ConcurrentHashMap

Detailed answer

Logic: Thread-safe map with fine-grained locking/CAS. compute/merge methods atomic per key. Weakly consistent iterators — no ConcurrentModificationException. Complexity notes included in code section when present. Pros: Better than Hashtable/synchronizedMap for high concurrency. Cons: Compound actions across keys need external locking; not for strong iteration snapshot. Core: Thread-safe map with fine-grained locking/CAS. compute/merge methods atomic per key. Weakly consistent iterators — no ConcurrentModificationException. Real-time example: Rate limiter stores token counts per API key updated from many threads concurrently. Pros: Better than Hashtable/synchronizedMap for high concurrency. Cons: Compound actions across keys need external locking; not for strong iteration snapshot. Common mistakes: if (!map.containsKey(k)) map.put(k,v) race — use putIfAbsent or compute. Best practices: Use compute/merge; avoid locking entire map for single-key updates. Audience level: Architect.

Full explanation

Thread-safe map with fine-grained locking/CAS. compute/merge methods atomic per key. Weakly consistent iterators — no ConcurrentModificationException.

Code example

ConcurrentHashMap<String, Integer> counts = new ConcurrentHashMap<>();

void increment(String key) {
    counts.merge(key, 1, Integer::sum);
}

int get(String key) {
    return counts.getOrDefault(key, 0);
}

Practice code · java (view only · no execution)

ConcurrentHashMap<String, Integer> counts = new ConcurrentHashMap<>();

void increment(String key) {
    counts.merge(key, 1, Integer::sum);
}

int get(String key) {
    return counts.getOrDefault(key, 0);
}

Follow-up questions

• How would you test ConcurrentHashMap?
• What metrics prove ConcurrentHashMap is healthy in prod?
• How does ConcurrentHashMap change at 10× traffic?