Real-Time Analytics with Apache Storm
list 2 séquences
assignment Niveau : Introductif
chat_bubble_outline Langue : Anglais
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Les infos clés

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En résumé

The world is trending in real time! Learn from Twitter to scalably process tweets, or any big data stream, in real-time to drive d3 visualizations using Apache Storm, the “Hadoop of Real Time.” Storm is free, open source, and fun to use! Learn from Karthik Ramasamy, Technical Lead of Storm@Twitter, about the distributed, fault-tolerant, and flexible technology used to power Twitter’s real-time data flow pipeline. Twitter open sourced Storm in 2011, and it graduated to a top-level Apache project in September, 2014. Starting from basic distributed concepts presented during our first Udacity-Twitter Storm Hackathon, link Storm concepts to Storm syntax to scalably drive Word Cloud visualizations with Vagrant, Ubuntu, Maven, Flask, Redis, and d3. Link to the public Twitter gardenhose stream to process live tweets, parse embedded URLs, and calculate Top worldwide hashtags. Extend beyond Storm basics by exploring multi-language capabilities in Python, integrate open source components, and implement real-time streaming joins. In your final project, follow real-time trending topics by implementing the data pipeline to visualize only tweets that contain Top worldwide hashtags. Extend your project by exploring the Twitter API, or any data source, alongside Hackathon participants as they design their own ideas, receive feedback from Karthik, and open source a final project calculating real-time tweet sentiment and geolocation to drive a U.S. Map.

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Le programme

Lesson 1

Join instructor Karthik Ramasamy and the first Udacity-Twitter Storm Hackathon to cover the motivation and practice of real-time, distributed, fault-tolerant data processing. Dive into basic Storm Topologies by linking to a real-time d3 Word Cloud Visualization using Redis, Flask, and d3.

Lesson 2

Explore Storm basics by programming Bolts, linking Spouts, and finally connecting to the live Twitter API to process real-time tweets. Explore open source components by connecting a Rolling Count Bolt to your topology to visualize Rolling Top Tweeted Words.

Lesson 3

Go beyond Storm basics by exploring multi-language capabilities to download and parse real-time Tweeted URLs in Python using Beautiful Soup. Integrate complex open source bolts to calculate Top-N words to visualize real-time Top-N Hashtags. Finally, use stream grouping concepts to easily create streaming join to connect and dynamically process multiple streams.

Lesson 4

Work on your final project and we cover additional questions and topics brought up by Hackathon participants. Explore Vagrant, VirtualBox, Redis, Flask, and d3 further if you are interested!

Final Project: Construct a Storm Topology

Design a Storm Topology and new bolt that uses streaming joins to dynamically calculate Top-N Hashtags and display real-time tweets that contain trending Top Hashtags. Post your visualization to the forum and tweet them to your Twitter followers.

Project Extensions

Use additional features of the real-time Twitter sample stream or use any data source to drive your real-time d3 visualization.
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Les intervenants

  • Karthik Ramasamy - Karthik is the engineering manager and technical lead of Storm, the real-time analytics engine@Twitter. He has two decades of experience working in parallel databases, big data infrastructure and networking. He co-founded Locomatix, a company that specializes in real time streaming processing on Hadoop and Cassandra using SQL that was acquired by Twitter. Prior to Locomatix, Karthik was at Juniper Networks and Greenplum. At the University of Wisconsin, he worked extensively in parallel database systems, query processing, scale out technologies, storage engine and online analytical systems. Several of these research were spun as a company later acquired by Teradata. He is the author of several publications, patents and one of the best selling book "Network Routing: Algorithms, Protocols and Architectures". He has a Ph.D. in Computer Science from University of Wisconsin, Madison.
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Le concepteur

Twitter

Twitter est un outil de microblogage géré par l'entreprise Twitter Inc. Il permet à un utilisateur d’envoyer gratuitement de brefs messages, appelés tweets, sur internet, par messagerie instantanée ou par SMS. Ces messages sont limités à 140 caractères.

Twitter a été créé le 21 mars 2006 par Jack Dorsey, Evan Williams, Biz Stone et Noah Glass, et lancé en juillet de la même année. Le service est rapidement devenu populaire, jusqu'à réunir plus de 500 millions d'utilisateurs dans le monde fin février 2012. Au 6 mai 2016, Twitter compte 320 millions d’utilisateurs actifs par mois avec 500 millions de tweets envoyés par jour et est disponible en plus de 35 langues.

Le siège social de Twitter Inc. se situe aux États-Unis à San Francisco. L'entreprise dispose de bureaux supplémentaires et de serveurs informatiques à New York.

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La plateforme

Udacity

Udacity est une entreprise fondé par Sebastian Thrun, David Stavens, et Mike Sokolsky offrant cours en ligne ouvert et massif.

Selon Thrun, l'origine du nom Udacity vient de la volonté de l'entreprise d'être "audacieux pour vous, l'étudiant ". Bien que Udacity se concentrait à l'origine sur une offre de cours universitaires, la plateforme se concentre désormais plus sur de formations destinés aux professionnels.

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