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Databricks Associate-Developer-Apache-Spark-3.5 Exam Syllabus Topics:

Databricks Certified Associate Developer for Apache Spark 3.5 - Python Sample Questions:

Question 1

A data engineer wants to create a Streaming DataFrame that reads from a Kafka topic called feed.

Which code fragment should be inserted in line 5 to meet the requirement?
Code context:
spark \
.readStream \
.format("kafka") \
.option("kafka.bootstrap.servers", "host1:port1,host2:port2") \
.[LINE 5] \
.load()
Options:

A. .option("topic", "feed")
B. .option("subscribe.topic", "feed")
C. .option("kafka.topic", "feed")
D. .option("subscribe", "feed")

Question 2

7 of 55.
A developer has been asked to debug an issue with a Spark application. The developer identified that the data being loaded from a CSV file is being read incorrectly into a DataFrame.
The CSV file has been read using the following Spark SQL statement:
CREATE TABLE locations
USING csv
OPTIONS (path '/data/locations.csv')
The first lines of the command SELECT * FROM locations look like this:
| city | lat | long |
| ALTI Sydney | -33... | ... |
Which parameter can the developer add to the OPTIONS clause in the CREATE TABLE statement to read the CSV data correctly again?

A. 'sep' ','
B. 'header' 'false'
C. 'header' 'true'
D. 'sep' '|'

Question 3

16 of 55.
A data engineer is reviewing a Spark application that applies several transformations to a DataFrame but notices that the job does not start executing immediately.
Which two characteristics of Apache Spark's execution model explain this behavior? (Choose 2 answers)

A. The Spark engine optimizes the execution plan during the transformations, causing delays.
B. The Spark engine requires manual intervention to start executing transformations.
C. Only actions trigger the execution of the transformation pipeline.
D. Transformations are evaluated lazily.
E. Transformations are executed immediately to build the lineage graph.

Question 4

5 of 55.
What is the relationship between jobs, stages, and tasks during execution in Apache Spark?

A. A job contains multiple stages, and each stage contains multiple tasks.
B. A job contains multiple tasks, and each task contains multiple stages.
C. A stage contains multiple jobs, and each job contains multiple tasks.
D. A stage contains multiple tasks, and each task contains multiple jobs.

Question 5

Given the following code snippet in my_spark_app.py:

What is the role of the driver node?

A. The driver node orchestrates the execution by transforming actions into tasks and distributing them to worker nodes
B. The driver node only provides the user interface for monitoring the application
C. The driver node stores the final result after computations are completed by worker nodes
D. The driver node holds the DataFrame data and performs all computations locally

Solutions: