New Year Sale 2026! Hurry Up, Grab the Special Discount - Save 25% - Ends In 00:00:00 Coupon code: SAVE25
Welcome to Pass4Success

- Free Preparation Discussions
Mail Us support@pass4success.com
Location US
Mob_nav_barsMENU

Databricks Machine Learning Professional Exam - Topic 12 Question 29 Discussion

Actual exam question for Databricks's Databricks Machine Learning Professional exam
Question #: 29
Topic #: 12
[All Databricks Machine Learning Professional Questions]

A data scientist has created a Python function compute_features that returns a Spark DataFrame with the following schema:

The resulting DataFrame is assigned to the features_df variable. The data scientist wants to create a Feature Store table using features_df.

Which of the following code blocks can they use to create and populate the Feature Store table using the Feature Store Client fs?

A)

B)

C)

features_df.write.mode("fs").path("new_table")

D)

Show Suggested Answer Hide Answer
Suggested Answer: D

by Miriam at Sep 18, 2024, 01:28 AM

Limited Time Offer

25%

Off

Get Premium Databricks Machine Learning Professional Questions as Interactive Web-Based Practice Test or PDF

Contribute your Thoughts:

0/2000 characters
Submit Cancel
Loreta
3 months ago
Not sure about Option E, that "feature" mode seems weird.
upvoted 0 times
...
Lonny
3 months ago
Definitely leaning towards Option D, it seems right.
upvoted 0 times
...
Kristine
3 months ago
Wait, can you really use "fs" in Option C? Sounds off.
upvoted 0 times
...
Reta
4 months ago
I think Option B is the way to go!
upvoted 0 times
...
Raelene
4 months ago
Option A looks solid for creating the Feature Store table.
upvoted 0 times
...
Reynalda
4 months ago
I vaguely remember that we should use a specific method for the Feature Store, but I can't remember if it's in option D or E.
upvoted 0 times
...
Levi
4 months ago
Option C seems off to me; I don't think "fs" is a valid mode for writing to a Feature Store.
upvoted 0 times
...
Sylvia
4 months ago
I think options A and B look similar to the examples we practiced, but I can't recall the exact syntax for creating a Feature Store table.
upvoted 0 times
...
Huey
5 months ago
I remember we discussed how to use the Feature Store Client, but I'm not sure which option correctly uses it here.
upvoted 0 times
...
Mitsue
5 months ago
This seems straightforward. I think Option B is the correct answer, as it uses the Feature Store Client `fs` to create and write the table.
upvoted 0 times
...
Shantay
5 months ago
Okay, let's think this through step-by-step. The key is to use the Feature Store Client `fs` to create and populate the table. I'll need to compare the code blocks and see which one matches that requirement.
upvoted 0 times
...
Thurman
5 months ago
Hmm, I'm a bit unsure about the different options here. I'll need to carefully read through the code blocks and the question to make sure I understand the correct approach.
upvoted 0 times
...
Dick
5 months ago
This looks like a straightforward question about creating a Feature Store table from a Spark DataFrame. I think I can handle this one.
upvoted 0 times
...
Stephane
5 months ago
I'm feeling a bit confused by the different options. I'll need to review the Feature Store documentation to make sure I understand the correct syntax and approach for this task.
upvoted 0 times
...
Gussie
5 months ago
I'm pretty confident this is about using vMotion to migrate VMs without downtime, so I'll go with option A.
upvoted 0 times
...
Myong
1 year ago
Haha, Option E? 'features_df.write.mode(feature).path(new_table)'? Is that like, a special 'feature-flavored' write mode or something?
upvoted 0 times
...
Bette
1 year ago
Option A is the winner here. The `fs.write_table()` method is the way to go. Although, I have to say, the 'new_table' name is a bit uninspired. How about 'feature_extravaganza'?
upvoted 0 times
Kirk
1 year ago
Let's go with Option A and name the table 'feature_extravaganza' for some added flair.
upvoted 0 times
...
Rory
1 year ago
Yes, Option A with the 'feature_extravaganza' table name sounds like a great combination.
upvoted 0 times
...
Van
1 year ago
I think the 'feature_extravaganza' name suggestion is fun and creative!
upvoted 0 times
...
Valentine
1 year ago
I agree, Option A is the best choice for creating and populating the Feature Store table.
upvoted 0 times
...
...
Hyman
1 year ago
Option C? Really? 'features_df.write.mode(fs).path(new_table)'? That's not how you interact with the Feature Store, my dude.
upvoted 0 times
...
Annette
1 year ago
Hmm, I'd go with Option D. The `fs.create_feature_table()` method looks like it's specifically designed for this use case.
upvoted 0 times
Ty
1 year ago
I think Option D is the correct one as well. The `fs.create_feature_table()` method seems to be the way to go.
upvoted 0 times
...
Edna
1 year ago
I agree, Option D seems to be the most appropriate for creating and populating the Feature Store table.
upvoted 0 times
...
Shala
1 year ago
Option D looks good to me too. The `fs.create_feature_table()` method seems like the right choice.
upvoted 0 times
...
...
Alease
1 year ago
Hmm, that makes sense. Let's see what others think before making a final decision.
upvoted 0 times
...
Catrice
1 year ago
I disagree, I believe Option B is the right choice because it uses the Feature Store Client fs.
upvoted 0 times
...
Nydia
1 year ago
Option B seems the most straightforward way to create the Feature Store table. No need to overcomplicate things.
upvoted 0 times
Devora
1 year ago
Yeah, Option B seems like the most straightforward solution.
upvoted 0 times
...
Chan
1 year ago
I agree, Option B looks simple and effective.
upvoted 0 times
...
Carey
1 year ago
I think Option B is the best choice.
upvoted 0 times
...
...
Alease
1 year ago
I think Option A is the correct code block to create the Feature Store table.
upvoted 0 times
...

Save Cancel