Spark Streaming makes it easy to build scalable fault-tolerant streaming applications.
At AppsFlyer, we use Spark for many of our offline processing services. Spark Streaming joined our technology stack a few months ago for real-time work flows, reading directly from Kafka to provide value to our clients in near-real-time.
In this session we will code a real-time dashboard application based on Spark Streaming technology. You will learn how to collect events from Kafka, aggregate them by time window and present aggregated insights in a dashboard.
As always, this is a live coding session, so come prepared with your own device.
Please visit this page: https://bitbucket.org/appsflyer/coding-with-af-spark-streaming
On the page, please follow the "Prerequisites" and "Preparation & Setup" sections.
It's really important to do so **prior** to coming to the meetup!
If you encounter any troubles or have any questions, don't hesitate to ask.
Event organizers
AppsFlyer Dev
AppsFlyer is all about analytics and data storytelling. Our analytics dashboard is the face of our product, our mobile SDK sends over 25 billion requests to our server each day, these requests are being handled and streamed to our databases live, and our entire landscape requires 100% uptime. In order to do so, our team uses cutting-edge technologies, frameworks, and landscapes such as ReactJS (Redux, and MobX), ECMAScript 2015 (ES6), Node.js, Webpack, Clojure, Spark, Druid, MemSQL, PostgreSQL, Kafka, Rabi
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