Ioannis Varsamidakis

Final Presentation

??.01.2018

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source: http://www.ncta.com

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source: http://www.vitria.com

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IoT Mashup tool

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akka streams

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akka streams

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Akka

component

Akka Streams

componentAkka

component

Akka Streams

component

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Method Responsiveness Settling time Scalability

No window Very slow Long Low

Tumbling window 50 Very fast Very long Very low

Tumbling window 300 Slow Very short High

Tumbling window 500 Slow None Very high

Sliding window 500 Slow None Very high

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https://mapr.com/ebooks/streaming-architecture/chapter-01-why-event-

streaming.html#ch01[2] Linear Mixed Models, May 2002 – John Fox

https://balamaci.ro/reactive-log-processing/

https://hackhands.com/overview-of-reactive-programming/

https://blog.redelastic.com/a-journey-into-reactive-streams-5ee2a9cd7e29

https://nodered.org/docs/creating-nodes/context

https://gist.github.com/staltz/868e7e9bc2a7b8c1f754

Icons: http://www.flaticon.com/

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akka streams project reactor

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Appendix - Reactive programming

Iterator Pattern (GoF)

(Java) Iterable data type (consistent way to consume all data in a collection).

Consumer -> Producer

(Consumer wants to get the data out of producer)

Producer can:

• Tell no more data

• Throw error

3 semantics:

• Pull data

• Tell no data

• Throw an error

Pull data (out of iterator)

Observable Pattern (GoF)

Producer -> Consumer (Producer gives data to

Consumer)

Producer is in control, decides when to give data to

consumer.

3 semantics:

• Push data

• Complete (no more stream data)

• Throw an error

Push data

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Appendix - Reactive programming

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Appendix - Reactive programming

Reactive Programming = Observable pattern + Iteratable pattern

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The 3 Vs of Big Data

Source: https://www.infoq.com/articles/stream-processing-hadoop

Hadoop:

Volume + Variety

Stream Analytics:

Velocity + Variety

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Source:

https://www.lightbend.com/blog/understanding-

akka-streams-back-pressure-and-asynchronous-

architectures

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Source:

https://www.lightbend.com/blog/understanding-

akka-streams-back-pressure-and-asynchronous-

architectures

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IoT will generate a staggering 400 zettabytes (ZB) of data a year by

2018 - Cisco

source: http://www.vitria.com

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Top open source Stream Analytics platforms

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• Need to be set up

• Need to program them (mostly in Scala or Java)

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