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, Scala. He is a fan of microservices architecture, and functional programming. He has dedicated considerable time and effort to be better every day. He recently dived into Big Data technologies such as Apache Spark and Hadoop. Tomasz is passionate about nearly everything associated with software development.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.
In this video, we will explore the Spark-Streaming Architecture and API
In this video, we will see how to create a project in Spark streaming
In this video, we will see how to implement testing
In this video, we will summarize all the topics covered in this course.
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