Comments (5)
Join examples are located at here:
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What are the Array("x", "y"),Array("x", "y")
in the file you linked? Are these supposed to indicate the geospatial columns? if yes, how can these support polygons i.e. it would look like only 2 df of points would be joinable.
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You need to use arrays if there is no shape type in your data source. If you are joining two attributes of ShapeType, you can simply put the join attribute names as strings without Array.
Examples for ShapeType attributes are located:
More about Dataset APIs we supported:
To make it easier to understand, one API joining two ShapeType attributes:
def distanceJoin(right: Dataset[_], leftKeys: Array[String], rightKeys: Array[String], r: Double) : DataFrame
from simba.
So
pointsDf. distanceJoin(polygonDf, Array("point"), Array("polygon"), 3).show
should work?
Do I understand correctly that I should build an index beforehand?
simba.indexTable("a", RTreeType, "testqtree", Array("x", "y") )
so here with points and polygons how can I make sure points and polygons are bot partitioned in the same way?
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Sorry, it should be:
def distanceJoin(right: Dataset[_], leftKey: String, rightKey: String, r: Double) : DataFrame
Array is not needed. And I should say, it may not work since I haven't try any queries for Polygons since it is still under development. I don't think you can do distance join between Polygons and Points in this version. Only things I can guarantee are point operations.
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Related Issues (20)
- Transplant the index part of Simba to standalone branch HOT 2
- Why in the partition folder of core(of sql) should add xxxPartition.scala file HOT 6
- DISTANCE JOIN does not work... HOT 4
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