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  <h1>Source code for pyspark.streaming.kafka</h1><div class="highlight"><pre>
<span class="c">#</span>
<span class="c"># Licensed to the Apache Software Foundation (ASF) under one or more</span>
<span class="c"># contributor license agreements.  See the NOTICE file distributed with</span>
<span class="c"># this work for additional information regarding copyright ownership.</span>
<span class="c"># The ASF licenses this file to You under the Apache License, Version 2.0</span>
<span class="c"># (the &quot;License&quot;); you may not use this file except in compliance with</span>
<span class="c"># the License.  You may obtain a copy of the License at</span>
<span class="c">#</span>
<span class="c">#    http://www.apache.org/licenses/LICENSE-2.0</span>
<span class="c">#</span>
<span class="c"># Unless required by applicable law or agreed to in writing, software</span>
<span class="c"># distributed under the License is distributed on an &quot;AS IS&quot; BASIS,</span>
<span class="c"># WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.</span>
<span class="c"># See the License for the specific language governing permissions and</span>
<span class="c"># limitations under the License.</span>
<span class="c">#</span>

<span class="kn">from</span> <span class="nn">py4j.java_gateway</span> <span class="kn">import</span> <span class="n">Py4JJavaError</span>

<span class="kn">from</span> <span class="nn">pyspark.rdd</span> <span class="kn">import</span> <span class="n">RDD</span>
<span class="kn">from</span> <span class="nn">pyspark.storagelevel</span> <span class="kn">import</span> <span class="n">StorageLevel</span>
<span class="kn">from</span> <span class="nn">pyspark.serializers</span> <span class="kn">import</span> <span class="n">PairDeserializer</span><span class="p">,</span> <span class="n">NoOpSerializer</span>
<span class="kn">from</span> <span class="nn">pyspark.streaming</span> <span class="kn">import</span> <span class="n">DStream</span>
<span class="kn">from</span> <span class="nn">pyspark.streaming.dstream</span> <span class="kn">import</span> <span class="n">TransformedDStream</span>
<span class="kn">from</span> <span class="nn">pyspark.streaming.util</span> <span class="kn">import</span> <span class="n">TransformFunction</span>

<span class="n">__all__</span> <span class="o">=</span> <span class="p">[</span><span class="s">&#39;Broker&#39;</span><span class="p">,</span> <span class="s">&#39;KafkaUtils&#39;</span><span class="p">,</span> <span class="s">&#39;OffsetRange&#39;</span><span class="p">,</span> <span class="s">&#39;TopicAndPartition&#39;</span><span class="p">,</span> <span class="s">&#39;utf8_decoder&#39;</span><span class="p">]</span>


<div class="viewcode-block" id="utf8_decoder"><a class="viewcode-back" href="../../../pyspark.streaming.html#pyspark.streaming.kafka.utf8_decoder">[docs]</a><span class="k">def</span> <span class="nf">utf8_decoder</span><span class="p">(</span><span class="n">s</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot; Decode the unicode as UTF-8 &quot;&quot;&quot;</span>
    <span class="k">if</span> <span class="n">s</span> <span class="ow">is</span> <span class="bp">None</span><span class="p">:</span>
        <span class="k">return</span> <span class="bp">None</span>
    <span class="k">return</span> <span class="n">s</span><span class="o">.</span><span class="n">decode</span><span class="p">(</span><span class="s">&#39;utf-8&#39;</span><span class="p">)</span>

</div>
<div class="viewcode-block" id="KafkaUtils"><a class="viewcode-back" href="../../../pyspark.streaming.html#pyspark.streaming.kafka.KafkaUtils">[docs]</a><span class="k">class</span> <span class="nc">KafkaUtils</span><span class="p">(</span><span class="nb">object</span><span class="p">):</span>

    <span class="nd">@staticmethod</span>
<div class="viewcode-block" id="KafkaUtils.createStream"><a class="viewcode-back" href="../../../pyspark.streaming.html#pyspark.streaming.kafka.KafkaUtils.createStream">[docs]</a>    <span class="k">def</span> <span class="nf">createStream</span><span class="p">(</span><span class="n">ssc</span><span class="p">,</span> <span class="n">zkQuorum</span><span class="p">,</span> <span class="n">groupId</span><span class="p">,</span> <span class="n">topics</span><span class="p">,</span> <span class="n">kafkaParams</span><span class="o">=</span><span class="bp">None</span><span class="p">,</span>
                     <span class="n">storageLevel</span><span class="o">=</span><span class="n">StorageLevel</span><span class="o">.</span><span class="n">MEMORY_AND_DISK_SER_2</span><span class="p">,</span>
                     <span class="n">keyDecoder</span><span class="o">=</span><span class="n">utf8_decoder</span><span class="p">,</span> <span class="n">valueDecoder</span><span class="o">=</span><span class="n">utf8_decoder</span><span class="p">):</span>
        <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">        Create an input stream that pulls messages from a Kafka Broker.</span>

