Question

A mobile app backend uses Java streams to process user data. The code snippet filters users who are active and older than 18, then collects them into a list:

List<User> result = users.stream()
        .filter(u -> u.isActive())
        .filter(u -> u.getAge() > 18)
        .collect(Collectors.toList());

Performance metrics show that this stream operation is slow when the user list has millions of entries. The team wants to improve performance without changing the business logic. Which change would most likely improve performance?

Accepted Answer

Replace .stream() with .parallelStream().. Replacing `.stream()` with `.parallelStream()` enables parallel processing of the stream, which can leverage multiple CPU cores to process the filter operations concurrently. For large datasets (millions of entries), this can significantly reduce execution time by splitting the workload across threads, while preserving the same business logic and order of operations.

Answer

Use a HashSet instead of List for users collection.

Answer

Replace the stream with a traditional for loop.

Answer

Combine both filters into one using logical AND operator.

1Z0-811 Java Basics and Syntax Practice Question

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