Practice GraphX Working (High-level Data Flow) - 2.5.3 | Week 8: Cloud Applications: MapReduce, Spark, and Apache Kafka | Distributed and Cloud Systems Micro Specialization
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2.5.3 - GraphX Working (High-level Data Flow)

Learning

Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

What are the two main RDDs used for constructing a graph in GraphX?

πŸ’‘ Hint: Think about what represents nodes and connections.

Question 2

Easy

What is a superstep in the Pregel API?

πŸ’‘ Hint: Consider how messages change the state of vertices.

Practice 4 more questions and get performance evaluation

Interactive Quizzes

Engage in quick quizzes to reinforce what you've learned and check your comprehension.

Question 1

What does GraphX primarily leverage for graph computations?

  • Boolean Algebra
  • Resilient Distributed Datasets
  • Arrays

πŸ’‘ Hint: Think about the foundational data structures in Spark.

Question 2

Is it true that a superstep allows vertices to send messages to their neighbors?

  • True
  • False

πŸ’‘ Hint: Consider what progressively updates the graph.

Solve 2 more questions and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

Given a directed graph with 4 vertices and 3 edges represented in GraphX, how would you construct the VertexRDD and EdgeRDD? Describe the process and its implications.

πŸ’‘ Hint: Think about how identifiers work in graphs.

Question 2

Critique the trade-offs of using GraphX for complex graph queries compared to a traditional RDBMS graph store. What are your thoughts?

πŸ’‘ Hint: Reflect on the features of RDBMS versus NoSQL graphs.

Challenge and get performance evaluation