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

1. A data scientist wants each record in the DataFrame to contain:
The first attempt at the code does read the text files but each record contains a single line. This code is shown below:

The entire contents of a file
The full file path
The issue: reading line-by-line rather than full text per file.
Code:
corpus = spark.read.text("/datasets/raw_txt/*") \
.select('*', '_metadata.file_path')
Which change will ensure one record per file?
Options:

A) Add the option wholetext=False to the text() function
B) Add the option wholetext=True to the text() function
C) Add the option lineSep=", " to the text() function
D) Add the option lineSep='\n' to the text() function

2. 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) save with mode Ignore
B) save with mode ErrorIfExists
C) saveAsTable with mode Overwrite
D) saveAsTable with mode ErrorIfExists

3. 36 of 55.
What is the main advantage of partitioning the data when persisting tables?

A) It optimizes by reading only the relevant subset of data from fewer partitions.
B) It automatically cleans up unused partitions to optimize storage.
C) It ensures that data is loaded into memory all at once for faster query execution.
D) It compresses the data to save disk space.

4. A data engineer is asked to build an ingestion pipeline for a set of Parquet files delivered by an upstream team on a nightly basis. The data is stored in a directory structure with a base path of "/path/events/data". The upstream team drops daily data into the underlying subdirectories following the convention year/month/day.
A few examples of the directory structure are:

Which of the following code snippets will read all the data within the directory structure?

A) df = spark.read.parquet("/path/events/data/*")
B) df = spark.read.parquet("/path/events/data/")
C) df = spark.read.option("recursiveFileLookup", "true").parquet("/path/events/data/")
D) df = spark.read.option("inferSchema", "true").parquet("/path/events/data/")

5. What is a feature of Spark Connect?

A) It supports only PySpark applications
B) Supports DataFrame, Functions, Column, SparkContext PySpark APIs
C) It has built-in authentication
D) It supports DataStreamReader, DataStreamWriter, StreamingQuery, and Streaming APIs

Solutions: