In a scenario where you are working with a large dataset stored in Azure Databricks, you encounter a 'product_info' column that contains JSON objects. Each JSON object includes various product details, among which is a 'price' field stored as a numeric value. Your task is to write a Spark SQL query that extracts the 'price' field from the JSON objects, casts it to a double type, and creates a new table displaying both the original 'price' and the newly casted 'double_price'. Considering the need for accuracy and efficiency in handling JSON data within Spark SQL, which of the following queries correctly accomplishes this task? (Choose one option)