Scala & Spark-Master Big Data with Scala and Spark - Spark Architecture

The video provides an overview of Spark architecture, focusing on the Spark context, driver node, and cluster manager. It explains how tasks are distributed among worker nodes and how data is communicated back to the Spark context for final output. The video aims to build understanding and interest in Spark's distributed behavior.

What is the primary function of the driver node in Spark architecture?

• To manage network connections

• To handle user inputs

• To execute the main code

• To store data

Which component is responsible for distributing tasks among worker nodes in Spark?

• Spark context

• Driver node

• Data node

• Cluster manager

How does the cluster manager decide which worker node to assign a task?

• Alphabetically by node name

• Randomly

• By the size of the task

• Based on the worker node's availability

What happens after a worker node completes its task in Spark?

• It sends the data back to the cluster manager

• It shuts down

• It deletes the data

• It waits for further instructions

In Spark architecture, what is the final step after data is processed by worker nodes?

• Data is sent to another worker node

• Data is discarded

• Data is stored in a database

• Data is communicated back to the Spark context