PySpark and AWS: Master Big Data with PySpark and AWS - RDD (Count and CountByValue)

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Information Technology (IT), Architecture
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7 questions
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1.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is the primary purpose of the 'collect' action in Spark RDD?
To count the number of elements
To collapse the data
To trigger all transformations and return the final output
To repartition the data
2.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Which action in Spark RDD returns the number of elements present in an RDD?
collect
repartition
count
collapse
3.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is the syntax for using the 'count' action in Spark RDD?
RDD.repartition()
RDD.count()
RDD.collapse()
RDD.collect()
4.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
How does the 'count by value' action differ from 'reduce by key'?
It provides the count of each unique value
It reduces the data by a specific key
It groups the data by a specific key
It collapses the data
5.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What does the 'count by value' action return?
The collapsed data
The repartitioned data
The count of each unique value in the RDD
The total number of elements
6.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
In what scenario might you choose to use transformations over actions in Spark RDD?
When you need to count the number of elements
When you want to minimize the use of actions
When you need to collapse the data
When you want to trigger all transformations
7.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What flexibility does Spark RDD offer when working with data?
It mandates the use of 'count by value'
It allows only actions to be used
It restricts the use of transformations
It offers a choice between using transformations and actions based on requirements
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