In a scenario where you are working with a large dataset in Azure Databricks that includes a 'timestamp' column formatted as 'yyyy-MM-dd HH:mm:ss', you are tasked with optimizing a Spark SQL query to extract the hour and minute from this 'timestamp' column for further analysis. The solution must not only be correct but also efficient, considering the dataset's size and the need for scalability. Given the following options, which Spark SQL query would you use to correctly and efficiently extract the hour and minute from the 'timestamp' column and create a new table with these extracted values? Choose the best option.