python/tests/core/test_rdd.py

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# to you under the Apache License, Version 2.0 (the
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#
#   http://www.apache.org/licenses/LICENSE-2.0
#
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import logging
import os

from shapely.geometry import Point

from tests import tests_resource
from tests.properties.polygon_properties import (
    polygon_rdd_end_offset,
    polygon_rdd_index_type,
    polygon_rdd_input_location,
    polygon_rdd_splitter,
    polygon_rdd_start_offset,
)
from tests.test_base import TestBase

from sedona.spark.core.enums import FileDataSplitter, GridType, IndexType
from sedona.spark.core.enums.join_build_side import JoinBuildSide
from sedona.spark.core.geom.envelope import Envelope
from sedona.spark.core.spatialOperator import JoinQuery, KNNQuery, RangeQuery
from sedona.spark.core.spatialOperator.join_params import JoinParams
from sedona.spark.core.SpatialRDD import CircleRDD, PointRDD, PolygonRDD

point_rdd_input_location = os.path.join(tests_resource, "arealm-small.csv")

point_rdd_splitter = FileDataSplitter.CSV

point_rdd_index_type = IndexType.RTREE
point_rdd_num_partitions = 5
point_rdd_offset = 1

knn_query_point = Point(-84.01, 34.01)

range_query_window = Envelope(-90.01, -80.01, 30.01, 40.01)

join_query_partitionin_type = GridType.QUADTREE
each_query_loop_times = 1


class TestSpatialRDD(TestBase):

    def test_empty_constructor_test(self):
        object_rdd = PointRDD(
            sparkContext=self.sc,
            InputLocation=point_rdd_input_location,
            Offset=point_rdd_offset,
            splitter=point_rdd_splitter,
            carryInputData=False,
        )
        object_rdd_copy = PointRDD()
        object_rdd_copy.rawJvmSpatialRDD = object_rdd.rawJvmSpatialRDD
        object_rdd_copy.analyze()

    def test_spatial_range_query(self):
        object_rdd = PointRDD(
            sparkContext=self.sc,
            InputLocation=point_rdd_input_location,
            Offset=point_rdd_offset,
            splitter=point_rdd_splitter,
            carryInputData=False,
        )

        for i in range(each_query_loop_times):
            result_size = RangeQuery.SpatialRangeQuery(
                object_rdd, range_query_window, False, False
            ).count()
            logging.info(result_size)

    def test_range_query_using_index(self):
        object_rdd = PointRDD(
            sparkContext=self.sc,
            InputLocation=point_rdd_input_location,
            Offset=point_rdd_offset,
            splitter=point_rdd_splitter,
            carryInputData=False,
        )
        object_rdd.buildIndex(point_rdd_index_type, False)
        for i in range(each_query_loop_times):
            result_size = RangeQuery.SpatialRangeQuery(
                object_rdd, range_query_window, False, True
            ).count

    def test_knn_query(self):
        object_rdd = PointRDD(
            sparkContext=self.sc,
            InputLocation=point_rdd_input_location,
            Offset=point_rdd_offset,
            splitter=point_rdd_splitter,
            carryInputData=False,
        )
        for i in range(each_query_loop_times):
            result = KNNQuery.SpatialKnnQuery(object_rdd, knn_query_point, 1000, False)

    def test_knn_query_with_index(self):
        object_rdd = PointRDD(
            sparkContext=self.sc,
            InputLocation=point_rdd_input_location,
            Offset=point_rdd_offset,
            splitter=point_rdd_splitter,
            carryInputData=False,
        )
        object_rdd.buildIndex(point_rdd_index_type, False)
        for i in range(each_query_loop_times):
            result = KNNQuery.SpatialKnnQuery(object_rdd, knn_query_point, 1000, True)

    def test_spaltial_join(self):
        query_window_rdd = PolygonRDD(
            self.sc,
            polygon_rdd_input_location,
            polygon_rdd_start_offset,
            polygon_rdd_end_offset,
            polygon_rdd_splitter,
            True,
        )

        object_rdd = PointRDD(
            sparkContext=self.sc,
            InputLocation=point_rdd_input_location,
            Offset=point_rdd_offset,
            splitter=point_rdd_splitter,
            carryInputData=False,
        )
        object_rdd.analyze()
        object_rdd.spatialPartitioning(join_query_partitionin_type)
        query_window_rdd.spatialPartitioning(object_rdd.getPartitioner())

        for x in range(each_query_loop_times):
            result_size = JoinQuery.SpatialJoinQuery(
                object_rdd, query_window_rdd, False, True
            ).count

    def test_spatial_join_using_index(self):
        query_window = PolygonRDD(
            self.sc,
            polygon_rdd_input_location,
            polygon_rdd_start_offset,
            polygon_rdd_end_offset,
            polygon_rdd_splitter,
            True,
        )
        object_rdd = PointRDD(
            sparkContext=self.sc,
            InputLocation=point_rdd_input_location,
            Offset=point_rdd_offset,
            splitter=point_rdd_splitter,
            carryInputData=False,
        )
        object_rdd.analyze()
        object_rdd.spatialPartitioning(join_query_partitionin_type)
        query_window.spatialPartitioning(object_rdd.getPartitioner())

