About this video

Spark Streaming is becoming incredibly popular, and with good reason. According to IBM, 90% of the data in the World today was created in the last two years alone. Our current output of data is roughly 2.5 quintillion bytes per day. The World is being immersed in data, more so each and every day. As such, analyzing static DataFrames for non-dynamic data is becoming less and less of a practical approach to more and more problems. This is where data streaming comes in, the ability to process data almost as soon as it's produced, recognizing the time-dependency of the data. Apache Spark Streaming gives us an unlimited ability to build cutting-edge applications. It is also one of the most compelling technologies of the last decade in terms of its disruption in the big data world. Spark provides in-memory cluster computing, which greatly boosts the speed of iterative algorithms and interactive data mining tasks. Spark also is a powerful engine for streaming data as well as processing it. The synergy between them makes Spark an ideal tool for processing gargantuan data fire hoses. Tons of companies, including Fortune 500 companies, are adapting Apache Spark Streaming to extract meaning from massive data streams; today, you have access to that same big data technology right on your desktop. This Apache Spark Streaming course is taught in Python. Python is currently one of the most popular programming languages in the World! Its rich data community, offering vast amounts of toolkits and features, makes it a powerful tool for data processing. Using PySpark (the Python API for Spark), you will be able to interact with Apache Spark Streaming's main abstraction, RDDs, as well as other Spark components, such as Spark SQL and much more! Let's learn how to write Apache Spark Streaming programs with PySpark Streaming to process big data sources today!

Style and Approach

This course covers all the fundamentals of Apache Spark Streaming with Python and teaches you everything you need to know about developing Spark Streaming applications using PySpark, the Python API for Spark. By the end of this course, you will have gained in-depth knowledge about Spark Streaming and general big data manipulation skills, to help your company adapt Spark Streaming and build big data processing pipelines and data analytics applications.

Publication date:
September 2018
3 hours 24 minutes

About the Authors

  • James Lee

    James Lee is a passionate software wizard working at one of the top Silicon Valley-based start-ups specializing in big data analysis. He has also worked at Google and Amazon. In his day job, he works with big data technologies, including Cassandra and Elasticsearch, and is an absolute Docker geek and IntelliJ IDEA lover. Apart from his career as a software engineer, he is keen on sharing his knowledge with others and guiding them, especially in relation to start-ups and programming. He has been teaching courses and conducting workshops on Java programming / IntelliJ IDEA since he was 21. James also enjoys skiing and swimming, and is a passionate traveler.

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  • Matthew P. McAteer

    Matthew P. McAteer is a data engineer who loves finding solutions to data analysis problems (which turns out to be most problems). After graduating from Brown University, he applied the skills gained from years in genomics and neurology research to machine learning and data science. In his spare time, he is involved in the DIY synthetic biology movement, and he has written scripts for algorithmic trading and game-playing bots. In Level up, they aim to teach technology the way it is used in the industrial world. The Level up Big Data program is established to deliver high-quality data analytics courses from industry experts and influencers.

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  • Tao W.

    Tao W. is a passionate software engineer who works in a leading big data analysis company in Silicon Valley. Previously Tao worked in big IT companies such as IBM and Cisco. Tao has a MS degree in Computer Science from University of McGill and many years of experience as a teaching assistant for various computer science classes. When Tao is not working, Tao enjoys reading and swimming, and he is a passionate photographer. In Level up, they aim to teach technology the way it is used in the industrial world. The Level up Big Data program is established to deliver high-quality data analytics courses from industry experts and influencers. Level UP was founded by James Lee and Tao W.

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