GeoMesa as a Distributed Spatio-Temporal Database and Computational Framework
GeoMesa builds on the Hadoop and Accumulo ecosystem to scale up indexing billions of spatio-temporal data. This presentation will showcase and discuss some of GeoMesa's existing distributed computational capabilities such as K-nearest neighbor queries, and then move on to highlight relevant work by the fall 2014 Facebook Open Academy (FOA) students. The FOA students have created a Web Processing Service (WPS) process to get back aggregate time series data for an Extended Common Query Language (ECQL) query. Examples and illustrations will use the open Global Database of Events, Language, and Tone (GDELT) dataset. The conclusion will include ideas for future work in distributed database computation touching on leveraging Spark and Tez. This presentation will be of interest to data scientists, geospatial systems developers, and users of massive Spatio-Temporal datasets.