You say big data, I say Fast data
Nowadays most of the "Big Data" problems are dealing with speed not size. Folks want "Fast Data". Speed is the problem to solve, not size. Most organizations today actually face smaller big data problems that they are trying to address through in-memory cached real-time processing of data. In this presentation we will explore architectures used for solving "Fast Data" problems.
We will be using Spark Streaming and Scala for code examples.
Outline/Structure of the Talk
- Introduction to data streaming landscape
- Types of streaming/fast data/near real time big data problems
- Challenges we face (lambda architecture, reactive streams)
- Spark streaming
- Examples
Learning Outcome
Audience will get exposed to following things
- Fast data problems
- Data streams (working with real time events)
- Tools
- Spark streaming and Scala
Target Audience
developers and architectures
Video
Links
- Reactive Reference architectures - https://www.parleys.com/tutorial/reactive-reference-architecture
- Play recipes - https://www.parleys.com/tutorial/delicious-play-recipes-real-world-akka-slick-ingredients
- Functional IO (JavaZone) - http://vimeo.com/74440529
Naresh Jain
madhavan
Debasish Ghosh
Tejas Dinkar
Bhasker Kode
