499ac3e69a
The current default storage level of Python persist API is MEMORY_ONLY_SER. This is different from the default level MEMORY_ONLY in the official document and RDD APIs. davies Is this inconsistency intentional? Thanks! Updates: Since the data is always serialized on the Python side, the storage levels of JAVA-specific deserialization are not removed, such as MEMORY_ONLY. Updates: Based on the reviewers' feedback. In Python, stored objects will always be serialized with the [Pickle](https://docs.python.org/2/library/pickle.html) library, so it does not matter whether you choose a serialized level. The available storage levels in Python include `MEMORY_ONLY`, `MEMORY_ONLY_2`, `MEMORY_AND_DISK`, `MEMORY_AND_DISK_2`, `DISK_ONLY`, `DISK_ONLY_2` and `OFF_HEAP`. Author: gatorsmile <gatorsmile@gmail.com> Closes #10092 from gatorsmile/persistStorageLevel.
74 lines
2.9 KiB
Python
74 lines
2.9 KiB
Python
#
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# Licensed to the Apache Software Foundation (ASF) under one or more
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# contributor license agreements. See the NOTICE file distributed with
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# this work for additional information regarding copyright ownership.
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# The ASF licenses this file to You under the Apache License, Version 2.0
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# (the "License"); you may not use this file except in compliance with
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# the License. You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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#
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from py4j.protocol import Py4JJavaError
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from pyspark.storagelevel import StorageLevel
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from pyspark.serializers import UTF8Deserializer
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from pyspark.streaming import DStream
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__all__ = ['MQTTUtils']
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class MQTTUtils(object):
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@staticmethod
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def createStream(ssc, brokerUrl, topic,
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storageLevel=StorageLevel.MEMORY_AND_DISK_2):
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"""
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Create an input stream that pulls messages from a Mqtt Broker.
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:param ssc: StreamingContext object
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:param brokerUrl: Url of remote mqtt publisher
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:param topic: topic name to subscribe to
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:param storageLevel: RDD storage level.
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:return: A DStream object
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"""
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jlevel = ssc._sc._getJavaStorageLevel(storageLevel)
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try:
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helperClass = ssc._jvm.java.lang.Thread.currentThread().getContextClassLoader() \
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.loadClass("org.apache.spark.streaming.mqtt.MQTTUtilsPythonHelper")
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helper = helperClass.newInstance()
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jstream = helper.createStream(ssc._jssc, brokerUrl, topic, jlevel)
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except Py4JJavaError as e:
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if 'ClassNotFoundException' in str(e.java_exception):
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MQTTUtils._printErrorMsg(ssc.sparkContext)
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raise e
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return DStream(jstream, ssc, UTF8Deserializer())
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@staticmethod
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def _printErrorMsg(sc):
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print("""
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________________________________________________________________________________________________
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Spark Streaming's MQTT libraries not found in class path. Try one of the following.
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1. Include the MQTT library and its dependencies with in the
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spark-submit command as
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$ bin/spark-submit --packages org.apache.spark:spark-streaming-mqtt:%s ...
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2. Download the JAR of the artifact from Maven Central http://search.maven.org/,
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Group Id = org.apache.spark, Artifact Id = spark-streaming-mqtt-assembly, Version = %s.
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Then, include the jar in the spark-submit command as
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$ bin/spark-submit --jars <spark-streaming-mqtt-assembly.jar> ...
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________________________________________________________________________________________________
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""" % (sc.version, sc.version))
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