Hi, I am new to Spark and I would like know how to compute (dynamically) real-time visualizations using Spark streaming (Kafka).
Use case : We have Real-time analytics dashboard (reports and dashboard), user can define report (visualization) with certain parameters like, refresh period, choose various metrics (segment variables & profile variables). We should compute only visualizations those are in use (users are accessing) with events coming from kafka streams using Spark streaming. Solution : One way of doing is compute visualizations for every incoming message and write back into result streams and application which consume the processed data/result streams. I would like to know is there any better approach? Please advice me here. Thanks, Suresh -- View this message in context: http://apache-spark-user-list.1001560.n3.nabble.com/Compute-Real-time-Visualizations-using-spark-streaming-tp24908.html Sent from the Apache Spark User List mailing list archive at Nabble.com. --------------------------------------------------------------------- To unsubscribe, e-mail: user-unsubscr...@spark.apache.org For additional commands, e-mail: user-h...@spark.apache.org
