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# 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.
from pyspark import SparkContext
from sedona.spark.core.enums.file_data_splitter import FileDataSplitter, FileSplitterJvm
from sedona.spark.core.SpatialRDD.spatial_rdd import JvmSpatialRDD, SpatialRDD
from sedona.spark.core.SpatialRDD.spatial_rdd_factory import SpatialRDDFactory
from sedona.spark.utils.meta import MultipleMeta
[docs]
class RectangleRDD(SpatialRDD, metaclass=MultipleMeta):
def __init__(self):
self._do_init()
self._srdd = self._jvm_spatial_rdd()
def __init__(self, rawSpatialRDD: JvmSpatialRDD):
"""
:param rawSpatialRDD:
"""
super().__init__(rawSpatialRDD.sc)
jsrdd = rawSpatialRDD.jsrdd
self._srdd = self._jvm_spatial_rdd(jsrdd)
def __init__(
self,
sparkContext: SparkContext,
InputLocation: str,
Offset: int,
splitter: FileDataSplitter,
carryInputData: bool,
partitions: int,
):
"""
:param sparkContext: SparkContext, the spark context
:param InputLocation: str, the input location
:param Offset:
:param splitter: FileDataSplitter, File data splitter which should be used to split the data
:param carryInputData:
:param partitions: int, the partitions
"""
super().__init__(sparkContext)
jvm_splitter = FileSplitterJvm(self._jvm, splitter)
self._srdd = self._jvm_spatial_rdd(
self._jsc,
InputLocation,
Offset,
jvm_splitter.jvm_instance,
carryInputData,
partitions,
)
def __init__(
self,
sparkContext: SparkContext,
InputLocation: str,
Offset: int,
splitter: FileDataSplitter,
carryInputData: bool,
):
"""
:param sparkContext: SparkContext, the spark context
:param InputLocation: str, the input location
:param Offset:
:param splitter: FileDataSplitter, File data splitter which should be used to split the data
:param carryInputData:
"""
super().__init__(sparkContext)
jvm_splitter = FileSplitterJvm(self._jvm, splitter)
self._srdd = self._jvm_spatial_rdd(
self._jsc, InputLocation, Offset, jvm_splitter.jvm_instance, carryInputData
)
def __init__(
self,
sparkContext: SparkContext,
InputLocation: str,
splitter: FileDataSplitter,
carryInputData: bool,
partitions: int,
):
"""
:param sparkContext: SparkContext, the spark context
:param InputLocation: str, the input location
:param splitter: FileDataSplitter, File data splitter which should be used to split the data
:param carryInputData:
:param partitions: int, the partitions
"""
super().__init__(sparkContext)
jvm_splitter = FileSplitterJvm(self._jvm, splitter)
self._srdd = self._jvm_spatial_rdd(
self._jsc,
InputLocation,
jvm_splitter.jvm_instance,
carryInputData,
partitions,
)
def __init__(
self,
sparkContext: SparkContext,
InputLocation: str,
splitter: FileDataSplitter,
carryInputData: bool,
):
"""
:param sparkContext: SparkContext, the spark context
:param InputLocation: str, the input location
:param splitter: FileDataSplitter, File data splitter which should be used to split the data
:param carryInputData:
"""
super().__init__(sparkContext)
jvm_splitter = FileSplitterJvm(self._jvm, splitter)
self._srdd = self._jvm_spatial_rdd(
self._jsc, InputLocation, jvm_splitter.jvm_instance, carryInputData
)
@property
def _jvm_spatial_rdd(self):
spatial_factory = SpatialRDDFactory(self._sc)
jvm_polygon_rdd = spatial_factory.create_rectangle_rdd()
return jvm_polygon_rdd
[docs]
def MinimumBoundingRectangle(self):
raise NotImplementedError(
"RectangleRDD has not MinimumBoundingRectangle method."
)