Streaming Big Data with Spark Streaming, Scala, and Spark 3

Preview this course

In this course, we will process massive streams of real-time data using Spark Streaming and create Spark applications using the Scala programming language (v2.12). We will also get our hands-on with some real live Twitter data, simulated streams of Apache access logs, and even data used to train machine learning models.

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44 on-demand videos & exercises
Level: Beginner
6hrs 21mins
Access on mobile, web and TV

What to know about this course

In this course, you will learn the basics of the Scala programming language; learn how Apache Spark operates on a cluster; set up discretized streams with Spark Streaming and transform them as data is received; analyze streaming data over sliding windows of time; maintain stateful information across streams of data; connect Spark Streaming with highly scalable sources of data, including Kafka, Flume, and Kinesis; dump streams of data in real-time to NoSQL databases such as Cassandra; run SQL queries on streamed data in real-time; train machine learning models in real-time with streaming data, and use them to make predictions that keep getting better over time; and also, package, deploy, and run self-contained Spark Streaming code to a real Hadoop cluster using Amazon Elastic MapReduce. This course is very hands-on, filled with achievable activities and exercises to reinforce your learning. By the end of this course, you will be confidently creating Spark Streaming scripts in Scala and be prepared to tackle massive streams of data in a whole new way. You will be surprised at how easy Spark Streaming makes it! 

Who's this course for?

If you are a student who wants to learn how to use Apache Spark or a big data professional who wants to process large amounts of data on a real-time basis, this course is for you.

Some basic programming and scripting experience is required to get the most out of the course.

What you'll learn

  • Process large amounts of real-time data using the Spark Streaming module
  • Create efficient Spark applications using the Scala programming language
  • Integrate Spark Streaming with various data sources
  • Integrate Spark Streaming with Spark SQL to query your data in real time
  • Train machine learning models with streaming data, and use for real-time predictions
  • Maintain stateful data across a continuous stream of input data.

Key Features

  • Process streams of real-time data from various sources with Spark Streaming.
  • Query your streaming data in real-time using Spark SQL.
  • A comprehensive tutorial with practical examples to help you develop real-time Spark applications.

Course Curriculum

About the Author

Frank Kane

Frank Kane has spent nine years at Amazon and IMDb, developing and managing the technology that automatically delivers product and movie recommendations to hundreds of millions of customers all the time. He holds 17 issued patents in the fields of distributed computing, data mining, and machine learning. In 2012, Frank left to start his own successful company, Sundog Software, which focuses on virtual reality environment technology and teaches others about big data analysis.

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