DP-600 practice - PrepKeys

Q5 Single choice

You are analyzing customer purchases in a Fabric notebook by using PySpark.

You have the following DataFrames: transactions: Contains five columns named transaction_id, customer_id, product_id, amount, and date and has 10 million rows, with each row representing a transaction. customers: Contains customer details in 1,000 rows and three columns named customer_id, name, and country.

You need to join the DataFrames on the customer_id column. The solution must minimize data shuffling.

You write the following code.

from pyspark.sql import functions as F results = Which code should you run to populate the results DataFrame?

A
transactions.join(F.broadcast(customers), transactions.customer_id == customers.customer_id)
B
transactions.join(customers, transactions.customer_id == customers.customer_id).distinct()
C
transactions.join(customers, transactions.customer_id == customers.customer_id)
D
transactions.crossJoin(customers).where(transactions.customer_id == customers.customer_id)