Apache Spark Spark Core and RDDs

Question 1

What does RDD stand for in Apache Spark?

Accepted Answer

Resilient Distributed Dataset

Answer

RDD stands for Resilient Distributed Dataset, which is the fundamental data structure in Apache Spark.

Question 2

Which of the following is a transformation in Spark RDDs?

Accepted Answer

map()

Answer

map() is a transformation that returns a new RDD, while collect(), count(), and save() are actions.

Question 3

What is the default number of partitions when creating an RDD from a collection using sc.parallelize()?

Accepted Answer

Depends on the SparkContext default parallelism

Answer

By default, sc.parallelize() uses the SparkContext's default parallelism, which is typically the number of cores.

Question 4

Which RDD operation returns all elements of the RDD to the driver program?

Accepted Answer

collect()

Answer

collect() returns all elements of the RDD to the driver program as an array.

Question 5

What does the flatMap() transformation do in Spark?

Accepted Answer

Maps each element to zero or more output elements and flattens the result

Answer

flatMap() applies a function to each element that returns an iterator and flattens all iterators into a single RDD.

Apache Spark Practice Test