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

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

· Java Zone ·
Free Resource

Verify, standardize, and correct the Big 4 + more– name, email, phone and global addresses – try our Data Quality APIs now at Melissa Developer Portal!

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.

Developers! Quickly and easily gain access to the tools and information you need! Explore, test and combine our data quality APIs at Melissa Developer Portal – home to tools that save time and boost revenue. Our APIs verify, standardize, and correct the Big 4 + more – name, email, phone and global addresses – to ensure accurate delivery, prevent blacklisting and identify risks in real-time.

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