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

2. A data engineer is working on the DataFrame:

(Referring to the table image: it has columnsId,Name,count, andtimestamp.) Which code fragment should the engineer use to extract the unique values in theNamecolumn into an alphabetically ordered list?

A) df.select("Name").orderBy(df["Name"].asc())
B) df.select("Name").distinct()
C) df.select("Name").distinct().orderBy(df["Name"].desc())
D) df.select("Name").distinct().orderBy(df["Name"])

3. A data analyst builds a Spark application to analyze finance data and performs the following operations:filter, select,groupBy, andcoalesce.
Which operation results in a shuffle?

A) coalesce
B) groupBy
C) select
D) filter

4. A data engineer replaces the exact percentile() function with approx_percentile() to improve performance, but the results are drifting too far from expected values.
Which change should be made to solve the issue?

A) Decrease the first value of the percentage parameter to increase the accuracy of the percentile ranges
B) Decrease the value of the accuracy parameter in order to decrease the memory usage but also improve the accuracy
C) Increase the last value of the percentage parameter to increase the accuracy of the percentile ranges
D) Increase the value of the accuracy parameter in order to increase the memory usage but also improve the accuracy

5. A developer needs to produce a Python dictionary using data stored in a small Parquet table, which looks like this:

The resulting Python dictionary must contain a mapping of region-> region id containing the smallest 3 region_idvalues.
Which code fragment meets the requirements?
A)

B)

C)

D)

The resulting Python dictionary must contain a mapping ofregion -> region_idfor the smallest
3region_idvalues.
Which code fragment meets the requirements?

A) regions = dict(
regions_df
.select('region', 'region_id')
.sort('region_id')
.take(3)
)
B) regions = dict(
regions_df
.select('region_id', 'region')
.limit(3)
.collect()
)
C) regions = dict(
regions_df
.select('region_id', 'region')
.sort('region_id')
.take(3)
)
D) regions = dict(
regions_df
.select('region', 'region_id')
.sort(desc('region_id'))
.take(3)
)

Solutions: