Analyzing data used to be something you did once a night. Now you need to be able to process data on the fly so you can provide up to the minute insights. But, how do you accomplish in real time what used to take hours without a complicated code base? In this course, Handling Fast Data with Apache Spark SQL and Streaming, you’ll learn to use Apache Spark Streaming and SQL libraries as a great way to handle this new world of real time, fast data processing. First, you’ll dive into SparkSQL. Next, you’ll explore how to catch potential fraud by analyzing streams with Spark Streaming. Finally, you’ll discover the newer Structured Streaming API. By the end of this course, you’ll have a deeper understanding of these APIs, along with a number of streaming concepts that have driven the API design.
Author Name: Justin Pihony
Author Description:
Justin is a software journeyman, continuously learning and honing his skills. Most of his early professional career was spent in C# and MSSQL, but he loves learning about many different languages, especially Scala. This passion for Scala led him to join the Lightbend (formerly Typesafe) team, diving even deeper into the Scala ecosphere. And, as much as he loves to learn, he also loves to spread his knowledge through teaching and helping others. He is a very active answerer on StackOverflow… more

Table of Contents

• Course Overview
  2mins
• Introduction
  21mins
• Querying Data with the DataFrames (Part 1)
  43mins
• Querying Data with the DataFrames (Part 2)
  41mins
• Improving Type Safety with Datasets
  41mins
• Processing Data with the Streaming API
  67mins
• Optimizing, Structured Streaming, and Spark 2.x
  58mins