def __init__(self, sparkContext: SparkContext, InputLocation: str,
startOffset: int, endOffset: int, splitter: FileDataSplitter,
carryInputData: bool, newLevel: StorageLevel,
sourceEpsgCRSCode: str, targetEpsgCode: str):
"""
:param sparkContext: SparkContext, the spark context
:param InputLocation: str, the input location
:param startOffset:
:param endOffset:
:param splitter: FileDataSplitter, File data splitter which should be used to split the data
:param carryInputData:
:param newLevel:
:param sourceEpsgCRSCode: str, the source epsg CRS code
:param targetEpsgCode: str, the target epsg code
"""
super().__init__(sparkContext)
jvm_splitter = FileSplitterJvm(self._jvm, splitter).jvm_instance
new_level_jvm = JvmStorageLevel(self._jvm, newLevel).jvm_instance
self._srdd = self._jvm_spatial_rdd(self._jsc, InputLocation,
startOffset, endOffset,
jvm_splitter, carryInputData,
new_level_jvm, sourceEpsgCRSCode,
targetEpsgCode)
def __init__(self, sparkContext: SparkContext, InputLocation: str,
startOffset: int, endOffset: int, splitter: FileDataSplitter,
carryInputData: bool, newLevel: StorageLevel,
sourceEpsgCRSCode: str, targetEpsgCode: str):
"""
:param sparkContext: SparkContext instance
:param InputLocation: str, location for loaded file
:param startOffset: int, starting offset
:param endOffset: int, ending offset
:param splitter: FileDataSplitter, data file splitter
:param carryInputData: bool, if spatial rdd should keep non geometry attributes
:param newLevel: StorageLevel
:param sourceEpsgCRSCode: str, epsg code which loaded files is in, ex. epsg:4326 stands for WGS84
:param targetEpsgCode: str, epsg code to transform SpatialRDD
"""
super().__init__(sparkContext)
jvm_splitter = FileSplitterJvm(self._jvm, splitter).jvm_instance
new_level_jvm = JvmStorageLevel(self._jvm, newLevel).jvm_instance
self._srdd = self._jvm_spatial_rdd(self._jsc, InputLocation,
startOffset, endOffset,
jvm_splitter, carryInputData,
new_level_jvm, sourceEpsgCRSCode,
targetEpsgCode)
def __init__(self, sparkContext: SparkContext, InputLocation: str,
splitter: FileDataSplitter, carryInputData: bool):
"""
:param sparkContext: SparkContext instance
:param InputLocation: str, location for loaded file
:param splitter: FileDataSplitter, data file splitter
:param carryInputData: bool, if spatial rdd should keep non geometry attributes
"""
super().__init__(sparkContext)
jvm_splitter = FileSplitterJvm(self._jvm, splitter).jvm_instance
self._srdd = self._jvm_spatial_rdd(self._jsc, InputLocation,
jvm_splitter, carryInputData)
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)
def __init__(self, sparkContext: SparkContext, InputLocation: str,
Offset: int, splitter: FileDataSplitter, carryInputData: bool,
partitions: int):
"""
:param sparkContext: SparkContext instance
:param InputLocation: str, location for loaded file
:param Offset: int, point offset int
:param splitter: FileDataSplitter, data file splitter
:param carryInputData: bool, if spatial rdd should keep non geometry attributes
:param partitions: int, number of partitions int
"""
super().__init__(sparkContext)
jvm_splitter = FileSplitterJvm(self._jvm, splitter).jvm_instance
self._srdd = self._jvm_spatial_rdd(sparkContext._jsc, InputLocation,
Offset, jvm_splitter,
carryInputData, partitions)
def __init__(self, sparkContext: SparkContext, InputLocation: str,
splitter: FileDataSplitter, carryInputData: bool,
partitions: int, newLevel: StorageLevel):
"""
:param sparkContext: SparkContext instance
:param InputLocation: str, location for loaded file
:param splitter: FileDataSplitter, data file splitter
:param carryInputData: bool, if spatial rdd should keep non geometry attributes
:param partitions: int, number of partitions
:param newLevel: StorageLevel
"""
super().__init__(sparkContext)
jvm_splitter = FileSplitterJvm(self._jvm, splitter).jvm_instance
new_level_jvm = JvmStorageLevel(self._jvm, newLevel).jvm_instance
self._srdd = self._jvm_spatial_rdd(self._jsc, InputLocation,
jvm_splitter, carryInputData,
partitions, new_level_jvm)
def __init__(self, sparkContext: SparkContext, InputLocation: str,
splitter: FileDataSplitter, carryInputData: bool,
partitions: int, newLevel: StorageLevel):
"""
: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
:param newLevel:
"""
super().__init__(sparkContext)
jvm_splitter = FileSplitterJvm(self._jvm, splitter)
new_level_jvm = JvmStorageLevel(self._jvm, newLevel).jvm_instance
self._srdd = self._jvm_spatial_rdd(self._jsc, InputLocation,
jvm_splitter.jvm_instance,
carryInputData, partitions,
new_level_jvm)
