#
# 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 time
from datetime import datetime
import traceback
from pyspark import SparkContext, RDD
class TransformFunction(object):
"""
This class wraps a function RDD[X] -> RDD[Y] that was passed to
DStream.transform(), allowing it to be called from Java via Py4J's
callback server.
Java calls this function with a sequence of JavaRDDs and this function
returns a single JavaRDD pointer back to Java.
"""
_emptyRDD = None
def __init__(self, ctx, func, *deserializers):
self.ctx = ctx
self.func = func
self.deserializers = deserializers
def call(self, milliseconds, jrdds):
try:
if self.ctx is None:
self.ctx = SparkContext._active_spark_context
if not self.ctx or not self.ctx._jsc:
# stopped
return
# extend deserializers with the first one
sers = self.deserializers
if len(sers) < len(jrdds):
sers += (sers[0],) * (len(jrdds) - len(sers))
rdds = [RDD(jrdd, self.ctx, ser) if jrdd else None
for jrdd, ser in zip(jrdds, sers)]
t = datetime.fromtimestamp(milliseconds / 1000.0)
r = self.func(t, *rdds)
if r:
return r._jrdd
except Exception:
traceback.print_exc()
def __repr__(self):
return "TransformFunction(%s)" % self.func
class Java:
implements = ['org.apache.spark.streaming.api.python.PythonTransformFunction']
class TransformFunctionSerializer(object):
"""
This class implements a serializer for PythonTransformFunction Java
objects.
This is necessary because the Java PythonTransformFunction objects are
actually Py4J references to Python objects and thus are not directly
serializable. When Java needs to serialize a PythonTransformFunction,
it uses this class to invoke Python, which returns the serialized function
as a byte array.
"""
def __init__(self, ctx, serializer, gateway=None):
self.ctx = ctx
self.serializer = serializer
self.gateway = gateway or self.ctx._gateway
self.gateway.jvm.PythonDStream.registerSerializer(self)
def dumps(self, id):
try:
func = self.gateway.gateway_property.pool[id]
return bytearray(self.serializer.dumps((func.func, func.deserializers)))
except Exception:
traceback.print_exc()
def loads(self, bytes):
try:
f, deserializers = self.serializer.loads(str(bytes))
return TransformFunction(self.ctx, f, *deserializers)
except Exception:
traceback.print_exc()
def __repr__(self):
return "TransformFunctionSerializer(%s)" % self.serializer
class Java:
implements = ['org.apache.spark.streaming.api.python.PythonTransformFunctionSerializer']
def rddToFileName(prefix, suffix, timestamp):
"""
Return string prefix-time(.suffix)
>>> rddToFileName("spark", None, 12345678910)
'spark-12345678910'
>>> rddToFileName("spark", "tmp", 12345678910)
'spark-12345678910.tmp'
"""
if isinstance(timestamp, datetime):
seconds = time.mktime(timestamp.timetuple())
timestamp = long(seconds * 1000) + timestamp.microsecond / 1000
if suffix is None:
return prefix + "-" + str(timestamp)
else:
return prefix + "-" + str(timestamp) + "." + suffix
if __name__ == "__main__":
import doctest
doctest.testmod()
