Interactive Visualization of Streaming Data Powered by Spark by Ruhollah Farchtchi

This document discusses how to visualize streaming data using Spark. It describes how Spark Streaming can be used to process streaming data in real-time and integrate it with visualization tools. Key points include: - Spark Streaming receives streaming data from sources like Kafka and processes it using in-memory computations in a single JVM cluster. - The processed data can be stored in buffers like MongoDB or output to systems like MemSQL, Solr to enable interactive visualizations that update in real-time. - A demo is shown of Twitter data being streamed and analyzed using Spark Streaming with results stored in MemSQL and Solr for visualization. - Benefits of this approach include being able to work with streaming data