What is a feature of Spark Connect?

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

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A developer wants to test Spark Connect with an existing Spark application.
What are the two alternative ways the developer can start a local Spark Connect server without changing their existing application code? (Choose 2 answers)

• A.Execute their pyspark shell with the option --remote "https://localhost"
• B.Execute their pyspark shell with the option --remote "sc://localhost"
• C.Set the environment variable SPARK_REMOTE="sc://localhost" before starting the pyspark shell
• D.Add .remote("sc://localhost") to their SparkSession.builder calls in their Spark code
• E.Ensure the Spark property spark.connect.grpc.binding.port is set to 15002 in the application code

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41 of 55.
A data engineer is working on the DataFrame df1 and wants the Name with the highest count to appear first (descending order by count), followed by the next highest, and so on.
The DataFrame has columns:
id | Name | count | timestamp
---------------------------------
1 | USA | 10
2 | India | 20
3 | England | 50
4 | India | 50
5 | France | 20
6 | India | 10
7 | USA | 30
8 | USA | 40
Which code fragment should the engineer use to sort the data in the Name and count columns?

• A.df1.orderBy(col("count").desc(), col("Name").asc())
• B.df1.sort("Name", "count")
• C.df1.orderBy("Name", "count")
• D.df1.orderBy(col("Name").desc(), col("count").asc())

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16 of 55.
A data engineer is reviewing a Spark application that applies several transformations to a DataFrame but notices that the job does not start executing immediately.
Which two characteristics of Apache Spark's execution model explain this behavior? (Choose 2 answers)

• A.Transformations are executed immediately to build the lineage graph.
• B.The Spark engine optimizes the execution plan during the transformations, causing delays.
• C.Transformations are evaluated lazily.
• D.The Spark engine requires manual intervention to start executing transformations.
• E.Only actions trigger the execution of the transformation pipeline.

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A data engineer is reviewing a Spark application that applies several transformations to a DataFrame but notices that the job does not start executing immediately.
Which two characteristics of Apache Spark's execution model explain this behavior?
Choose 2 answers:

• A.The Spark engine requires manual intervention to start executing transformations.
• B.Only actions trigger the execution of the transformation pipeline.
• C.Transformations are executed immediately to build the lineage graph.
• D.The Spark engine optimizes the execution plan during the transformations, causing delays.
• E.Transformations are evaluated lazily.

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