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

1. A Spark application developer wants to identify which operations cause shuffling, leading to a new stage in the Spark execution plan.
Which operation results in a shuffle and a new stage?

A) DataFrame.select()
B) DataFrame.filter()
C) DataFrame.withColumn()
D) DataFrame.groupBy().agg()

2. 13 of 55.
A developer needs to produce a Python dictionary using data stored in a small Parquet table, which looks like this:
region_id
region_name
10
North
12
East
14
West
The resulting Python dictionary must contain a mapping of region_id to region_name, containing the smallest 3 region_id values.
Which code fragment meets the requirements?

A) regions_dict = regions.select("region_id", "region_name").take(3)
B) regions_dict = dict(regions.select("region_id", "region_name").rdd.collect())
C) regions_dict = dict(regions.orderBy("region_id").limit(3).rdd.map(lambda x: (x.region_id, x.region_name)).collect())
D) regions_dict = dict(regions.take(3))

3. 23 of 55.
A data scientist is working with a massive dataset that exceeds the memory capacity of a single machine. The data scientist is considering using Apache Spark™ instead of traditional single-machine languages like standard Python scripts.
Which two advantages does Apache Spark™ offer over a normal single-machine language in this scenario? (Choose 2 answers)

A) It processes data solely on disk storage, reducing the need for memory resources.
B) It requires specialized hardware to run, making it unsuitable for commodity hardware clusters.
C) It has built-in fault tolerance, allowing it to recover seamlessly from node failures during computation.
D) It can distribute data processing tasks across a cluster of machines, enabling horizontal scalability.
E) It eliminates the need to write any code, automatically handling all data processing.

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

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

5. A developer initializes a SparkSession:

spark = SparkSession.builder \
.appName("Analytics Application") \
.getOrCreate()
Which statement describes the spark SparkSession?

A) A new SparkSession is created every time the getOrCreate() method is invoked.
B) If a SparkSession already exists, this code will return the existing session instead of creating a new one.
C) A SparkSession is unique for each appName, and calling getOrCreate() with the same name will return an existing SparkSession once it has been created.
D) The getOrCreate() method explicitly destroys any existing SparkSession and creates a new one.

Solutions: