def collect(self):
"""Returns all the records as a list of :class:`Row`.
>>> df.collect()
[Row(age=2, name=u'Alice'), Row(age=5, name=u'Bob')]
"""
with SCCallSiteSync(self._sc) as css:
port = self._sc._jvm.PythonRDD.collectAndServe(self._jdf.javaToPython().rdd())
rs = list(_load_from_socket(port, BatchedSerializer(PickleSerializer())))
cls = _create_cls(self.schema)
return [cls(r) for r in rs]
def collect(self):
"""Returns all the records as a list of :class:`Row`.
>>> df.collect()
[Row(age=2, name=u'Alice'), Row(age=5, name=u'Bob')]
"""
with SCCallSiteSync(self._sc) as css:
port = self._sc._jvm.PythonRDD.collectAndServe(self._jdf.javaToPython().rdd())
rs = list(_load_from_socket(port, BatchedSerializer(PickleSerializer())))
cls = _create_cls(self.schema)
return [cls(r) for r in rs]
def collect(self):
"""Return a list that contains all of the rows.
Each object in the list is a Row, the fields can be accessed as
attributes.
>>> df.collect()
[Row(age=2, name=u'Alice'), Row(age=5, name=u'Bob')]
"""
with SCCallSiteSync(self._sc) as css:
port = self._sc._jvm.PythonRDD.collectAndServe(self._jdf.javaToPython().rdd())
rs = list(_load_from_socket(port, BatchedSerializer(PickleSerializer())))
cls = _create_cls(self.schema)
return [cls(r) for r in rs]
def collect(self):
"""Return a list that contains all of the rows.
Each object in the list is a Row, the fields can be accessed as
attributes.
>>> df.collect()
[Row(age=2, name=u'Alice'), Row(age=5, name=u'Bob')]
"""
with SCCallSiteSync(self._sc) as css:
port = self._sc._jvm.PythonRDD.collectAndServe(self._jdf.javaToPython().rdd())
rs = list(_load_from_socket(port, BatchedSerializer(PickleSerializer())))
cls = _create_cls(self.schema)
return [cls(r) for r in rs]
def collect(self):
"""Return a list that contains all of the rows.
Each object in the list is a Row, the fields can be accessed as
attributes.
>>> df.collect()
[Row(age=2, name=u'Alice'), Row(age=5, name=u'Bob')]
"""
with SCCallSiteSync(self._sc) as css:
bytesInJava = self._jdf.javaToPython().collect().iterator()
tempFile = NamedTemporaryFile(delete=False, dir=self._sc._temp_dir)
tempFile.close()
self._sc._writeToFile(bytesInJava, tempFile.name)
# Read the data into Python and deserialize it:
with open(tempFile.name, 'rb') as tempFile:
rs = list(BatchedSerializer(PickleSerializer()).load_stream(tempFile))
os.unlink(tempFile.name)
cls = _create_cls(self.schema)
return [cls(r) for r in rs]
def collect(self):
"""Return a list that contains all of the rows.
Each object in the list is a Row, the fields can be accessed as
attributes.
>>> df.collect()
[Row(age=2, name=u'Alice'), Row(age=5, name=u'Bob')]
"""
with SCCallSiteSync(self._sc) as css:
bytesInJava = self._jdf.javaToPython().collect().iterator()
tempFile = NamedTemporaryFile(delete=False, dir=self._sc._temp_dir)
tempFile.close()
self._sc._writeToFile(bytesInJava, tempFile.name)
# Read the data into Python and deserialize it:
with open(tempFile.name, 'rb') as tempFile:
rs = list(
BatchedSerializer(PickleSerializer()).load_stream(tempFile))
os.unlink(tempFile.name)
cls = _create_cls(self.schema)
return [cls(r) for r in rs]
def applySchema(it):
cls = _create_cls(schema)
return itertools.imap(cls, it)
def applySchema(it):
cls = _create_cls(schema)
return map(cls, it)
def applySchema(it):
cls = _create_cls(schema)
return itertools.imap(cls, it)
def applySchema(it):
cls = _create_cls(schema)
return map(cls, it)
