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Databricks Machine Learning Professional Exam - Topic 12 Question 29 Discussion

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)
D) Option D
A) Option A
B) Option B
C) Option C
E) features_df.write.mode('feature').path('new_table')

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)

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Suggested Answer: D

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

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Loreta
7 months ago
Not sure about Option E, that "feature" mode seems weird.
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Lonny
8 months ago
Definitely leaning towards Option D, it seems right.
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Kristine
8 months ago
Wait, can you really use "fs" in Option C? Sounds off.
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Reta
8 months ago
I think Option B is the way to go!
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Raelene
8 months ago
Option A looks solid for creating the Feature Store table.
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Reynalda
9 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.
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Levi
9 months ago
Option C seems off to me; I don't think "fs" is a valid mode for writing to a Feature Store.
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Sylvia
9 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.
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Huey
9 months ago
I remember we discussed how to use the Feature Store Client, but I'm not sure which option correctly uses it here.
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Mitsue
9 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.
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Shantay
9 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.
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Thurman
9 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.
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Dick
9 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.
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Stephane
9 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.
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Gussie
9 months ago
I'm pretty confident this is about using vMotion to migrate VMs without downtime, so I'll go with option A.
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Myong
2 years ago
Haha, Option E? 'features_df.write.mode(feature).path(new_table)'? Is that like, a special 'feature-flavored' write mode or something?
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Bette
2 years 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'?
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Kirk
2 years ago
Let's go with Option A and name the table 'feature_extravaganza' for some added flair.
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Rory
2 years ago
Yes, Option A with the 'feature_extravaganza' table name sounds like a great combination.
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Van
2 years ago
I think the 'feature_extravaganza' name suggestion is fun and creative!
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Valentine
2 years ago
I agree, Option A is the best choice for creating and populating the Feature Store table.
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Hyman
2 years ago
Option C? Really? 'features_df.write.mode(fs).path(new_table)'? That's not how you interact with the Feature Store, my dude.
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Annette
2 years ago
Hmm, I'd go with Option D. The `fs.create_feature_table()` method looks like it's specifically designed for this use case.
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Ty
2 years ago
I think Option D is the correct one as well. The `fs.create_feature_table()` method seems to be the way to go.
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Edna
2 years ago
I agree, Option D seems to be the most appropriate for creating and populating the Feature Store table.
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Shala
2 years ago
Option D looks good to me too. The `fs.create_feature_table()` method seems like the right choice.
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Alease
2 years ago
Hmm, that makes sense. Let's see what others think before making a final decision.
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Catrice
2 years ago
I disagree, I believe Option B is the right choice because it uses the Feature Store Client fs.
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Nydia
2 years ago
Option B seems the most straightforward way to create the Feature Store table. No need to overcomplicate things.
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Devora
2 years ago
Yeah, Option B seems like the most straightforward solution.
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Chan
2 years ago
I agree, Option B looks simple and effective.
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Carey
2 years ago
I think Option B is the best choice.
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Alease
2 years ago
I think Option A is the correct code block to create the Feature Store table.
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