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Databricks Exam Databricks-Certified-Associate-Developer-for-Apache-Spark-3.0 Topic 2 Question 65 Discussion

Actual exam question for Databricks's Databricks-Certified-Associate-Developer-for-Apache-Spark-3.0 exam
Question #: 65
Topic #: 2
[All Databricks-Certified-Associate-Developer-for-Apache-Spark-3.0 Questions]

Which of the following code blocks shows the structure of a DataFrame in a tree-like way, containing both column names and types?

Show Suggested Answer Hide Answer
Suggested Answer: B

itemsDf.printSchema()

Correct! Here is an example of what itemsDf.printSchema() shows, you can see the tree-like structure containing both column names and types:

root

|-- itemId: integer (nullable = true)

|-- attributes: array (nullable = true)

| |-- element: string (containsNull = true)

|-- supplier: string (nullable = true)

itemsDf.rdd.printSchema()

No, the DataFrame's underlying RDD does not have a printSchema() method.

spark.schema(itemsDf)

Incorrect, there is no spark.schema command.

print(itemsDf.columns)

print(itemsDf.dtypes)

Wrong. While the output of this code blocks contains both column names and column types, the information is not arranges in a tree-like way.

itemsDf.print.schema()

No, DataFrame does not have a print method.

Static notebook | Dynamic notebook: See test 3, Question: 36 (Databricks import instructions)


Contribute your Thoughts:

Mona
22 days ago
B is the clear winner here. The other options either don't show the full schema or are just plain silly.
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Lacey
23 days ago
Haha, I almost went with E. `itemsDf.print.schema()` - sounds like something a comedy writer would come up with!
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Tommy
3 days ago
User2: B) itemsDf.printSchema() shows the structure of a DataFrame in a tree-like way.
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Fausto
6 days ago
User1: I almost went with E. `itemsDf.print.schema()` - sounds like something a comedy writer would come up with!
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Levi
24 days ago
I agree, B is the correct answer. The other options don't quite capture the tree-like structure with column names and types.
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Clay
26 days ago
Definitely B, `itemsDf.printSchema()` is the way to go! It's the most concise and straightforward option.
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Tijuana
6 days ago
User3: I always use `printSchema()` to check the DataFrame structure.
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Iesha
12 days ago
Yeah, it's simple and easy to understand.
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Augustine
18 days ago
I agree, `itemsDf.printSchema()` is the best choice.
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Noah
1 months ago
Hey, at least we're not asked to write any code! I'd probably end up with a syntax error or two if that were the case.
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Domingo
1 days ago
Haha, yeah, coding can be tricky sometimes!
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Cristy
3 days ago
B) itemsDf.printSchema()
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Tricia
17 days ago
A) 1. print(itemsDf.columns) 2. print(itemsDf.types)
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Nathan
1 months ago
Hmm, I was leaning towards Option D, but I guess that's not the right way to go about it. Rookie mistake, I suppose.
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Iluminada
2 days ago
User1: Thanks for the clarification, I'll go with Option B then.
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Boris
7 days ago
User3: Yeah, Option B is the one that shows the structure of a DataFrame in a tree-like way.
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Aileen
10 days ago
I agree, Option B is the way to go.
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Lucia
1 months ago
I think Option B is the correct one.
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Dan
2 months ago
I'm not sure, but I think D) itemsDf.rdd.printSchema() might also work. It's worth considering as an alternative option.
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Roslyn
2 months ago
Haha, true that! Coding on exams is the worst. I'm just glad we get to choose from multiple-choice options here.
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Francoise
13 days ago
I always get nervous during coding exams.
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Rodolfo
29 days ago
That's the correct option for displaying DataFrame structure.
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Twanna
1 months ago
B) itemsDf.printSchema()
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Dion
2 months ago
I agree with Curt. B) itemsDf.printSchema() is the right choice because it displays both column names and types.
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Roxanne
2 months ago
Option B is the correct answer. itemsDf.printSchema() displays the schema of the DataFrame in a tree-like format, showing both column names and data types.
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Dean
2 months ago
Yes, that's correct. It shows the structure of the DataFrame in a tree-like way.
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Tatum
2 months ago
I think the answer is B) itemsDf.printSchema()
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Curt
2 months ago
I think the answer is B) itemsDf.printSchema(). It shows the structure of a DataFrame in a tree-like way.
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