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

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

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

2. A data engineer writes the following code to join two DataFrames df1 and df2:
df1 = spark.read.csv("sales_data.csv") # ~10 GB
df2 = spark.read.csv("product_data.csv") # ~8 MB
result = df1.join(df2, df1.product_id == df2.product_id)

Which join strategy will Spark use?

A) Shuffle join because no broadcast hints were provided
B) Shuffle join, as the size difference between df1 and df2 is too large for a broadcast join to work efficiently
C) Shuffle join, because AQE is not enabled, and Spark uses a static query plan
D) Broadcast join, as df2 is smaller than the default broadcast threshold

3. 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?

A) df1.orderBy(col("count").desc(), col("Name").asc())
B) df1.orderBy("Name", "count")
C) df1.sort("Name", "count")
D) df1.orderBy(col("Name").desc(), col("count").asc())

4. 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 recoveryLocation during writeStream
C) By configuring the option recoveryLocation during the SparkSession initialization
D) By configuring the option checkpointLocation during readStream

5. A data engineer needs to write a Streaming DataFrame as Parquet files.
Given the code:

Which code fragment should be inserted to meet the requirement?
A)

B)

C)

D)

Which code fragment should be inserted to meet the requirement?

A) CopyEdit
.option("format", "parquet")
.option("destination", "path/to/destination/dir")
B) .format("parquet")
.option("path", "path/to/destination/dir")
C) .option("format", "parquet")
.option("location", "path/to/destination/dir")
D) .format("parquet")
.option("location", "path/to/destination/dir")

Solutions: