Discuss Databricks Databricks Machine Learning Professional Exam Topic 9 Question 49

A data scientist wants to remove the star_rating column from the Delta table at the location path. To do this, they need to load in data and drop the star_rating column.

Which option best code blocks accomplishes this task?

Espark.sql(''SELECT * EXCEPT star_rating FROM path'')

CDelta tables cannot be modified

Bspark.read.format(''delta'').table(path).drop(''star_rating'')

Dspark.read.table(path).drop(''star_rating'')

Aspark.read.format(''delta'').load(path).drop(''star_rating'')

Suggested Answer: D

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26 comments · newest first

Hester 3 months ago

I feel like option D might miss some steps. Better to be thorough!

Edelmira 3 months ago

I’m leaning towards option C. It seems efficient for large datasets.

Jame 3 months ago

I agree, but option A looks good too. It’s straightforward.

Ty 4 months ago

I think option B is the best choice. It clearly shows how to load and drop the column.

Arthur 5 months ago

I think you might need to save the changes after dropping the column.

Kirby 5 months ago

Make sure to load the data first, or it won't work!

Kiera 5 months ago

Wait, can you really just drop it like that? Seems too simple.

Isaac 6 months ago

Totally agree, that's the easiest way to do it.

Matt 6 months ago

Just use the `drop` method on the DataFrame!

James 6 months ago

Option D is just plain silly. Who would write code like that?

Bettina 6 months ago

Hmm, I'm torn between B and C. Decisions, decisions!

Terrilyn 6 months ago

Option A is a bit too verbose, in my opinion.

Annice 6 months ago

Option C seems the most concise and efficient.

Lavonna 7 months ago

This looks straightforward. I'd go with option B.

Anisha 7 months ago

I vaguely remember that we need to use the `spark.read` method to load the data, but I'm confused about how to specify the path correctly.

Belen 7 months ago

I feel like the answer might involve reading the Delta table into a DataFrame and then chaining the drop method. I hope I remember the right order!

Serina 8 months ago

I think we practiced a similar question where we had to manipulate a DataFrame. It involved using `withColumn` and `drop`, but I can't recall the exact syntax.

Yong 8 months ago

I remember something about using the `drop` function in PySpark to remove a column, but I'm not entirely sure how to load the data first.

Chaya 8 months ago

Easy peasy! I'll just read in the data, confirm the column names, and then use that drop() method to get rid of the star_rating column. Shouldn't take more than a few lines of code.

Curt 8 months ago

Ugh, I'm a little unsure about the location path part. I'll need to double-check how to properly load the data from that specified location. But once I have the DataFrame, dropping the column should be easy.

Susy 8 months ago

No problem, I've done something like this before. I'll load the data, check the column names, and then use DataFrame.drop() to remove the star_rating column.

Lasandra 9 months ago

Okay, let's see. I'll need to figure out how to load the data from the specified location path first. Then I can drop the column using DataFrame.drop().

Jani 9 months ago

Hmm, this seems pretty straightforward. I'd start by loading the data into a DataFrame, then use the drop() method to remove the star_rating column.

An 3 months ago

↳ replying to Jani

Don't forget to save the changes back to the Delta table!

Vincent 3 months ago

↳ replying to Jani

Then we can use df.drop('star_rating', axis=1).

Billy 3 months ago

↳ replying to Jani

I agree, loading into a DataFrame is the first step.

Databricks Machine Learning Professional Exam - Topic 9 Question 49 Discussion