<span class="sd">        :param ssc:  StreamingContext object</span>
<span class="sd">        :param zkQuorum:  Zookeeper quorum (hostname:port,hostname:port,..).</span>
<span class="sd">        :param groupId:  The group id for this consumer.</span>
<span class="sd">        :param topics:  Dict of (topic_name -&gt; numPartitions) to consume.</span>
<span class="sd">                        Each partition is consumed in its own thread.</span>
<span class="sd">        :param kafkaParams: Additional params for Kafka</span>
<span class="sd">        :param storageLevel:  RDD storage level.</span>
<span class="sd">        :param keyDecoder:  A function used to decode key (default is utf8_decoder)</span>
<span class="sd">        :param valueDecoder:  A function used to decode value (default is utf8_decoder)</span>
<span class="sd">        :return: A DStream object</span>
<span class="sd">        &quot;&quot;&quot;</span>
        <span class="k">if</span> <span class="n">kafkaParams</span> <span class="ow">is</span> <span class="bp">None</span><span class="p">:</span>
            <span class="n">kafkaParams</span> <span class="o">=</span> <span class="nb">dict</span><span class="p">()</span>
        <span class="n">kafkaParams</span><span class="o">.</span><span class="n">update</span><span class="p">({</span>
            <span class="s">&quot;zookeeper.connect&quot;</span><span class="p">:</span> <span class="n">zkQuorum</span><span class="p">,</span>
            <span class="s">&quot;group.id&quot;</span><span class="p">:</span> <span class="n">groupId</span><span class="p">,</span>
            <span class="s">&quot;zookeeper.connection.timeout.ms&quot;</span><span class="p">:</span> <span class="s">&quot;10000&quot;</span><span class="p">,</span>
        <span class="p">})</span>
        <span class="k">if</span> <span class="ow">not</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">topics</span><span class="p">,</span> <span class="nb">dict</span><span class="p">):</span>
            <span class="k">raise</span> <span class="ne">TypeError</span><span class="p">(</span><span class="s">&quot;topics should be dict&quot;</span><span class="p">)</span>
        <span class="n">jlevel</span> <span class="o">=</span> <span class="n">ssc</span><span class="o">.</span><span class="n">_sc</span><span class="o">.</span><span class="n">_getJavaStorageLevel</span><span class="p">(</span><span class="n">storageLevel</span><span class="p">)</span>

