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

1. What is a feature of Spark Connect?

A) It supports DataStreamReader, DataStreamWriter, StreamingQuery, and Streaming APIs
B) It has built-in authentication
C) It supports only PySpark applications
D) Supports DataFrame, Functions, Column, SparkContext PySpark APIs

2. 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) Transformations are executed immediately to build the lineage graph.
C) Transformations are evaluated lazily.
D) Only actions trigger the execution of the transformation pipeline.
E) The Spark engine requires manual intervention to start executing transformations.

3. A data engineer wants to create an external table from a JSON file located at /data/input.json with the following requirements:
Create an external table named users
Automatically infer schema
Merge records with differing schemas
Which code snippet should the engineer use?
Options:

A) CREATE EXTERNAL TABLE users USING json OPTIONS (path '/data/input.json', mergeSchema 'true')
B) CREATE EXTERNAL TABLE users USING json OPTIONS (path '/data/input.json')
C) CREATE TABLE users USING json OPTIONS (path '/data/input.json')
D) CREATE EXTERNAL TABLE users USING json OPTIONS (path '/data/input.json', schemaMerge 'true')

4. A data engineer is running a batch processing job on a Spark cluster with the following configuration:
10 worker nodes
16 CPU cores per worker node
64 GB RAM per node
The data engineer wants to allocate four executors per node, each executor using four cores.
What is the total number of CPU cores used by the application?

A) 160
B) 40
C) 64
D) 80

5. Which feature of Spark Connect is considered when designing an application to enable remote interaction with the Spark cluster?

A) It provides a way to run Spark applications remotely in any programming language
B) It is primarily used for data ingestion into Spark from external sources
C) It can be used to interact with any remote cluster using the REST API
D) It allows for remote execution of Spark jobs

Solutions: