Which industry has/needs the most challenging sql queries?

• PolygonDistances

  4 2 7.5 Python

  Create distance-from-country maps using a nonstandard(?) technique that projects longitude and latitude to 3D, performs the computations there, and then projects back to longitude and latitude

The fastest thing I've found so far is to rasterize the data, project the points into 3D, create a KDTree, compute the straight line distances, and convert those to spherical distances, all using numpy with python (not SQL), but I wonder if I'm missing something. My work so far: https://github.com/barrycarter/PolygonDistances/

• bcapps

  65 20 7.3

OK, so how do I do this exactly? I was under the impression that creating distance-based contours (not degree-based contours) using polygons was difficult. Is there an easy way to do this in QGIS (or even GRASS) that I'm missing? My sort of attempt to do this ages ago is https://github.com/barrycarter/bcapps/tree/master/STACK/bc-buffer-land.grass but I'm pretty sure I never got it working and I ended up using an existing file instead of creating my own.

• InfluxDB

  www.influxdata.com featured

  Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

  

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