About this Course

The world is trending in actual time! Study from Twitter to scalably course of tweets, or any massive knowledge stream, in real-time to drive d3 visualizations utilizing Apache Storm, the “Hadoop of Actual Time.” Storm is free, open supply, and enjoyable to make use of! Study from Karthik Ramasamy, Technical Lead of Storm@Twitter, concerning the distributed, fault-tolerant, and versatile expertise used to energy Twitter’s real-time knowledge stream pipeline. Twitter open sourced Storm in 2011, and it graduated to a top-level Apache venture in September, 2014.

Ranging from fundamental distributed ideas offered throughout our first Udacity-Twitter Storm Hackathon, hyperlink Storm ideas to Storm syntax to scalably drive Phrase Cloud visualizations with Vagrant, Ubuntu, Maven, Flask, Redis, and d3. Hyperlink to the general public Twitter gardenhose stream to course of dwell tweets, parse embedded URLs, and calculate High worldwide hashtags. Prolong past Storm fundamentals by exploring multi-language capabilities in Python, combine open supply parts, and implement real-time streaming joins.

In your last venture, comply with real-time trending subjects by implementing the information pipeline to visualise solely tweets that comprise High worldwide hashtags. Prolong your venture by exploring the Twitter API, or any knowledge supply, alongside Hackathon members as they design their very own concepts, obtain suggestions from Karthik, and open supply a last venture calculating real-time tweet sentiment and geolocation to drive a U.S. Map.

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