python/tests/test_scala_example.py

# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements.  See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership.  The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License.  You may obtain a copy of the License at
#
#   http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied.  See the License for the
# specific language governing permissions and limitations
# under the License.

import os

from pyspark import StorageLevel
from shapely.geometry import Point

from tests import tests_resource
from tests.test_base import TestBase

from sedona.spark.core.enums import FileDataSplitter, GridType, IndexType
from sedona.spark.core.geom.envelope import Envelope
from sedona.spark.core.spatialOperator import JoinQuery, KNNQuery, RangeQuery
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

polygon_rdd_input_location = os.path.join(tests_resource, "primaryroads-polygon.csv")
polygon_rdd_splitter = FileDataSplitter.CSV
polygon_rdd_num_partitions = 5
polygon_rdd_start_offset = 0
polygon_rdd_end_offset = 9

knn_query_point = Point(-84.01, 34.01)
range_query_window = Envelope(-90.01, -80.01, 30.01, 40.01)
join_query_partitioning_type = GridType.QUADTREE
each_query_loop_times = 1

shape_file_input_location = os.path.join(tests_resource, "shapefiles/polygon")


class TestScalaExample(TestBase):

    def test_spatial_range_query(self):
        object_rdd = PointRDD(
            self.sc,
            point_rdd_input_location,
            point_rdd_offset,
            point_rdd_splitter,
            True,
        )
        object_rdd.rawJvmSpatialRDD.persist(StorageLevel.MEMORY_ONLY)
        for _ in range(each_query_loop_times):
            result_size = RangeQuery.SpatialRangeQuery(
                object_rdd, range_query_window, False, False
            ).count()

        object_rdd = PointRDD(
            self.sc,
            point_rdd_input_location,
            point_rdd_offset,
            point_rdd_splitter,
            True,
        )
        object_rdd.rawJvmSpatialRDD.persist(StorageLevel.MEMORY_ONLY)
        for _ in range(each_query_loop_times):
            result_size = RangeQuery.SpatialRangeQuery(
                object_rdd, range_query_window, False, False
            ).count()

