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

Real-time stream processing of graph data

Answer

Machine learning on tabular datasets

Answer

SQL queries on graph databases

Question 2

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

Accepted Answer

Vertices and Edges

Answer

Edges and Paths

Answer

Nodes and Relationships

Answer

Rows and Columns

Question 3

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

Accepted Answer

Long (64-bit integer)

Answer

String

Answer

UUID

Answer

Integer (32-bit)

Question 4

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

Accepted Answer

VertexRDD

Answer

DataFrame

Answer

HashSet

Answer

DenseVector

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.fromVertices()

Answer

Graph.apply()

Answer

Graph.edgeListFile()

Question 6

What does the `triplets` property of a GraphX Graph return?

Accepted Answer

An RDD of EdgeTriplet objects containing source vertex, edge, and destination vertex attributes

Answer

Three separate RDDs for source, edge, and destination

Answer

A tuple of (VertexRDD, EdgeRDD, PartitionRDD)

Answer

An array of three graphs representing different structural views

Question 7

Which GraphX edge partitioning strategy assigns edges to partitions based solely on the source vertex ID?

Accepted Answer

EdgePartition1D

Answer

RandomVertexCut

Answer

CanonicalRandomVertexCut

Answer

EdgePartition2D