def test_distance_join_query_flat_to_df(self):
poi_point_rdd = WktReader.readToGeometryRDD(self.sc, bank_csv_path, 1, False, False)
circle_rdd = CircleRDD(poi_point_rdd, 2.0)
circle_rdd.analyze()
poi_point_rdd.analyze()
poi_point_rdd.spatialPartitioning(GridType.QUADTREE)
circle_rdd.spatialPartitioning(poi_point_rdd.getPartitioner())
jvm_sedona_rdd = JoinQueryRaw.DistanceJoinQueryFlat(poi_point_rdd, circle_rdd, False, True)
assert jvm_sedona_rdd.to_rdd().collect().__len__() == 10
def DistanceJoinQueryFlat(cls, spatialRDD: SpatialRDD,
queryRDD: SpatialRDD, useIndex: bool,
considerBoundaryIntersection: bool) -> RDD:
"""
:param spatialRDD: SpatialRDD
:param queryRDD: SpatialRDD
:param useIndex: bool
:param considerBoundaryIntersection: bool
>> spatial_rdd =
>> query_rdd =
>> spatial_join_result = JoinQuery.DistanceJoinQueryFlat(spatial_rdd, query_rdd, True, True)
>> spatial_join_result.collect()
[GeoData(), GeoData()]
:return:
"""
pair_rdd = JoinQueryRaw.DistanceJoinQueryFlat(
spatialRDD, queryRDD, useIndex, considerBoundaryIntersection)
return pair_rdd.to_rdd()
def test_distance_join_query_flat_to_df(self):
poi_point_rdd = WktReader.readToGeometryRDD(self.sc, bank_csv_path, 1,
False, False)
circle_rdd = CircleRDD(poi_point_rdd, 2.0)
circle_rdd.analyze()
poi_point_rdd.analyze()
poi_point_rdd.spatialPartitioning(GridType.QUADTREE)
circle_rdd.spatialPartitioning(poi_point_rdd.getPartitioner())
jvm_sedona_rdd = JoinQueryRaw.DistanceJoinQueryFlat(
poi_point_rdd, circle_rdd, False, True)
df_sedona_rdd = Adapter.toDf(jvm_sedona_rdd,
["poi_from_id", "poi_from_name"],
["poi_to_id", "poi_to_name"], self.spark)
assert df_sedona_rdd.count() == 10
assert df_sedona_rdd.columns == [
"leftgeometry", "poi_from_id", "poi_from_name", "rightgeometry",
"poi_to_id", "poi_to_name"
]