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

1. A data scientist is working on a project that requires processing large amounts of structured data, performing SQL queries, and applying machine learning algorithms. The data scientist is considering using Apache Spark for this task.
Which combination of Apache Spark modules should the data scientist use in this scenario?
Options:

A) Spark SQL, Pandas API on Spark, and Structured Streaming
B) Spark Streaming, GraphX, and Pandas API on Spark
C) Spark DataFrames, Structured Streaming, and GraphX
D) Spark DataFrames, Spark SQL, and MLlib

2. 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')
B) CREATE TABLE users USING json OPTIONS (path '/data/input.json')
C) CREATE EXTERNAL TABLE users USING json OPTIONS (path '/data/input.json', schemaMerge 'true')
D) CREATE EXTERNAL TABLE users USING json OPTIONS (path '/data/input.json', mergeSchema 'true')

3. A data engineer is building a Structured Streaming pipeline and wants the pipeline to recover from failures or intentional shutdowns by continuing where the pipeline left off.
How can this be achieved?

A) By configuring the option checkpointLocation during writeStream
B) By configuring the option checkpointLocation during readStream
C) By configuring the option recoveryLocation during the SparkSession initialization
D) By configuring the option recoveryLocation during writeStream

4. What is the relationship between jobs, stages, and tasks during execution in Apache Spark?
Options:

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

5. A data engineer is working on a real-time analytics pipeline using Apache Spark Structured Streaming. The engineer wants to process incoming data and ensure that triggers control when the query is executed. The system needs to process data in micro-batches with a fixed interval of 5 seconds.
Which code snippet the data engineer could use to fulfil this requirement?
A)

B)

C)

D)

Options:

A) Uses trigger() - default micro-batch trigger without interval.
B) Uses trigger(processingTime=5000) - invalid, as processingTime expects a string.
C) Uses trigger(continuous='5 seconds') - continuous processing mode.
D) Uses trigger(processingTime='5 seconds') - correct micro-batch trigger with interval.

Solutions: