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

1. 6 of 55.
Which components of Apache Spark's Architecture are responsible for carrying out tasks when assigned to them?

A) Worker Nodes
B) Driver Nodes
C) Executors
D) CPU Cores

2. A data engineer needs to write a DataFrame df to a Parquet file, partitioned by the column country, and overwrite any existing data at the destination path.
Which code should the data engineer use to accomplish this task in Apache Spark?

A) df.write.mode("overwrite").parquet("/data/output")
B) df.write.partitionBy("country").parquet("/data/output")
C) df.write.mode("append").partitionBy("country").parquet("/data/output")
D) df.write.mode("overwrite").partitionBy("country").parquet("/data/output")

3. A data scientist is working on a project that requires processing large amounts of structured data, performing SQL queries, and applying machine learning algorithms. The data scientist is considering using Apache Spark for this task.
Which combination of Apache Spark modules should the data scientist use in this scenario?
Options:

A) Spark SQL, Pandas API on Spark, and Structured Streaming
B) Spark DataFrames, Spark SQL, and MLlib
C) Spark DataFrames, Structured Streaming, and GraphX
D) Spark Streaming, GraphX, and Pandas API on Spark

4. 46 of 55.
A data engineer is implementing a streaming pipeline with watermarking to handle late-arriving records.
The engineer has written the following code:
inputStream \
.withWatermark("event_time", "10 minutes") \
.groupBy(window("event_time", "15 minutes"))
What happens to data that arrives after the watermark threshold?

A) Data arriving more than 10 minutes after the latest watermark will still be included in the aggregation but will be placed into the next window.
B) The watermark ensures that late data arriving within 10 minutes of the latest event time will be processed and included in the windowed aggregation.
C) Records that arrive later than the watermark threshold (10 minutes) will automatically be included in the aggregation if they fall within the 15-minute window.
D) Any data arriving more than 10 minutes after the watermark threshold will be ignored and not included in the aggregation.

5. Which command overwrites an existing JSON file when writing a DataFrame?

A) df.write.mode("overwrite").json("path/to/file")
B) df.write.overwrite.json("path/to/file")
C) df.write.json("path/to/file", overwrite=True)
D) df.write.format("json").save("path/to/file", mode="overwrite")

Solutions: