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#
# 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.
#
from py4j.java_gateway import Py4JJavaError
from pyspark.storagelevel import StorageLevel
from pyspark.serializers import PairDeserializer, NoOpSerializer
from pyspark.streaming import DStream
__all__ = ['KafkaUtils', 'utf8_decoder']
def utf8_decoder(s):
""" Decode the unicode as UTF-8 """
return s and s.decode('utf-8')
class KafkaUtils(object):
@staticmethod
def createStream(ssc, zkQuorum, groupId, topics, kafkaParams={},
storageLevel=StorageLevel.MEMORY_AND_DISK_SER_2,
keyDecoder=utf8_decoder, valueDecoder=utf8_decoder):
"""
Create an input stream that pulls messages from a Kafka Broker.
:param ssc: StreamingContext object
:param zkQuorum: Zookeeper quorum (hostname:port,hostname:port,..).
:param groupId: The group id for this consumer.
:param topics: Dict of (topic_name -> numPartitions) to consume.
Each partition is consumed in its own thread.
:param kafkaParams: Additional params for Kafka
:param storageLevel: RDD storage level.
:param keyDecoder: A function used to decode key (default is utf8_decoder)
:param valueDecoder: A function used to decode value (default is utf8_decoder)
:return: A DStream object
"""
kafkaParams.update({
"zookeeper.connect": zkQuorum,
"group.id": groupId,
"zookeeper.connection.timeout.ms": "10000",
})
if not isinstance(topics, dict):
raise TypeError("topics should be dict")
jlevel = ssc._sc._getJavaStorageLevel(storageLevel)
try:
# Use KafkaUtilsPythonHelper to access Scala's KafkaUtils (see SPARK-6027)
helperClass = ssc._jvm.java.lang.Thread.currentThread().getContextClassLoader()\
.loadClass("org.apache.spark.streaming.kafka.KafkaUtilsPythonHelper")
helper = helperClass.newInstance()
jstream = helper.createStream(ssc._jssc, kafkaParams, topics, jlevel)
except Py4JJavaError as e:
# TODO: use --jar once it also work on driver
if 'ClassNotFoundException' in str(e.java_exception):
print("""
________________________________________________________________________________________________
Spark Streaming's Kafka libraries not found in class path. Try one of the following.
1. Include the Kafka library and its dependencies with in the
spark-submit command as
$ bin/spark-submit --packages org.apache.spark:spark-streaming-kafka:%s ...
2. Download the JAR of the artifact from Maven Central http://search.maven.org/,
Group Id = org.apache.spark, Artifact Id = spark-streaming-kafka-assembly, Version = %s.
Then, include the jar in the spark-submit command as
$ bin/spark-submit --jars <spark-streaming-kafka-assembly.jar> ...
________________________________________________________________________________________________
""" % (ssc.sparkContext.version, ssc.sparkContext.version))
raise e
ser = PairDeserializer(NoOpSerializer(), NoOpSerializer())
stream = DStream(jstream, ssc, ser)
return stream.map(lambda k_v: (keyDecoder(k_v[0]), valueDecoder(k_v[1])))
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