DP-600 · Question #92
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might h
The correct answer is B. No. df.explain gives execution plan. https://spark.apache.org/docs/3.1.2/api/python/reference/api/pyspark.sql.DataFrame.explain.html
Question
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution. After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen. You have a Fabric tenant that contains a new semantic model in OneLake. You use a Fabric notebook to read the data into a Spark DataFrame. You need to evaluate the data to calculate the min, max, mean, and standard deviation values for all the string and numeric columns. Solution: You use the following PySpark expression:
df.explain().show() Does this meet the goal?
Options
- AYes
- BNo
How the community answered
(34 responses)- A12% (4)
- B88% (30)
Explanation
df.explain gives execution plan. https://spark.apache.org/docs/3.1.2/api/python/reference/api/pyspark.sql.DataFrame.explain.html
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