Which of the following option is used to create RDD?

PySpark - Quiz(MCQ)

Using join() function

Using filter() function

Using parallel() function

Using parallelize() function

Correct Answer : Using parallelize() function

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____ represents a set of named columns and distributed data.

pyspark.sql.DataFrame

pyspark.sql.Row

pyspark.sql.Column

pyspark.sql.GroupedData

Correct Answer : pyspark.sql.DataFrame

Explanation : pyspark.SQL.DataFrame represents a set of named columns and distributed data.

DataFrame and SQL functionality is accessed through ____.

pyspark.sql.Row

pyspark.sql.Column

pyspark.sql.DataFrame

pyspark.sql.SparkSession

Correct Answer : pyspark.sql.SparkSession

Explanation : DataFrame and SQL functionality are accessed through pyspark.sql.SparkSession.

A UDF extends Spark SQL's DSL vocabulary for transforming DataFrames by defining a new ____-based function.

Tuple

Row

Column

None of the above

Correct Answer : Column

Explaination : A UDF extends Spark SQL's DSL vocabulary for transforming DataFrames by defining a new column-based function.

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