Log Processing (Parsing & Aggregation)

Log Processing (Parsing & Aggregation) You are given line-based text logs. Each line contains multiple fields (e.g., timestamp, request id, user id, event type, status code, latency). You must parse, clean, and compute the required aggregations or output filtered records. Typical tasks (the interviewer will specify) Per-user/per-endpoint success rate, P95/P99 latency, error counts Identify endpoints/users with the highest failure rates Time-windowed aggregations (per minute / per 5 minutes) Group by trace/request id and output anomalous flows Input/Output Input: multiple log lines (some may be malformed). Output: aggregated results (map/table/sorted list/printed report). Constraints Explain handling of malformed lines, missing fields, out-of-order events, and large scale (streaming vs in-memory). Note: Original details are missing; this is the interview-pattern summary.