Solution#242
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Review Summary
Great job on the overall structure and use of CompletableFuture! Your solution correctly implements most of the requirements.
However, there is a critical concurrency issue in AsyncRequestProcessor.java that needs to be addressed. The current if (cache.containsKey(userId)) { ... } else { ... } logic creates a race condition. If two requests for the same new user arrive at the same time, both can pass the containsKey check and proceed to execute the expensive processing task, defeating the purpose of the cache.
To resolve this, you should use an atomic operation. I recommend looking into the ConcurrentHashMap.computeIfAbsent() method. It's designed for exactly this scenario, ensuring that the value-computation logic is executed only once for any given key. Fixing this will make your solution robust and efficient under concurrent loads.
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Footnotes
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| public CompletableFuture<UserData> processRequest(String userId) { | ||
| return null; | ||
| if (cache.containsKey(userId)) { |
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This check-then-act pattern creates a race condition. If two requests for the same new userId arrive concurrently, both might find the cache empty and proceed to execute the expensive supplyAsync task. This results in redundant work. Consider how you could make the cache check and the task creation an atomic operation to ensure processing for a given userId only happens once.
mateacademy-ai-mentor
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Review Summary
Excellent work on this solution! You've done a fantastic job resolving the race condition from the previous review by using computeIfAbsent. This is the ideal, thread-safe approach for this scenario, making your code robust and efficient. Your implementation now correctly meets all the task requirements. I am happy to approve this submission. Keep up the great work!
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