An engineer has a large ORC file located at /file/test_data.

The correct way to load specific columns from an ORC file is to first load the file using .load() and then apply .select() on the resulting DataFrame. This is valid with .read.format("orc") or the shortcut .read.orc().

df = spark.read.format("orc").load("/file/test_data.orc").select("col1", "col2")

Why others are incorrect:

A performs selection after filtering, but doesn’t match the intention to minimize memory at load.

B incorrectly tries to use .select() before .load(), which is invalid.

C uses a non-existent .selected() method.

D correctly loads and then selects.