    #
    # def test_spatial_range_query_using_index(self):
    #     object_rdd = PointRDD(
    #         self.sc,
    #         point_rdd_input_location,
    #         point_rdd_offset,
    #         point_rdd_splitter,
    #         True,
    #     )
    #     object_rdd.buildIndex(point_rdd_index_type, False)
    #     object_rdd.indexedRawRDD.persist(StorageLevel.MEMORY_ONLY)
    #     assert object_rdd.indexedRawRDD.is_cached
    #
    #     for _ in range(each_query_loop_times):
    #         result_size = RangeQuery.SpatialRangeQuery(
    #             object_rdd, range_query_window, False, True
    #         ).count
    #
    # def test_spatial_knn_query(self):
    #     object_rdd = PointRDD(
    #         self.sc,
    #         point_rdd_input_location,
    #         point_rdd_offset,
    #         point_rdd_splitter,
    #         True,
    #     )
    #     object_rdd.rawJvmSpatialRDD.persist(StorageLevel.MEMORY_ONLY)
    #
    #     for _ in range(each_query_loop_times):
    #         result = KNNQuery.SpatialKnnQuery(object_rdd, knn_query_point, 1000, False)
    #
    # def test_spatial_knn_query_using_index(self):
    #     object_rdd = PointRDD(
    #         self.sc,
    #         point_rdd_input_location,
    #         point_rdd_offset,
    #         point_rdd_splitter,
    #         True,
    #     )
    #     object_rdd.buildIndex(point_rdd_index_type, False)
    #     object_rdd.indexedRawRDD.persist(StorageLevel.MEMORY_ONLY)
    #
    #     for _ in range(each_query_loop_times):
    #         result = KNNQuery.SpatialKnnQuery(object_rdd, knn_query_point, 1000, True)
    #
    # def test_spatial_join_query(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(
    #         self.sc,
    #         point_rdd_input_location,
    #         point_rdd_offset,
    #         point_rdd_splitter,
    #         True,
    #     )
    #
    #     object_rdd.spatialPartitioning(join_query_partitioning_type)
    #     query_window_rdd.spatialPartitioning(object_rdd.getPartitioner())
    #
    #     object_rdd.jvmSpatialPartitionedRDD.persist(StorageLevel.MEMORY_ONLY)
    #     query_window_rdd.jvmSpatialPartitionedRDD.persist(StorageLevel.MEMORY_ONLY)
    #
    #     for _ 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_rdd = PolygonRDD(
    #         self.sc,
    #         polygon_rdd_input_location,
    #         polygon_rdd_start_offset,
    #         polygon_rdd_end_offset,
    #         polygon_rdd_splitter,
    #         True,
    #     )
    #     object_rdd = PointRDD(
    #         self.sc,
    #         point_rdd_input_location,
    #         point_rdd_offset,
    #         point_rdd_splitter,
    #         True,
    #     )
    #
    #     object_rdd.spatialPartitioning(join_query_partitioning_type)
    #     query_window_rdd.spatialPartitioning(object_rdd.getPartitioner())
    #
    #     object_rdd.buildIndex(point_rdd_index_type, True)
    #
    #     object_rdd.indexedRDD.persist(StorageLevel.MEMORY_ONLY)
    #     query_window_rdd.jvmSpatialPartitionedRDD.persist(StorageLevel.MEMORY_ONLY)
    #
    #     for _ in range(each_query_loop_times):
    #         result_size = JoinQuery.SpatialJoinQuery(
    #             object_rdd, query_window_rdd, True, False
    #         ).count()
    #
    # def test_distance_join_query(self):
    #     object_rdd = PointRDD(
    #         self.sc,
    #         point_rdd_input_location,
    #         point_rdd_offset,
    #         point_rdd_splitter,
    #         True,
    #     )
    #     query_window_rdd = CircleRDD(object_rdd, 0.1)
    #
    #     object_rdd.spatialPartitioning(GridType.QUADTREE)
    #     query_window_rdd.spatialPartitioning(object_rdd.getPartitioner())
    #
    #     object_rdd.spatialPartitionedRDD.persist(StorageLevel.MEMORY_ONLY)
    #     assert object_rdd.spatialPartitionedRDD.is_cached
    #
    #     query_window_rdd.spatialPartitionedRDD.persist(StorageLevel.MEMORY_ONLY)
    #
    #     for _ in range(each_query_loop_times):
    #         result_size = JoinQuery.DistanceJoinQuery(
    #             object_rdd, query_window_rdd, False, True
    #         ).count()
    #
    # def test_distance_join_using_index(self):
    #     object_rdd = PointRDD(
    #         self.sc,
    #         point_rdd_input_location,
    #         point_rdd_offset,
    #         point_rdd_splitter,
    #         True,
    #     )
    #
    #     query_window_rdd = CircleRDD(object_rdd, 0.1)
    #
    #     object_rdd.spatialPartitioning(GridType.QUADTREE)
    #     query_window_rdd.spatialPartitioning(object_rdd.getPartitioner())
    #
    #     object_rdd.buildIndex(IndexType.RTREE, True)
    #
    #     object_rdd.indexedRDD.persist(StorageLevel.MEMORY_ONLY)
    #     query_window_rdd.spatialPartitionedRDD.persist(StorageLevel.MEMORY_ONLY)
    #     assert object_rdd.indexedRDD.is_cached
    #     assert query_window_rdd.spatialPartitionedRDD.is_cached
    #
    #     for _ in range(each_query_loop_times):
    #         result_size = JoinQuery.DistanceJoinQuery(
    #             object_rdd, query_window_rdd, True, True
    #         ).count()
    #
    # def test_indexed_rdd_assignment(self):
    #     object_rdd = PointRDD(
    #         self.sc,
    #         point_rdd_input_location,
    #         point_rdd_offset,
    #         point_rdd_splitter,
    #         True,
    #     )
    #     query_window_rdd = CircleRDD(object_rdd, 0.1)
    #     object_rdd.analyze()
    #     object_rdd.spatialPartitioning(GridType.QUADTREE)
    #     object_rdd.buildIndex(IndexType.QUADTREE, True)
    #
    #     query_window_rdd.spatialPartitioning(object_rdd.getPartitioner())
    #
    #     object_rdd.buildIndex(IndexType.RTREE, False)
    #
    #     object_rdd.indexedRDD.persist(StorageLevel.MEMORY_ONLY)
    #     query_window_rdd.jvmSpatialPartitionedRDD.persist(StorageLevel.MEMORY_ONLY)
    #     query_window_rdd.jvmSpatialPartitionedRDD.count()
    #     object_rdd.indexedRDD.count()
    #
    #     import time
    #
    #     start = time.time()
    #     for _ in range(each_query_loop_times):
    #         result_size = JoinQuery.DistanceJoinQuery(
    #             object_rdd, query_window_rdd, True, True
    #         ).count()
    #     diff = time.time() - start
    #
    #     object_rdd = PointRDD(
    #         self.sc,
    #         point_rdd_input_location,
    #         point_rdd_offset,
    #         point_rdd_splitter,
    #         True,
    #     )
    #     query_window_rdd = CircleRDD(object_rdd, 0.1)
    #
    #     object_rdd.analyze()
    #     object_rdd.spatialPartitioning(GridType.QUADTREE)
    #     object_rdd.buildIndex(IndexType.QUADTREE, True)
    #
    #     query_window_rdd.spatialPartitioning(object_rdd.getPartitioner())
    #
    #     object_rdd.buildIndex(IndexType.RTREE, False)
    #
    #     start1 = time.time()
    #     for _ in range(each_query_loop_times):
    #         result_size = JoinQuery.DistanceJoinQuery(
    #             object_rdd, query_window_rdd, True, True
    #         ).count()