Start by clarifying requirements and constraints, then design the API with setter methods for conjunctive filters and cursor-based pagination. Explain the cursor encoding, sort key, and how to handle edge cases like empty pages and data mutations. Finally, provide complexity analysis and discuss trade-offs.
Pro tip: Emphasize idempotency and consistency: use a stable sort key (e.g., timestamp + ID) and encode the last seen values in the cursor to avoid duplicates or missed records when data changes between requests.
Ask about data volume, expected query patterns, consistency requirements, and whether mutations are frequent. Confirm the need for conjunctive filters and cursor-based pagination.
Define setter methods for each filter field (start date, end date, user ID, amount) that combine with AND logic. Specify a method to execute the query with a cursor and limit, returning a page of results and a next cursor.
Choose a sort key (e.g., start_date, then transaction_id). Encode the last record's sort key values into an opaque cursor (e.g., Base64-encoded JSON). On subsequent requests, use the cursor to fetch records after the last seen key.
Address empty pages by returning an empty list and null cursor. Detect end-of-results when no more records match. For data mutations, use the cursor to maintain a stable snapshot or acknowledge potential inconsistencies and suggest strategies like versioning or time-travel queries.
Discuss time complexity of filtering and pagination (e.g., O(log n + k) with indexed sort key). Compare cursor-based vs offset pagination. Mention trade-offs between consistency and performance.
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