A data engineer needs to load a set of JSON files from a mounted cloud storage location into a DataFrame for a one-time batch analysis. Each JSON file contains a single record that spans multiple lines (pretty-printed JSON). When they run spark.read.format('json').load('/mnt/raw/orders/'), every row comes back as corrupt records instead of parsed fields. What change will correctly parse these files?