        <span class="k">try</span><span class="p">:</span>
            <span class="c"># Use KafkaUtilsPythonHelper to access Scala&#39;s KafkaUtils (see SPARK-6027)</span>
            <span class="n">helperClass</span> <span class="o">=</span> <span class="n">ssc</span><span class="o">.</span><span class="n">_jvm</span><span class="o">.</span><span class="n">java</span><span class="o">.</span><span class="n">lang</span><span class="o">.</span><span class="n">Thread</span><span class="o">.</span><span class="n">currentThread</span><span class="p">()</span><span class="o">.</span><span class="n">getContextClassLoader</span><span class="p">()</span>\
                <span class="o">.</span><span class="n">loadClass</span><span class="p">(</span><span class="s">&quot;org.apache.spark.streaming.kafka.KafkaUtilsPythonHelper&quot;</span><span class="p">)</span>
            <span class="n">helper</span> <span class="o">=</span> <span class="n">helperClass</span><span class="o">.</span><span class="n">newInstance</span><span class="p">()</span>
            <span class="n">jstream</span> <span class="o">=</span> <span class="n">helper</span><span class="o">.</span><span class="n">createStream</span><span class="p">(</span><span class="n">ssc</span><span class="o">.</span><span class="n">_jssc</span><span class="p">,</span> <span class="n">kafkaParams</span><span class="p">,</span> <span class="n">topics</span><span class="p">,</span> <span class="n">jlevel</span><span class="p">)</span>
        <span class="k">except</span> <span class="n">Py4JJavaError</span> <span class="k">as</span> <span class="n">e</span><span class="p">:</span>
            <span class="c"># TODO: use --jar once it also work on driver</span>
            <span class="k">if</span> <span class="s">&#39;ClassNotFoundException&#39;</span> <span class="ow">in</span> <span class="nb">str</span><span class="p">(</span><span class="n">e</span><span class="o">.</span><span class="n">java_exception</span><span class="p">):</span>
                <span class="n">KafkaUtils</span><span class="o">.</span><span class="n">_printErrorMsg</span><span class="p">(</span><span class="n">ssc</span><span class="o">.</span><span class="n">sparkContext</span><span class="p">)</span>
            <span class="k">raise</span> <span class="n">e</span>
        <span class="n">ser</span> <span class="o">=</span> <span class="n">PairDeserializer</span><span class="p">(</span><span class="n">NoOpSerializer</span><span class="p">(),</span> <span class="n">NoOpSerializer</span><span class="p">())</span>
        <span class="n">stream</span> <span class="o">=</span> <span class="n">DStream</span><span class="p">(</span><span class="n">jstream</span><span class="p">,</span> <span class="n">ssc</span><span class="p">,</span> <span class="n">ser</span><span class="p">)</span>
        <span class="k">return</span> <span class="n">stream</span><span class="o">.</span><span class="n">map</span><span class="p">(</span><span class="k">lambda</span> <span class="n">k_v</span><span class="p">:</span> <span class="p">(</span><span class="n">keyDecoder</span><span class="p">(</span><span class="n">k_v</span><span class="p">[</span><span class="mi">0</span><span class="p">]),</span> <span class="n">valueDecoder</span><span class="p">(</span><span class="n">k_v</span><span class="p">[</span><span class="mi">1</span><span class="p">])))</span>
</div>
    <span class="nd">@staticmethod</span>
<div class="viewcode-block" id="KafkaUtils.createDirectStream"><a class="viewcode-back" href="../../../pyspark.streaming.html#pyspark.streaming.kafka.KafkaUtils.createDirectStream">[docs]</a>    <span class="k">def</span> <span class="nf">createDirectStream</span><span class="p">(</span><span class="n">ssc</span><span class="p">,</span> <span class="n">topics</span><span class="p">,</span> <span class="n">kafkaParams</span><span class="p">,</span> <span class="n">fromOffsets</span><span class="o">=</span><span class="bp">None</span><span class="p">,</span>
                           <span class="n">keyDecoder</span><span class="o">=</span><span class="n">utf8_decoder</span><span class="p">,</span> <span class="n">valueDecoder</span><span class="o">=</span><span class="n">utf8_decoder</span><span class="p">):</span>
        <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">        .. note:: Experimental</span>

<span class="sd">        Create an input stream that directly pulls messages from a Kafka Broker and specific offset.</span>

<span class="sd">        This is not a receiver based Kafka input stream, it directly pulls the message from Kafka</span>
<span class="sd">        in each batch duration and processed without storing.</span>

<span class="sd">        This does not use Zookeeper to store offsets. The consumed offsets are tracked</span>
<span class="sd">        by the stream itself. For interoperability with Kafka monitoring tools that depend on</span>
<span class="sd">        Zookeeper, you have to update Kafka/Zookeeper yourself from the streaming application.</span>
<span class="sd">        You can access the offsets used in each batch from the generated RDDs (see</span>

<span class="sd">        To recover from driver failures, you have to enable checkpointing in the StreamingContext.</span>
<span class="sd">        The information on consumed offset can be recovered from the checkpoint.</span>
<span class="sd">        See the programming guide for details (constraints, etc.).</span>

<span class="sd">        :param ssc:  StreamingContext object.</span>
<span class="sd">        :param topics:  list of topic_name to consume.</span>
<span class="sd">        :param kafkaParams: Additional params for Kafka.</span>
<span class="sd">        :param fromOffsets: Per-topic/partition Kafka offsets defining the (inclusive) starting</span>
<span class="sd">                            point of the stream.</span>
<span class="sd">        :param keyDecoder:  A function used to decode key (default is utf8_decoder).</span>
<span class="sd">        :param valueDecoder:  A function used to decode value (default is utf8_decoder).</span>
<span class="sd">        :return: A DStream object</span>
<span class="sd">        &quot;&quot;&quot;</span>
        <span class="k">if</span> <span class="n">fromOffsets</span> <span class="ow">is</span> <span class="bp">None</span><span class="p">:</span>
            <span class="n">fromOffsets</span> <span class="o">=</span> <span class="nb">dict</span><span class="p">()</span>
        <span class="k">if</span> <span class="ow">not</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">topics</span><span class="p">,</span> <span class="nb">list</span><span class="p">):</span>
            <span class="k">raise</span> <span class="ne">TypeError</span><span class="p">(</span><span class="s">&quot;topics should be list&quot;</span><span class="p">)</span>
        <span class="k">if</span> <span class="ow">not</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">kafkaParams</span><span class="p">,</span> <span class="nb">dict</span><span class="p">):</span>
            <span class="k">raise</span> <span class="ne">TypeError</span><span class="p">(</span><span class="s">&quot;kafkaParams should be dict&quot;</span><span class="p">)</span>

