Apache: Big Data North America 2017

This talk will discuss adaptation of Apache Big Data Technologies to analyze large, self-described, structured scientific data sets. We will present initial results for the problem of analyzing petabytes of weather forecasting simulation data produced as part of National Oceanic and Atmospheric Administration's annual Hazardous Weather Testbed. The challenge is to enable weather researchers to perform investigative queries over the full forecast simulation outputs to find the signatures for severe weather phenomena like tornadogenesis. Given the size of the data and the complexity of weather phenomena, these data sets are candidates for exploration by machine learning techniques that can identify heretofore unknown relationships in the dozens of weather parameters generated by the simulations, guiding researchers into developing new scientific models.