def test_convert_spatial_join_result_to_dataframe(self):
polygon_wkt_df = self.spark.read.format("csv").option("delimiter", "\t").option("header", "false").load(
mixed_wkt_geometry_input_location)
polygon_wkt_df.createOrReplaceTempView("polygontable")
polygon_df = self.spark.sql(
"select ST_GeomFromWKT(polygontable._c0) as usacounty from polygontable")
polygon_rdd = Adapter.toSpatialRdd(polygon_df, "usacounty")
polygon_rdd.analyze()
point_csv_df = self.spark.read.format("csv").option("delimiter", ",").option("header", "false").load(
area_lm_point_input_location)
point_csv_df.createOrReplaceTempView("pointtable")
point_df = self.spark.sql(
"select ST_Point(cast(pointtable._c0 as Decimal(24,20)),cast(pointtable._c1 as Decimal(24,20))) as arealandmark from pointtable")
point_rdd = Adapter.toSpatialRdd(point_df, "arealandmark")
point_rdd.analyze()
point_rdd.spatialPartitioning(GridType.QUADTREE)
polygon_rdd.spatialPartitioning(point_rdd.getPartitioner())
point_rdd.buildIndex(IndexType.QUADTREE, True)
join_result_point_rdd = JoinQuery.\
SpatialJoinQueryFlat(point_rdd, polygon_rdd, True, True)
join_result_df = Adapter.toDf(join_result_point_rdd, self.spark)
join_result_df.show()
join_result_df2 = Adapter.toDf(join_result_point_rdd, ["abc", "def"], list(), self.spark)
join_result_df2.show()
def test_to_spatial_rdd_df_and_geom_field_name(self):
spatial_df = self._create_spatial_point_table()
spatial_rdd = Adapter.toSpatialRdd(spatial_df, "geom")
spatial_rdd = Adapter.toSpatialRdd(spatial_df, "s")
spatial_rdd.analyze()
assert spatial_rdd.approximateTotalCount == 121960
assert spatial_rdd.boundaryEnvelope == Envelope(-179.147236, 179.475569, -14.548699, 71.35513400000001)
def test_load_id_column_data_check(self):
spatial_rdd = PolygonRDD(self.spark.sparkContext, geojson_id_input_location, FileDataSplitter.GEOJSON, True)
spatial_rdd.analyze()
df = Adapter.toDf(spatial_rdd, self.spark)
df.show()
assert df.columns.__len__() == 4
assert df.count() == 1
def test_read_shapefile_to_dataframe(self):
spatial_rdd = ShapefileReader.readToGeometryRDD(
self.spark.sparkContext, shape_file_input_location)
spatial_rdd.analyze()
logging.info(spatial_rdd.fieldNames)
df = Adapter.toDf(spatial_rdd, self.spark)
df.show()
def test_read_csv_point_into_spatial_rdd(self):
df = self.spark.read.\
format("csv").\
option("delimiter", "\t").\
option("header", "false").\
load(area_lm_point_input_location)
df.show()
df.createOrReplaceTempView("inputtable")
spatial_df = self.spark.sql("select ST_PointFromText(inputtable._c0,\",\") as arealandmark from inputtable")
spatial_df.show()
spatial_df.printSchema()
spatial_rdd = Adapter.toSpatialRdd(spatial_df, "arealandmark")
spatial_rdd.analyze()
Adapter.toDf(spatial_rdd, self.spark).show()
def test_read_mixed_wkt_geometries_into_spatial_rdd_with_unique_id(self):
df = self.spark.read.format("csv").\
option("delimiter", "\t").\
option("header", "false").\
load(mixed_wkt_geometry_input_location)
df.show()
df.createOrReplaceTempView("inputtable")
spatial_df = self.spark.sql(
"select ST_GeomFromWKT(inputtable._c0) as usacounty, inputtable._c3, inputtable._c5 from inputtable")
spatial_df.show()
spatial_df.printSchema()
spatial_rdd = Adapter.toSpatialRdd(spatial_df, "usacounty")
spatial_rdd.analyze()
assert (Adapter.toDf(spatial_rdd, self.spark).columns.__len__() == 3)
Adapter.toDf(spatial_rdd, self.spark).show()
def test_read_csv_point_into_spatial_rdd_with_unique_id_by_passing_coordinates(self):
df = self.spark.read.format("csv").\
option("delimiter", ",").\
option("header", "false").\
load(area_lm_point_input_location)
df.show()
df.createOrReplaceTempView("inputtable")
spatial_df = self.spark.sql(
"select ST_Point(cast(inputtable._c0 as Decimal(24,20)),cast(inputtable._c1 as Decimal(24,20))) as arealandmark from inputtable")
spatial_df.show()
spatial_df.printSchema()
spatial_rdd = SpatialRDD(self.spark.sparkContext)
spatial_rdd.rawJvmSpatialRDD = Adapter.toRdd(spatial_df)
spatial_rdd.analyze()
assert (Adapter.toDf(spatial_rdd, self.spark).columns.__len__() == 1)
Adapter.toDf(spatial_rdd, self.spark).show()
def test_geojson_to_dataframe(self):
spatial_rdd = PolygonRDD(
self.spark.sparkContext, geojson_input_location, FileDataSplitter.GEOJSON, True
)
spatial_rdd.analyze()
df = Adapter.toDf(spatial_rdd, self.spark).\
withColumn("geometry", expr("ST_GeomFromWKT(geometry)"))
df.show()
assert (df.columns[1] == "STATEFP")
def test_to_rdd_from_dataframe(self):
spatial_df = self._create_spatial_point_table()
spatial_df.show()
jsrdd = Adapter.toRdd(spatial_df)
spatial_rdd = SpatialRDD(self.sc)
spatial_rdd.rawJvmSpatialRDD = jsrdd
spatial_rdd.analyze()
assert spatial_rdd.approximateTotalCount == 121960
assert spatial_rdd.boundaryEnvelope == Envelope(-179.147236, 179.475569, -14.548699, 71.35513400000001)
def test_to_spatial_rdd_df_geom_column_id(self):
df = self.spark.read.\
format("csv").\
option("delimiter", "\t").\
option("header", "false").\
load(mixed_wkt_geometry_input_location)
df_shorter = df.select(col("_c0").alias("geom"), col("_c6").alias("county_name"))
df_shorter.createOrReplaceTempView("county_data")
spatial_df = self.spark.sql("SELECT ST_GeomFromWKT(geom) as geom, county_name FROM county_data")
spatial_df.show()
spatial_rdd = Adapter.toSpatialRdd(spatial_df, ["geom", "county_name"])
spatial_rdd.analyze()
assert spatial_rdd.approximateTotalCount == 100
def test_to_df_srdd_fn_spark(self):
spatial_rdd = PolygonRDD(
self.spark.sparkContext, geojson_input_location, FileDataSplitter.GEOJSON, True
)
spatial_rdd.analyze()
assert spatial_rdd.approximateTotalCount == 1001
spatial_columns = [
"state_id", "county_id", "tract_id", "bg_id",
"fips", "fips_short", "bg_nr", "type", "code1", "code2"
]
spatial_df = Adapter.toDf(
spatial_rdd,
spatial_columns,
self.spark
)
spatial_df.show()
assert spatial_df.columns == ["geometry", *spatial_columns]
assert spatial_df.count() == 1001