The quota-freeing part is what tripped me up.
Start by clarifying the data model and concurrency requirements, then outline the complete_task operation's contract: validate assignment existence and active status, atomically update state, and release the quota slot. Emphasize idempotency, thread-safety, and consistency between assignment status and quota accounting.
Pro tip: Discuss how you would handle race conditions—e.g., using locks or compare-and-swap—to ensure the quota is freed exactly once, and mention that returning false for non-existent or inactive assignments prevents double-freeing and maintains data integrity.
Ask about concurrency expectations, persistence, and whether assignments can be shared. Confirm that 'active' means not completed or cancelled, and that quota is per-user.
Define an Assignment entity with fields like id, userId, status (active/completed), and timestamps. Ensure the scheduler maintains a mapping from assignment to user and a quota counter per user.
Look up the assignment by ID; if missing or not active, return false. Otherwise, atomically set status to completed, decrement the user's active assignment count, and return true.
Use locks, transactions, or atomic operations to prevent race conditions where two complete_task calls could both succeed and double-decrement quota. Consider optimistic concurrency with versioning.
Handle cases like completing an already completed assignment, quota overflow/underflow, and how this operation interacts with update and search. Mention logging and metrics for observability.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
I went straight to a linear scan over all assignments and the interviewer pushed back pretty fast.
Clarify the data model and semantics first, then propose an efficient query using appropriate indexes and possibly denormalization. Discuss trade-offs between read-time computation and write-time maintenance, and how to scale for large datasets.
Pro tip: Mention that you would use a partial index on (user_id, due_date) WHERE completed_at IS NULL to make the query fast, and consider a materialized view or background job if the query is frequent.
Ask about the schema: how tasks, assignments, and completions are stored. Confirm that 'finish time' means due date and that 'never completed before that deadline' means completed_at is null or > due_date.
Write a SQL query that selects task IDs from assignments where user_id = ? and due_date < ? and (completed_at is null or completed_at > due_date).
Propose a composite index on (user_id, due_date) and a partial index for incomplete tasks. Discuss covering indexes to avoid table lookups.
If the query is frequent, suggest denormalizing overdue tasks into a separate table or using a background job to precompute results. Discuss caching and read replicas.
Mention handling of null due dates, time zones, and tasks completed exactly at the deadline. Suggest unit tests and performance testing.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Start by clarifying the requirements and defining the state model as a finite set of states with explicit transitions, then discuss how to represent derived states like overdue. Walk through the lifecycle from creation to completion, explaining how get_user_tasks should filter and return tasks based on the requested view (active, completed, overdue) and how to handle the fact that overdue is neither active nor completed. Emphasize trade-offs between storing state vs. computing it, and how to ensure consistency and performance.
Pro tip: Mention that overdue is a derived state based on due date and completion status, so it shouldn't be stored as a primary state to avoid stale data. Instead, compute it dynamically or via a scheduled job, and ensure get_user_tasks accepts a filter parameter to return the appropriate subset.
Ask questions to understand what states are needed, how tasks are assigned, and what get_user_tasks is expected to return. Confirm whether overdue is a separate state or a derived condition.
Propose a finite state machine with states like pending, completed, and possibly expired/cancelled. Define allowed transitions (e.g., pending -> completed, pending -> overdue) and how overdue is determined (due date passed and not completed).
Suggest storing a status field for primary states (pending, completed) and a due_date field. Overdue is computed as status == pending AND due_date < now. Discuss trade-offs of materializing overdue vs. computing on the fly.
Explain that get_user_tasks should accept parameters like user_id and a filter (e.g., view='active', 'completed', 'overdue'). For 'active', return pending tasks that are not overdue; for 'overdue', return pending tasks past due; for 'completed', return completed tasks. Ensure the query is efficient with proper indexing.
Discuss handling time zones, clock skew, and how to update overdue status (e.g., via cron job or on-read). Mention consistency concerns if materializing overdue and how to avoid race conditions.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.