Combine a dynamic array for O(1) random access with a hash map for O(1) insert/delete by storing each element's index. When deleting, swap the target with the last element, update the map, and pop the array. This ensures all operations average O(1).
Pro tip: Mention that the hash map must store indices, and that deletion requires swapping with the last element to maintain O(1) and avoid shifting. Also note that duplicates require careful handling, such as storing a set of indices per value.
Confirm that elements are unique or discuss handling duplicates, and that getRandom should return each element with equal probability.
Select a dynamic array (e.g., ArrayList in Java, list in Python) for O(1) random access and a hash map (dictionary) for O(1) lookups.
Append the new element to the array and record its index in the hash map.
To delete, swap the target element with the last element in the array, update the hash map for the swapped element, then remove the last element from both the array and the map.
Generate a random index within the array's bounds and return the element at that index.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Start by briefly restating the data structure (e.g., dynamic array with hash map for O(1) operations) and its invariants. Then present two distinct concurrency designs: coarse-grained locking and fine-grained locking (or lock-free). For each, explain the mechanism, analyze trade-offs in performance, scalability, and complexity, and conclude with a recommendation based on expected workload.
Pro tip: Acknowledge that 'thread-safe' doesn't mean 'lock everything'—discuss how read-heavy workloads might benefit from read-write locks or copy-on-write, and mention that Google often values scalability and simplicity over micro-optimizations.
Briefly describe the underlying data structure (e.g., array + hash map) and the add, delete, get-random operations, highlighting the invariants that must be preserved under concurrency.
Propose a single mutex protecting the entire structure. Explain how each operation acquires the lock, performs the operation, and releases it. Discuss simplicity and correctness, but note limited scalability due to serialization.
Propose a more concurrent design, such as per-bucket locks for the hash map and a separate lock for the array, or a lock-free approach using atomic operations. Explain how operations coordinate to maintain consistency.
Analyze each design in terms of performance (throughput, latency), scalability (contention, number of cores), complexity (implementation, debugging), and memory overhead. Mention scenarios where each is preferable.
Based on the comparison, recommend one design for a given workload (e.g., read-heavy vs write-heavy) and summarize key considerations.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.