PySpark and AWS: Master Big Data with PySpark and AWS - Spark Architecture and Ecosystem

The video provides an overview of Spark architecture and ecosystem. It explains the components of Spark architecture, including the driver node, cluster manager, and worker nodes, highlighting their roles in distributed computing. The Spark ecosystem is introduced, emphasizing its core APIs and compatibility with multiple programming languages like Scala, Java, Python, and R. The video also covers important Spark libraries such as Spark SQL, Spark Streaming, MLlib, and GraphX, which enhance data processing capabilities. The video concludes with encouragement for hands-on practice to deepen understanding.

What is the significance of Spark's core APIs?

List and explain at least two libraries provided by Spark for enhanced functionality.

How does Spark Streaming differ from traditional batch processing?