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What is a DataFrame in Apache Spark?
A distributed collection of data organized into named columns.
A static data structure that cannot be modified.
A type of RDD (Resilient Distributed Dataset).
A table-like structure that supports complex data types.
Which of the following operations can be performed on a DataFrame?
Filtering data using the filter() method.
Grouping data using the groupBy() method.
Joining two DataFrames using the join() method.
Creating a DataFrame from an RDD using toDF().
What is the primary advantage of using DataFrames over RDDs?
DataFrames provide a higher-level abstraction.
DataFrames are always faster than RDDs.
DataFrames support a richer set of operations.
DataFrames can automatically optimize queries.
Which of the following languages can be used to work with DataFrames in Apache Spark?
Python
Java
Scala
R
What is the purpose of the schema in a DataFrame?
To define the structure of the DataFrame.
To enforce data types on each column.
To provide metadata about the DataFrame.
To optimize the execution plan.
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8 Modules