Apache Spark 3 for Data Engineering and Analytics with Python - The Spark Unified Stack

The video introduces Apache Spark as a unified engine for big data processing, highlighting its core components and modules. It covers the Spark Core, which provides essential functionalities for distributed applications, and explores various modules built on top of it, including Spark SQL for structured data, Spark Structured Streaming for real-time data processing, Spark MLib for machine learning, and Spark Graph for graph processing. The video concludes with a summary of Spark's capabilities and a preview of the next lesson on installing Spark locally.

What is the foundational component of the Spark unified stack?

• Spark MLib

• Spark Graph

• Spark Core

• Spark SQL

Which Spark module is designed for handling structured data?

• Spark MLib

• Spark Graph

• Spark SQL

• Spark Streaming

What is the primary function of Spark Structured Streaming?

• To process batch data

• To handle real-time streaming data

• To perform graph processing

• To execute machine learning algorithms

Which module in Spark is used for machine learning tasks?

• Spark Graph

• Spark SQL

• Spark Core

• Spark MLib

What type of data structures does Spark Graph operate on?

• Unstructured data

• Graph data structures

• Tabular data

• Time-series data