Processing Spatio-temporal Data On Map-Reduce

The amount of spatio-temporal data generated in numerous scientific and industrial settings have exploded in recent years. Without a distributed platform, supporting efficient analytics operations over such voluminous datasets become prohibitively expensive. As a result there has been an increasing interest in using map-reduce to parallelize the processing of large-scale spatio-temporal data. While Hadoop, which has become the de-facto implementation of map-reduce, has shown to be effective in handling large volumes of unstructured data, several key issues needs to be addressed to exploit its power for processing spatio-temporal data.