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

1. 17 of 55.
A data engineer has noticed that upgrading the Spark version in their applications from Spark 3.0 to Spark 3.5 has improved the runtime of some scheduled Spark applications.
Looking further, the data engineer realizes that Adaptive Query Execution (AQE) is now enabled.
Which operation should AQE be implementing to automatically improve the Spark application performance?

A) Optimizing the layout of Delta files on disk
B) Collecting persistent table statistics and storing them in the metastore for future use
C) Dynamically switching join strategies
D) Improving the performance of single-stage Spark jobs

2. A data engineer is working on a Streaming DataFrame streaming_df with the given streaming data:

Which operation is supported with streamingdf ?

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

3. 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()

4. A Spark developer is building an app to monitor task performance. They need to track the maximum task processing time per worker node and consolidate it on the driver for analysis.
Which technique should be used?

A) Use an accumulator to record the maximum time on the driver
B) Broadcast a variable to share the maximum time among workers
C) Configure the Spark UI to automatically collect maximum times
D) Use an RDD action like reduce() to compute the maximum time

5. What is the risk associated with this operation when converting a large Pandas API on Spark DataFrame back to a Pandas DataFrame?

A) The operation will fail if the Pandas DataFrame exceeds 1000 rows
B) Data will be lost during conversion
C) The operation will load all data into the driver's memory, potentially causing memory overflow
D) The conversion will automatically distribute the data across worker nodes

Solutions: