To create a Python dictionary from a Spark DataFrame, you can first collect the data to the driver node and then convert it into a Python dictionary using dict().

Steps:

Select only relevant columns.

Order by region_id to get the smallest ones.

Limit to 3 rows.

Map each row into key–value pairs.

Collect results to the driver and convert to a dictionary.

Correct code:

regions_dict = dict(

regions.orderBy("region_id")

limit(3)

rdd.map(lambda x: (x.region_id, x.region_name))

collect()

)

This produces a dictionary like:

{10: 'North', 12: 'East', 14: 'West'}

Why the other options are incorrect:

A/B: take(3) returns a list of Row objects, not key–value pairs.

C: Doesn’t order or limit by smallest IDs, so the result may not be correct.