Practice Graphx Working (high-level Data Flow) (2.5.3) - Cloud Applications: MapReduce, Spark, and Apache Kafka
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GraphX Working (High-level Data Flow)

Practice - GraphX Working (High-level Data Flow)

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Practice Questions

Test your understanding with targeted questions

Question 1 Easy

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

💡 Hint: Think about what represents nodes and connections.

Question 2 Easy

What is a superstep in the Pregel API?

💡 Hint: Consider how messages change the state of vertices.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What does GraphX primarily leverage for graph computations?

Boolean Algebra
Resilient Distributed Datasets
Arrays

💡 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

💡 Hint: Consider what progressively updates the graph.

2 more questions available

Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

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.

💡 Hint: Think about how identifiers work in graphs.

Challenge 2 Hard

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

💡 Hint: Reflect on the features of RDBMS versus NoSQL graphs.

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Reference links

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