In this course you will grow your expertise in the components of streaming data systems, and build a real
time analytics application. Specifically, you will be able to identify components of Spark Streaming (architecture
and API), build a continuous application with Structured Streaming, consume and process data from Apache
Kafka with Spark Structured Streaming (including setting up and running a Spark Cluster), create a DataFrame
as an aggregation of source DataFrames, sink a composite DataFrame to Kafka, and visually inspect a data sink
for accuracy.
Overview
Syllabus
- Welcome
- Introduction to Data Streaming with Spark
- Streaming Dataframes, Views, and Spark SQL
- In this lesson, you'll learn about working with Spark Dataframes and views.
- Joins and JSON
- In this lesson, you'll learn how to work with JSON and complete Joins for data streaming.
- Redis, Base64 and JSON
- This lesson will focus on working with Redis, Base64, and JSON in Data Streaming.
- Evaluate Human Balance with Spark Streaming
- As your final project for this course, you will demonstrate the skills you have learned by evaluating human balance with spark streaming.
Taught by
Sean Murdock
