IBM jStart team has joined with the SETI Institute to develop a Spark application to analyze the 198 million radio events detected by the Allen Telescope Array over the past decade. The complex nature of the data demands sophisticated mathematical models to tease out faint signals, and machine learning algorithms to separate terrestrial interference from true signals of interest. These requirements are well suited to the scalable in-memory capabilities offered by IBM Apache Spark Services.
You can learn more by going to the repo home page or by visiting the project website.
This Spark project is implemented under the Apache 2.0 licensing terms. Please see license.txt.