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

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

1. 35 of 55.
A data engineer is building a Structured Streaming pipeline and wants it to recover from failures or intentional shutdowns by continuing where it 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 checkpointLocation during readStream.
D) By configuring the option recoveryLocation during SparkSession initialization.

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

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

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

4. A data engineer wants to process a streaming DataFrame that receives sensor readings every second with columns sensor_id, temperature, and timestamp. The engineer needs to calculate the average temperature for each sensor over the last 5 minutes while the data is streaming.
Which code implementation achieves the requirement?
Options from the images provided:

A)

B)

C)

D)

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

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

Solutions: