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Which of the following code blocks returns a new DataFrame with only columns predError and values of every second row of DataFrame transactionsDf? Entire DataFrame transactionsDf: 1.+-------------+---------+-----+-------+---------+----+ 2.|transactionId|predError|value|storeId|productId| f| 3.+-------------+---------+-----+-------+---------+----+ 4.| 1| 3| 4| 25| 1|null| 5.| 2| 6| 7| 2| 2|null| 6.| 3| 3| null| 25| 3|null| 7.| 4| null| null| 3| 2|null| 8.| 5| null| null| null| 2|null| 9.| 6| 3| 2| 25| 2|null| 10.+-------------+---------+-----+-------+---------+----+
Correct Answer: D
Explanation Output of correct code block: +---------+-----+ |predError|value| +---------+-----+ | 6| 7| | null| null| | 3| 2| +---------+-----+ This is not an easy question to solve. You need to know that % stands for the module operator in Python. % 2 will return true for every second row. The statement using spark.sql gets it almost right (the modulo operator exists in SQL as well), but % 2 = 2 will never yield true, since modulo 2 is either 0 or 1. Other answers are wrong since they are missing quotes around the column names and/or use filter or select incorrectly. If you have any doubts about SparkSQL and answer options 3 and 4 in this question, check out the notebook I created as a response to a related student question. Static notebook | Dynamic notebook: See test 1