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Working with Streams and Lambda ExpressionsmediumMultiple ChoiceObjective-mapped

1Z0-829 Working with Streams and Lambda Expressions Practice Question

A data analytics platform processes user activity logs. Each log entry is a LogRecord with fields: userId (int), action (String), timestamp (long). The requirement is to find the top 3 most active users (by count of actions) in the last hour. The logs are stored in a List<LogRecord> logs. The current solution sorts all records by userId and counts manually, but it's slow. The team decides to use streams with parallel processing. Which code correctly identifies the top 3 users?

⚠ Common exam trap

The trap here is that candidates may forget to filter by timestamp (as in option C) or group by the wrong field (as in option D), or sort by the wrong comparator (as in option B), leading to incorrect results that still compile and run.

Answer choices

Why each option matters

Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.

Correct answer & explanation

logs.parallelStream().filter(l -> l.timestamp() > System.currentTimeMillis() - 3600000).collect(Collectors.groupingBy(LogRecord::userId, Collectors.counting())).entrySet().stream().sorted(Map.Entry.<Long, Long>comparingByValue().reversed()).limit(3).collect(Collectors.toList())

It first filters logs to only those within the last hour, then groups by userId and counts actions, sorts the resulting map entries by count in descending order, limits to the top 3, and collects the result. This uses parallelStream() for performance and correctly applies the required logic.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • logs.parallelStream().filter(l -> l.timestamp() > System.currentTimeMillis() - 3600000).collect(Collectors.groupingBy(LogRecord::userId, Collectors.counting())).entrySet().stream().sorted(Map.Entry.<Long, Long>comparingByValue().reversed()).limit(3).collect(Collectors.toList())

    Why this is correct

    Correct.

  • logs.parallelStream().filter(l -> l.timestamp() > System.currentTimeMillis() - 3600000).collect(Collectors.groupingBy(LogRecord::userId, Collectors.counting())).entrySet().stream().sorted(Map.Entry.comparingByKey()).limit(3).collect(Collectors.toList())

    Why it's wrong here

    Sorted by userId, not count.

  • logs.parallelStream().collect(Collectors.groupingBy(LogRecord::userId, Collectors.counting())).entrySet().stream().sorted(Map.Entry.comparingByValue().reversed()).limit(3).collect(Collectors.toList())

    Why it's wrong here

    No time filter.

  • logs.parallelStream().filter(l -> l.timestamp() > System.currentTimeMillis() - 3600000).collect(Collectors.groupingBy(LogRecord::action, Collectors.counting())).entrySet().stream().sorted(Map.Entry.comparingByValue().reversed()).limit(3).collect(Collectors.toList())

    Why it's wrong here

    Grouped by action, not userId.

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Last reviewed: Jun 11, 2026

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