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Presented by Twitter's Karthik Ramasamy, learn the theory and motivation of Storm, including Stream vs. Batch processing, and real-time Big Data lessons learned at Twitter. Continue on linking Storm Concepts to Storm Syntax with basic setup using Vagrant and VirtualBox to explore Storm Topologies to drive real-time visualizations using d3 (Data Driven Documents).
Program the basics of Storm, including Bolts, Spouts, and basic Topologies. Obtain Twitter OAuth credentials to link to the real-time Twitter Sample Stream to drive Word Cloud visualizations using d3.
Move beyond Storm basics with intermediate concepts exploring multi-language capabilities using Python, open source bolts to calculate Top-N hashtags, and streaming joins to dynamically process tuples from different sources.
Design a Storm Topology and implement a new bolt that uses streaming joins to dynamically calculate Top-N Hashtags and display real-time tweets that contain trending Top Hashtags. Work alongside our Udacity-Twitter Hackathon participants as their final project questions are fielded by Karthik. Post your visualization to the forum and tweet them to your Twitter followers. Extend your project to use additional features of the real-time Twitter sample stream or use any data source to drive your real-time d3 visualization.
Special thanks to Karthik Ramasamy, Chris Kellogg, and Vikas Rameshkedigehalli of Twitter, along with Jorge Herrera and Hyung-Suk Kim of Stanford University for help and support throughout this course.