Earth Data Analytics Service (EDAS) – Server Side Analytics at the NCCS

Laura E. Carriere, Computer Science Corp, laura.carriere@nasa.gov (Presenter)
Thomas Maxwell, CSRA, thomas.maxwell@nasa.gov
Daniel Duffy, GSFC, daniel.q.duffy@nasa.gov

As the availability and volume of Earth data grow, researchers spend more time downloading and processing their data than doing science. The NASA Center for Climate Simulation (NCCS) has developed the Earth Data Analytics Service (EDAS), a high-performance big data analytics framework built on Apache Spark, to allow researchers to leverage our compute power to analyze large datasets located at the NCCS through a web-based interface, thereby eliminating the need to download the data.

EDAS provides access to a suite of “canonical operations”—min, max, sum, difference, average, root mean square, anomaly, and standard deviation— that researchers can combine to develop various workflows. EDAS uses a dynamic caching architecture, a custom framework, and a streaming parallel in-memory workflow for efficiently processing huge datasets within limited memory spaces at interactive response times. These operations and datasets can be accessed via a Web Processing Service (WPS) API using applications written by the user.

This poster will present information on accessing EDAS as well as a variety of use cases for using EDAS to evaluate climate reanalysis data such as MERRA2. Examples provided will utilize Jupyter Notebooks.

Poster Location ID: 109

Session Assigned: Crosscutting