Apache Spark GraphX and Graph Processing

Question 1

What is Apache Spark GraphX primarily used for?

Accepted Answer

Graph-parallel computation and graph analytics

Answer

GraphX is Spark's API for graph-parallel computation, enabling graph creation, transformation, and execution of graph algorithms at scale.

Question 2

In GraphX, what are the two fundamental components of a Property Graph?

Accepted Answer

Vertices and Edges

Answer

A Property Graph in GraphX consists of vertices (nodes) and edges (connections), each carrying associated user-defined properties.

Question 3

Which data type is used as a vertex identifier (VertexId) in GraphX?

Accepted Answer

Long (64-bit integer)

Answer

GraphX defines VertexId as a type alias for Long, providing a large namespace of unique IDs suitable for billions of vertices.

Question 4

What distributed collection type does GraphX use internally to store vertex attributes?

Accepted Answer

VertexRDD

Answer

GraphX uses VertexRDD[VD], which extends RDD[(VertexId, VD)], to store and index vertex attributes as key-value pairs.

Question 5

What method in GraphX creates a graph from an RDD of edges, assigning a default attribute to all vertices?

Accepted Answer

Graph.fromEdges()

Answer

Graph.fromEdges() constructs a graph from an RDD[Edge[ED]] and automatically creates vertex entries with a supplied default attribute.

Apache Spark Practice Test