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Databricks Associate-Developer-Apache-Spark-3.5 Exam Syllabus Topics:

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

1. A data engineer wants to write a Spark job that creates a new managed table. If the table already exists, the job should fail and not modify anything.
Which save mode and method should be used?

A) saveAsTable with mode ErrorIfExists
B) save with mode ErrorIfExists
C) saveAsTable with mode Overwrite
D) save with mode Ignore

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) Broadcast join, as df2 is smaller than the default broadcast threshold
C) Shuffle join, as the size difference between df1 and df2 is too large for a broadcast join to work efficiently
D) Shuffle join, because AQE is not enabled, and Spark uses a static query plan

3. A data engineer is streaming data from Kafka and requires:
Minimal latency
Exactly-once processing guarantees
Which trigger mode should be used?

A) .trigger(availableNow=True)
B) .trigger(continuous=True)
C) .trigger(processingTime='1 second')
D) .trigger(continuous='1 second')

4. 29 of 55.
A Spark application is experiencing performance issues in client mode due to the driver being 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) Add more executor instances to the cluster.
D) Switch the deployment mode to local mode.

5. Given:
python
CopyEdit
spark.sparkContext.setLogLevel("<LOG_LEVEL>")
Which set contains the suitable configuration settings for Spark driver LOG_LEVELs?

A) ALL, DEBUG, FAIL, INFO
B) ERROR, WARN, TRACE, OFF
C) FATAL, NONE, INFO, DEBUG
D) WARN, NONE, ERROR, FATAL

Solutions: