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SkillsCast

Distributed Real-Time Stream Processing: Why and How

10th December 2015 in London at Business Design Centre

There are 36 other SkillsCasts available from Scala eXchange 2015

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In this talk you will discover various state-of-the-art open-source distributed streaming frameworks, their similarities and differences, implementation trade-offs, their intended use-cases, and how to choose between them. Petr will focus on the popular frameworks, including Spark Streaming, Storm, Samza and Flink. You will also explore theoretical introduction, common pitfalls, popular architectures, and much more. 

The demand for stream processing is increasing. Immense amounts of data has to be processed fast from a rapidly growing set of disparate data sources. This pushes the limits of traditional data processing infrastructures. These stream-based applications, include trading, social networks, the Internet of Things, and system monitoring, are becoming more and more important. A number of powerful, easy-to-use open source platforms have emerged to address this.

Petr's goal is to provide a comprehensive overview of modern streaming solutions and to help fellow developers with picking the best possible solution for their particular use-case. Join this talk if you are thinking about, implementing, or have already deployed a streaming solution.

Have a look at Spark Streaming, Storm, Samza, and Flink.

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Distributed Real-Time Stream Processing: Why and How

Petr Zapletal

Petr is a Consultant who specializes in the design and implementation of highly scaleable, reactive and resilient distributed systems. He is a functional programming and open source enthusiast and has expertise in the area of big data and machine classification techniques.

SkillsCast

Please log in to watch this conference skillscast.

Https s3.amazonaws.com prod.tracker2 resource 41088130 skillsmatter conference skillscast o9nohu

In this talk you will discover various state-of-the-art open-source distributed streaming frameworks, their similarities and differences, implementation trade-offs, their intended use-cases, and how to choose between them. Petr will focus on the popular frameworks, including Spark Streaming, Storm, Samza and Flink. You will also explore theoretical introduction, common pitfalls, popular architectures, and much more. 

The demand for stream processing is increasing. Immense amounts of data has to be processed fast from a rapidly growing set of disparate data sources. This pushes the limits of traditional data processing infrastructures. These stream-based applications, include trading, social networks, the Internet of Things, and system monitoring, are becoming more and more important. A number of powerful, easy-to-use open source platforms have emerged to address this.

Petr's goal is to provide a comprehensive overview of modern streaming solutions and to help fellow developers with picking the best possible solution for their particular use-case. Join this talk if you are thinking about, implementing, or have already deployed a streaming solution.

Have a look at Spark Streaming, Storm, Samza, and Flink.

YOU MAY ALSO LIKE:

About the Speaker

Distributed Real-Time Stream Processing: Why and How

Petr Zapletal

Petr is a Consultant who specializes in the design and implementation of highly scaleable, reactive and resilient distributed systems. He is a functional programming and open source enthusiast and has expertise in the area of big data and machine classification techniques.

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