A data engineer is building a Silver-layer table from ingested event records. Each row has columns event_id, user_id, event_type, and ingest_timestamp. Duplicate events can arrive with the same event_id but slightly different ingest_timestamp values. The engineer wants to keep only one row per unique event_id, regardless of the timestamp. Which PySpark approach correctly deduplicates the DataFrame based on event_id alone?