Microsoft Exam DP-600 Topic 3 Question 17 Discussion

Actual exam question for Microsoft's DP-600 exam

Question #: 17
Topic #: 3

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.show()

Does this meet the goal?

AYes

BNo

Show Suggested Answer

Suggested Answer: B

The df.show() method also does not meet the goal. It is used to show the contents of the DataFrame, not to compute statistical functions. Reference = The usage of the show() function is documented in the PySpark API documentation.

by Jules at Jul 11, 2024, 02:21 PM

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Janine

8 months ago

I'm sorry, but df.show() is not going to give us the statistical analysis we need. I think the correct answer is 'No' on this one. Let's move on to the next question, where we can hopefully find a more challenging problem to solve.

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Lucina

8 months ago

Yeah, we definitely need a different approach for this.

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Claudio

8 months ago

I agree, df.show() won't give us the stats we need.

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My

8 months ago

Haha, I've seen some lazy solutions in my day, but this takes the cake. df.show()? Really? I bet the answer is 'No' on this one.

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Jame

8 months ago

Nah, this isn't going to cut it. We need to dig deeper into the Spark DataFrame API to get the job done. What is this, PySpark for Dummies?

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Rima

8 months ago

Hmm, df.show() just prints the first few rows of the DataFrame. It doesn't actually calculate any statistical measures. I think we need to use functions like min(), max(), mean(), and stddev() to get the job done.

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Mitsue

8 months ago

Wow, that's a pretty basic solution. I'm not sure it's going to give us the full analysis we need. Where are the min, max, mean, and standard deviation calculations?

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