Over a million developers have joined DZone.

SpringOne2GX 2014 Replay: Scalable Big Data stream processing with Storm and Groovy

DZone's Guide to

SpringOne2GX 2014 Replay: Scalable Big Data stream processing with Storm and Groovy

· Java Zone ·
Free Resource

Delivering modern software? Atomist automates your software delivery experience.

Speaker: Eugene Dvorkin

More Groovy Track

Slides: http://www.slideshare.net/SpringCentral/storm-twtterwebmd

With advances in distributed computing and creation of frameworks like Storm and Spark, building real-time, fault-tolerant, and scalable solutions to process huge volume of data in real-time has become easy. Storm is one of the most popular framework to develop real-time analytics and event processing applications. Storm enables to tackle real-time Big Data challenges the same way Hadoop enables batch processing of Big Data. One of the use cases of Storm is processing feeds from social networks in real-time. Social networks like Twitter, Facebook, LinkedIn, Google+ became part of our life. By analyzing social networks, companies can process important information about their product, services, and provide real-time information to customers. In this talk, Eugene will provide introduction to Storm framework, explain how to build real-time applications on top of Storm with Groovy, how to process data from Twitter in real-time and architectural decision behind WebMD MedPulse mobile application.

Start automating your delivery right there on your own laptop, today! Get the open source Atomist Software Delivery Machine.


Published at DZone with permission of

Opinions expressed by DZone contributors are their own.

{{ parent.title || parent.header.title}}

{{ parent.tldr }}

{{ parent.urlSource.name }}