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

1. 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_spark()
B) psdf.to_pyspark()
C) psdf.to_pandas()
D) psdf.to_dataframe()

2. An engineer wants to join two DataFramesdf1anddf2on the respectiveemployee_idandemp_idcolumns:
df1:employee_id INT,name STRING
df2:emp_id INT,department STRING
The engineer uses:
result = df1.join(df2, df1.employee_id == df2.emp_id, how='inner')
What is the behaviour of the code snippet?

A) The code fails to execute because it must use on='employee_id' to specify the join column explicitly
B) The code fails to execute because PySpark does not support joining DataFrames with a different structure
C) The code works as expected because the join condition explicitly matches employee_id from df1 with emp_id from df2
D) The code fails to execute because the column names employee_id and emp_id do not match automatically

3. A data engineer is working ona Streaming DataFrame streaming_df with the given streaming data:

Which operation is supported with streaming_df?

A) streaming_df.select(countDistinct("Name"))
B) streaming_df.filter(col("count") < 30).show()
C) streaming_df.orderBy("timestamp").limit(4)
D) streaming_df.groupby("Id").count()

4. A developer runs:

What is the result?
Options:

A) It creates separate directories for each unique combination of color and fruit.
B) It stores all data in a single Parquet file.
C) It appends new partitions to an existing Parquet file.
D) It throws an error if there are null values in either partition column.

5. A data engineer uses a broadcast variable to share a DataFrame containing millions of rows across executors for lookup purposes. What will be the outcome?

A) The job may fail because the driver does not have enough CPU cores to serialize the large DataFrame
B) The job may fail if the executors do not have enough CPU cores to process the broadcasted dataset
C) The job may fail if the memory on each executor is not large enough to accommodate the DataFrame being broadcasted
D) The job will hang indefinitely as Spark will struggle to distribute and serialize such a large broadcast variable to all executors

Solutions: