You are running a streaming pipeline with Dataflow and are using hopping windows to group the data as the data arrives. You noticed that some data is arriving late but is not being marked as late data, which is resulting in inaccurate aggregations downstream. You need to find a solution that allows you to capture the late data in the appropriate window. What should you do?

A. Use watermarks to define the expected data arrival window. Allow late data as it arrives. B. Change your windowing function to tumbling windows to avoid overlapping window periods. C. Change your windowing function to session windows to define your windows based on certain activity. D. Expand your hopping window so that the late data has more time to arrive within the grouping.