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

1. 24 of 55.
Which code should be used to display the schema of the Parquet file stored in the location events.parquet?

A) spark.sql("SELECT * FROM events.parquet").show()
B) spark.sql("SELECT schema FROM events.parquet").show()
C) spark.read.parquet("events.parquet").printSchema()
D) spark.read.format("parquet").load("events.parquet").show()

2. Given the code fragment:

import pyspark.pandas as ps
psdf = ps.DataFrame({'col1': [1, 2], 'col2': [3, 4]})
Which method is used to convert a Pandas API on Spark DataFrame (pyspark.pandas.DataFrame) into a standard PySpark DataFrame (pyspark.sql.DataFrame)?

A) psdf.to_pandas()
B) psdf.to_spark()
C) psdf.to_pyspark()
D) psdf.to_dataframe()

3. A Spark DataFrame df is cached using the MEMORY_AND_DISK storage level, but the DataFrame is too large to fit entirely in memory.
What is the likely behavior when Spark runs out of memory to store the DataFrame?

A) Spark stores the frequently accessed rows in memory and less frequently accessed rows on disk, utilizing both resources to offer balanced performance.
B) Spark splits the DataFrame evenly between memory and disk, ensuring balanced storage utilization.
C) Spark duplicates the DataFrame in both memory and disk. If it doesn't fit in memory, the DataFrame is stored and retrieved from the disk entirely.
D) Spark will store as much data as possible in memory and spill the rest to disk when memory is full, continuing processing with performance overhead.

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

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

5. A data engineer is building a Structured Streaming pipeline and wants the pipeline to recover from failures or intentional shutdowns by continuing where the pipeline left off.
How can this be achieved?

A) By configuring the option recoveryLocation during the SparkSession initialization
B) By configuring the option checkpointLocation during writeStream
C) By configuring the option checkpointLocation during readStream
D) By configuring the option recoveryLocation during writeStream

Solutions: