Optimizing Spatiotemporal Analysis Using Multidimensional Indexing with GeoWave

The open source software GeoWave bridges the gap between geographic information systems and distributed computing. This is done by preserving locality of multidimensional data when indexing it into a single-dimensional key-value store, using space filling curves. This means that like values in each dimension are stored physically close together in the datastore. We demonstrate the efficiencies and benefits of the GeoWave indexing algorithm to store and query billions of spatiotemporal data points. We show how this indexing strategy can be used to reduce query and processing times by multiple orders of magnitude using publicly available taxi trip data published by the New York City Taxi & Limousine Commission. Furthermore, we demonstrate how this efficiency lends itself to analysis that would otherwise be unfeasible