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

1. 54 of 55.
What is the benefit of Adaptive Query Execution (AQE)?

A) It automatically distributes tasks across nodes in the clusters and does not perform runtime adjustments to the query plan.
B) It enables the adjustment of the query plan during runtime, handling skewed data, optimizing join strategies, and improving overall query performance.
C) It optimizes query execution by parallelizing tasks and does not adjust strategies based on runtime metrics like data skew.
D) It allows Spark to optimize the query plan before execution but does not adapt during runtime.

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

3. Given a DataFrame df that has 10 partitions, after running the code:
result = df.coalesce(20)
How many partitions will the result DataFrame have?

A) 20
B) Same number as the cluster executors
C) 10
D) 1

4. 4 of 55.
A developer is working on a Spark application that processes a large dataset using SQL queries. Despite having a large cluster, the developer notices that the job is underutilizing the available resources. Executors remain idle for most of the time, and logs reveal that the number of tasks per stage is very low. The developer suspects that this is causing suboptimal cluster performance.
Which action should the developer take to improve cluster utilization?

A) Enable dynamic resource allocation to scale resources as needed
B) Increase the value of spark.sql.shuffle.partitions
C) Increase the size of the dataset to create more partitions
D) Reduce the value of spark.sql.shuffle.partitions

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

Solutions: