PySpark and AWS: Master Big Data with PySpark and AWS - Spark Streaming Context

The video tutorial explains how to specify directories in Spark Streaming, set up the Spark Streaming Context, and manage data streams. It covers the importance of using directories for input, starting the streaming context, and handling data streams with transformations. The tutorial also discusses termination conditions and provides a brief overview of the next steps in the series.

What is the significance of specifying the directory in Spark Streaming?

How does Spark Streaming handle files that are added to the specified directory?

Explain the purpose of 'awaitTermination' in Spark Streaming.

What is the difference between RDD and DStream in Spark Streaming?

What actions can be performed on DStreams in Spark Streaming?

How can you manually stop a Spark Streaming job?

What happens if no input files are received within the specified timeout in Spark Streaming?