Apache Spark Certification Practice Test

Multi RDD transformations in Apache Spark refer to operations that combine or manipulate multiple RDDs (Resilient Distributed Datasets) to produce a new RDD. The correct choice highlights transformations that operate on more than one RDD and the results reflect the interaction of these datasets.

Union, intersect, and subtract are classic examples of multi RDD transformations. Union combines the elements of two or more RDDs, creating a new RDD containing all elements from the involved RDDs. Intersect finds common elements between multiple RDDs, producing an RDD with those shared entries. Subtract removes elements of one RDD from another, resulting in an RDD that has the remainder after the specified removal.

In contrast, the other options present operations that do not qualify as multi RDD transformations. The map, flatMap, and filter operations focus solely on processing single RDDs, applying functions to the data contained within without forming relationships with other RDDs. ReduceByKey, collect, and count also operate within the scope of individual RDDs, where they aggregate or gather information based on their contents, rather than combining multiple RDDs.