Spark Geospatial Analytics
Software Engineering Daily had a great podcast performing Geospatial Analytics using Magellan on Apache Spark which is a distribute Big Data Analytics engine.
One of the common problems in geospatial is given a longitude and latitude how to find which zip code in the United states is this point is located in. So if you have a set of polygons that define the region for all the zip codes in the United States. Then this is basically a point in a polygon geometry problem. Since this is an expensive operation it does not make sense to check for say a location in Florida by checking all the zip code polygons in the US. They way Magellan solves this problem is by dividing the Earth into a recursive set of squares and then checking first if a point belongs in a square. We then have an index of all the zip codes in that square. Once we recursively descend down the squares we can start checking against a set of polygons that are in the square.
Spark Geospatial Analytics podcast
One of the common problems in geospatial is given a longitude and latitude how to find which zip code in the United states is this point is located in. So if you have a set of polygons that define the region for all the zip codes in the United States. Then this is basically a point in a polygon geometry problem. Since this is an expensive operation it does not make sense to check for say a location in Florida by checking all the zip code polygons in the US. They way Magellan solves this problem is by dividing the Earth into a recursive set of squares and then checking first if a point belongs in a square. We then have an index of all the zip codes in that square. Once we recursively descend down the squares we can start checking against a set of polygons that are in the square.
Spark Geospatial Analytics podcast
Comments