In this chapter, we have introduced the concepts of storing data in a spatio-temporal way so that we can use GeoMesa and GeoServer to create and run queries. We have shown these queries executed in both the tools themselves and in a programmatic way, leveraging GeoServer to display results. Further, we have demonstrated how to merge different artifacts to create insights purely from the raw GDELT events, before any follow-on processing. Following on from GeoMesa, we have touched upon the highly complex world of oil pricing and worked on a simple algorithm to estimate weekly oil changes. Whilst it is not reasonable to create an accurate model with the time and resources available, we have explored a number of areas of concern and attempted to address these, at least at a high level, in order to give an insight into possible approaches that can be made in this problem space.
Throughout the chapter, we have introduced a number of key Spark libraries and functions, the key area being...