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Databricks Databricks-Certified-Associate-Developer-for-Apache-Spark-3.5 Exam With Confidence Using Practice Dumps

Exam Code:
Databricks-Certified-Associate-Developer-for-Apache-Spark-3.5
Exam Name:
Databricks Certified Associate Developer for Apache Spark 3.5 – Python
Certification:
Databricks Certification
Vendor:
Databricks
Questions:
136
Last Updated:
Jul 19, 2026
Exam Status:
Stable
Databricks Databricks-Certified-Associate-Developer-for-Apache-Spark-3.5

Databricks-Certified-Associate-Developer-for-Apache-Spark-3.5: Databricks Certification Exam 2025 Study Guide Pdf and Test Engine

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Databricks Certified Associate Developer for Apache Spark 3.5 – Python Questions and Answers

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Question 1

26 of 55.

A data scientist at an e-commerce company is working with user data obtained from its subscriber database and has stored the data in a DataFrame df_user.

Before further processing, the data scientist wants to create another DataFrame df_user_non_pii and store only the non-PII columns.

The PII columns in df_user are name, email, and birthdate.

Which code snippet can be used to meet this requirement?

Options:

A.

df_user_non_pii = df_user.drop("name", "email", "birthdate")

B.

df_user_non_pii = df_user.dropFields("name", "email", "birthdate")

C.

df_user_non_pii = df_user.select("name", "email", "birthdate")

D.

df_user_non_pii = df_user.remove("name", "email", "birthdate")

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Question 2

41 of 55.

A data engineer is working on the DataFrame df1 and wants the Name with the highest count to appear first (descending order by count), followed by the next highest, and so on.

The DataFrame has columns:

id | Name | count | timestamp

---------------------------------

1 | USA | 10

2 | India | 20

3 | England | 50

4 | India | 50

5 | France | 20

6 | India | 10

7 | USA | 30

8 | USA | 40

Which code fragment should the engineer use to sort the data in the Name and count columns?

Options:

A.

df1.orderBy(col("count").desc(), col("Name").asc())

B.

df1.sort("Name", "count")

C.

df1.orderBy("Name", "count")

D.

df1.orderBy(col("Name").desc(), col("count").asc())

Question 3

A data engineer is streaming data from Kafka and requires:

Minimal latency

Exactly-once processing guarantees

Which trigger mode should be used?

Options:

A.

.trigger(processingTime='1 second')

B.

.trigger(continuous=True)

C.

.trigger(continuous='1 second')

D.

.trigger(availableNow=True)

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