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Udacity

Streaming API Development and Documentation

via Udacity

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Overview

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.

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

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