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Databricks Certified Associate Developer for Apache Spark 3.5 - Python Sample Questions (Q32-Q37):
NEW QUESTION # 32
A developer initializes a SparkSession:
spark = SparkSession.builder
.appName("Analytics Application")
.getOrCreate()
Which statement describes the spark SparkSession?
Answer: D
Explanation:
According to the PySpark API documentation:
"getOrCreate(): Gets an existing SparkSession or, if there is no existing one, creates a new one based on the options set in this builder." This means Spark maintains a global singleton session within a JVM process. Repeated calls to getOrCreate() return the same session, unless explicitly stopped.
Option A is incorrect: the method does not destroy any session.
Option B incorrectly ties uniqueness to appName, which does not influence session reusability.
Option D is incorrect: it contradicts the fundamental behavior of getOrCreate().
(Source: PySpark SparkSession API Docs)
NEW QUESTION # 33
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:
Answer: A
Explanation:
To read each file as a single record, use:
spark.read.text(path, wholetext=True)
This ensures that Spark reads the entire file contents into one row.
Reference:Spark read.text() with wholetext
NEW QUESTION # 34
A data engineer wants to create a Streaming DataFrame that reads from a Kafka topic called feed.
Which code fragment should be inserted in line 5 to meet the requirement?
Code context:
spark
.readStream
.format("kafka")
.option("kafka.bootstrap.servers","host1:port1,host2:port2")
.[LINE5]
.load()
Options:
Answer: A
Explanation:
Comprehensive and Detailed Explanation:
To read from a specific Kafka topic using Structured Streaming, the correct syntax is:
python
CopyEdit
option("subscribe","feed")
This is explicitly defined in the Spark documentation:
"subscribe - The Kafka topic to subscribe to. Only one topic can be specified for this option." (Source:Apache Spark Structured Streaming + Kafka Integration Guide)
B)."subscribe.topic" is invalid.
C)."kafka.topic" is not a recognized option.
D)."topic" is not valid for Kafka source in Spark.
NEW QUESTION # 35
A Data Analyst is working on the DataFrame sensor_df, which contains two columns:
Which code fragment returns a DataFrame that splits the record column into separate columns and has one array item per row?
A)
B)
C)
D)
Answer: D
Explanation:
To flatten an array of structs into individual rows and access fields within each struct, you must:
Use explode() to expand the array so each struct becomes its own row.
Access the struct fields via dot notation (e.g., record_exploded.sensor_id).
Option C does exactly that:
First, explode the record array column into a new column record_exploded.
Then, access fields of the struct using the dot syntax in select.
This is standard practice in PySpark for nested data transformation.
Final answer: C
NEW QUESTION # 36
A Spark application suffers from too many small tasks due to excessive partitioning. How can this be fixed without a full shuffle?
Options:
Answer: C
Explanation:
coalesce(n) reduces the number of partitions without triggering a full shuffle, unlike repartition().
This is ideal when reducing partition count, especially during write operations.
NEW QUESTION # 37
......
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