        object_rdd.buildIndex(point_rdd_index_type, True)

        for i in range(each_query_loop_times):
            result_size = JoinQuery.SpatialJoinQuery(
                object_rdd, query_window, True, False
            ).count()

    def test_spatial_join_using_index_on_polygons(self):
        query_window = PolygonRDD(
            self.sc,
            polygon_rdd_input_location,
            polygon_rdd_start_offset,
            polygon_rdd_end_offset,
            polygon_rdd_splitter,
            True,
        )
        object_rdd = PointRDD(
            sparkContext=self.sc,
            InputLocation=point_rdd_input_location,
            Offset=point_rdd_offset,
            splitter=point_rdd_splitter,
            carryInputData=False,
        )
        object_rdd.analyze()
        object_rdd.spatialPartitioning(join_query_partitionin_type)
        query_window.spatialPartitioning(object_rdd.getPartitioner())

        query_window.buildIndex(polygon_rdd_index_type, True)

        for i in range(each_query_loop_times):
            result_size = JoinQuery.SpatialJoinQuery(
                object_rdd, query_window, True, False
            ).count()

    def test_spatial_join_query_using_index_on_polygons(self):
        query_window_rdd = PolygonRDD(
            self.sc,
            polygon_rdd_input_location,
            polygon_rdd_start_offset,
            polygon_rdd_end_offset,
            polygon_rdd_splitter,
            True,
        )
        object_rdd = PointRDD(
            sparkContext=self.sc,
            InputLocation=point_rdd_input_location,
            Offset=point_rdd_offset,
            splitter=point_rdd_splitter,
            carryInputData=False,
        )
        object_rdd.analyze()
        object_rdd.spatialPartitioning(join_query_partitionin_type)
        query_window_rdd.spatialPartitioning(object_rdd.getPartitioner())

        for i in range(each_query_loop_times):
            result_size = JoinQuery.SpatialJoinQuery(
                object_rdd, query_window_rdd, True, False
            )

    def test_spatial_join_query_and_build_index_on_points_on_the_fly(self):
        query_window = PolygonRDD(
            self.sc,
            polygon_rdd_input_location,
            polygon_rdd_start_offset,
            polygon_rdd_end_offset,
            polygon_rdd_splitter,
            True,
        )
        object_rdd = PointRDD(
            sparkContext=self.sc,
            InputLocation=point_rdd_input_location,
            Offset=point_rdd_offset,
            splitter=point_rdd_splitter,
            carryInputData=False,
        )
        object_rdd.analyze()
        object_rdd.spatialPartitioning(join_query_partitionin_type)
        query_window.spatialPartitioning(object_rdd.getPartitioner())

        for i in range(each_query_loop_times):
            result_size = JoinQuery.SpatialJoinQuery(
                object_rdd, query_window, True, False
            ).count()

    def test_spatial_join_query_and_build_index_on_polygons_on_the_fly(self):
        query_window_rdd = PolygonRDD(
            self.sc,
            polygon_rdd_input_location,
            polygon_rdd_start_offset,
            polygon_rdd_end_offset,
            polygon_rdd_splitter,
            True,
        )

        object_rdd = PointRDD(
            sparkContext=self.sc,
            InputLocation=point_rdd_input_location,
            Offset=point_rdd_offset,
            splitter=point_rdd_splitter,
            carryInputData=False,
        )
        object_rdd.analyze()
        object_rdd.spatialPartitioning(join_query_partitionin_type)
        query_window_rdd.spatialPartitioning(object_rdd.getPartitioner())

        for i in range(each_query_loop_times):
            join_params = JoinParams(
                True, False, polygon_rdd_index_type, JoinBuildSide.LEFT
            )
            resultSize = JoinQuery.spatialJoin(
                query_window_rdd, object_rdd, join_params
            ).count()

    def test_distance_join_query(self):
        object_rdd = PointRDD(
            sparkContext=self.sc,
            InputLocation=point_rdd_input_location,
            Offset=point_rdd_offset,
            splitter=point_rdd_splitter,
            carryInputData=False,
        )
        query_window_rdd = CircleRDD(object_rdd, 0.1)
        object_rdd.analyze()
        object_rdd.spatialPartitioning(GridType.QUADTREE)
        query_window_rdd.spatialPartitioning(object_rdd.getPartitioner())

        for i in range(each_query_loop_times):
            result_size = JoinQuery.DistanceJoinQuery(
                object_rdd, query_window_rdd, False, True
            ).count()

    def test_distance_join_query_using_index(self):
        object_rdd = PointRDD(
            sparkContext=self.sc,
            InputLocation=point_rdd_input_location,
            Offset=point_rdd_offset,
            splitter=point_rdd_splitter,
            carryInputData=False,
        )
        query_window_rdd = CircleRDD(object_rdd, 0.1)
        object_rdd.analyze()
        object_rdd.spatialPartitioning(GridType.QUADTREE)
        query_window_rdd.spatialPartitioning(object_rdd.getPartitioner())

        object_rdd.buildIndex(IndexType.RTREE, True)

        for i in range(each_query_loop_times):
            result_size = JoinQuery.DistanceJoinQuery(
                object_rdd, query_window_rdd, True, True
            ).count