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Real Time Streaming using Apache Spark Streaming

Features Includes:
  • Self-paced with Life Time Access
  • Certificate on Completion
  • Access on Android and iOS App

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Description

Analyze data in real-time using the Apache Spark Streaming API.

Spark is the technology that allows us to perform big data processing in the MapReduce paradigm very rapidly, due to performing the processing in memory without the need for extensive I/O operations.

Recently, the streaming approach to processing events in near real time became more widely adopted and more necessary. In this course, you will learn how to handle big amount of unbounded infinite streams of data. You will analyze data and draw conclusions from it. Furthermore, we will look at common problems when processing event streams: sorting, watermarks, deduplication, and keeping state (for example, user sessions). You will also implement streaming processing using Spark Streaming and analyze traffic on a web page in real time.

About the Author

  • Tomasz Lelek is a software engineer, programming mostly in Java and Scala. A fan of microservices architecture and functional programming, he has dedicated considerable time and effort to getting better every day and has recently delved into big data technologies such as Apache Spark and Hadoop. He is passionate about nearly everything associated with software development; his belief is that we should always try to consider different solutions and approaches before solving a problem. Recently he was a speaker at conferences in Poland, Confitura, and JDD (Java Developers Day), and also at Krakow Scala User Group. He has also conducted a live coding session at Geecon Conference.JDD.
  • https://www.youtube.com/watch?v=BnORjQbnZNQJDD
  • http://16.jdd.org.pl/program/speakers/lelek-tomasz/Bottega
  • http://bottega.com.pl/warsztat-bigdata-machine-learning

Basic knowledge
  • A basic understanding and functional knowledge of Apache Spark, stream processing, and big data are required

What will you learn
  • Implement stream processing using Apache Spark Streaming
  • Consume events from the source (for instance, Kafka), apply logic on it, and send it to a data sink
  • Understand how to deduplicate events when you have a system that ensures at-least-once deliver
  • Learn to tackle common stream processing problems
  • Create a job to analyze data in real time using the Apache Spark Streaming API
  • Master event time and processing time
  • Single event processing and the micro-batch approach to processing events
  • Learn to sort infinite event streams
Course Curriculum
Number of Lectures: 13 Total Duration: 00:59:38
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