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

1. A developer is working with a pandas DataFrame containing user behavior data from a web application.
Which approach should be used for executing agroupByoperation in parallel across all workers in Apache Spark 3.5?
A)
Use the applylnPandas API
B)

C)

D)

A) Use a Pandas UDF:
@pandas_udf("double")
def mean_func(value: pd.Series) -> float:
return value.mean()
df.groupby("user_id").agg(mean_func(df["value"])).show()
B) Use themapInPandasAPI:
df.mapInPandas(mean_func, schema="user_id long, value double").show()
C) Use theapplyInPandasAPI:
df.groupby("user_id").applyInPandas(mean_func, schema="user_id long, value double").show()
D) Use a regular Spark UDF:
from pyspark.sql.functions import mean
df.groupBy("user_id").agg(mean("value")).show()

2. A Spark application is experiencing performance issues in client mode because the driver is resource- constrained.
How should this issue be resolved?

A) Switch the deployment mode to cluster mode
B) Increase the driver memory on the client machine
C) Switch the deployment mode to local mode
D) Add more executor instances to the cluster

3. A developer wants to test Spark Connect with an existing Spark application.
What are the two alternative ways the developer can start a local Spark Connect server without changing their existing application code? (Choose 2 answers)

A) Add.remote("sc://localhost")to their SparkSession.builder calls in their Spark code
B) Ensure the Spark propertyspark.connect.grpc.binding.portis set to 15002 in the application code
C) Execute their pyspark shell with the option--remote "https://localhost"
D) Execute their pyspark shell with the option--remote "sc://localhost"
E) Set the environment variableSPARK_REMOTE="sc://localhost"before starting the pyspark shell

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. How can a Spark developer ensure optimal resource utilization when running Spark jobs in Local Mode for testing?
Options:

A) Configure the application to run in cluster mode instead of local mode.
B) Use the spark.dynamicAllocation.enabled property to scale resources dynamically.
C) Increase the number of local threads based on the number of CPU cores.
D) Set the spark.executor.memory property to a large value.

Solutions: