A data scientist is building a training dataset using a Databricks Feature Store feature table that stores time-varying customer metrics (e.g., rolling 30-day spend) with a timestamp column. Each training label event also has its own event timestamp. When creating the training set with FeatureLookup, the scientist wants to ensure that each label row is joined only with feature values that were known at or before the label's event time, preventing data leakage from future feature updates. Which approach correctly achieves this?