Câu 41: DP-600: Implementing Analytics Solutions Using Microsoft Fabric

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 Fresults =Which code should you run to populate the results DataFrame?

1. A. transactions.join(F.broadcast(customers), transactions.customer_id == customers.customer_id) — đáp án hiện tại
2. B. transactions.join(customers, transactions.customer_id == customers.customer_id).distinct()
3. C. transactions.join(customers, transactions.customer_id == customers.customer_id)
4. D. transactions.crossJoin(customers).where(transactions.customer_id == customers.customer_id)