        <span class="k">try</span><span class="p">:</span>
            <span class="n">helperClass</span> <span class="o">=</span> <span class="n">ssc</span><span class="o">.</span><span class="n">_jvm</span><span class="o">.</span><span class="n">java</span><span class="o">.</span><span class="n">lang</span><span class="o">.</span><span class="n">Thread</span><span class="o">.</span><span class="n">currentThread</span><span class="p">()</span><span class="o">.</span><span class="n">getContextClassLoader</span><span class="p">()</span> \
                <span class="o">.</span><span class="n">loadClass</span><span class="p">(</span><span class="s">&quot;org.apache.spark.streaming.kafka.KafkaUtilsPythonHelper&quot;</span><span class="p">)</span>
            <span class="n">helper</span> <span class="o">=</span> <span class="n">helperClass</span><span class="o">.</span><span class="n">newInstance</span><span class="p">()</span>

            <span class="n">jfromOffsets</span> <span class="o">=</span> <span class="nb">dict</span><span class="p">([(</span><span class="n">k</span><span class="o">.</span><span class="n">_jTopicAndPartition</span><span class="p">(</span><span class="n">helper</span><span class="p">),</span>
                                  <span class="n">v</span><span class="p">)</span> <span class="k">for</span> <span class="p">(</span><span class="n">k</span><span class="p">,</span> <span class="n">v</span><span class="p">)</span> <span class="ow">in</span> <span class="n">fromOffsets</span><span class="o">.</span><span class="n">items</span><span class="p">()])</span>
            <span class="n">jstream</span> <span class="o">=</span> <span class="n">helper</span><span class="o">.</span><span class="n">createDirectStream</span><span class="p">(</span><span class="n">ssc</span><span class="o">.</span><span class="n">_jssc</span><span class="p">,</span> <span class="n">kafkaParams</span><span class="p">,</span> <span class="nb">set</span><span class="p">(</span><span class="n">topics</span><span class="p">),</span> <span class="n">jfromOffsets</span><span class="p">)</span>
        <span class="k">except</span> <span class="n">Py4JJavaError</span> <span class="k">as</span> <span class="n">e</span><span class="p">:</span>
            <span class="k">if</span> <span class="s">&#39;ClassNotFoundException&#39;</span> <span class="ow">in</span> <span class="nb">str</span><span class="p">(</span><span class="n">e</span><span class="o">.</span><span class="n">java_exception</span><span class="p">):</span>
                <span class="n">KafkaUtils</span><span class="o">.</span><span class="n">_printErrorMsg</span><span class="p">(</span><span class="n">ssc</span><span class="o">.</span><span class="n">sparkContext</span><span class="p">)</span>
            <span class="k">raise</span> <span class="n">e</span>

        <span class="n">ser</span> <span class="o">=</span> <span class="n">PairDeserializer</span><span class="p">(</span><span class="n">NoOpSerializer</span><span class="p">(),</span> <span class="n">NoOpSerializer</span><span class="p">())</span>
        <span class="n">stream</span> <span class="o">=</span> <span class="n">DStream</span><span class="p">(</span><span class="n">jstream</span><span class="p">,</span> <span class="n">ssc</span><span class="p">,</span> <span class="n">ser</span><span class="p">)</span> \
            <span class="o">.</span><span class="n">map</span><span class="p">(</span><span class="k">lambda</span> <span class="n">k_v</span><span class="p">:</span> <span class="p">(</span><span class="n">keyDecoder</span><span class="p">(</span><span class="n">k_v</span><span class="p">[</span><span class="mi">0</span><span class="p">]),</span> <span class="n">valueDecoder</span><span class="p">(</span><span class="n">k_v</span><span class="p">[</span><span class="mi">1</span><span class="p">])))</span>
        <span class="k">return</span> <span class="n">KafkaDStream</span><span class="p">(</span><span class="n">stream</span><span class="o">.</span><span class="n">_jdstream</span><span class="p">,</span> <span class="n">ssc</span><span class="p">,</span> <span class="n">stream</span><span class="o">.</span><span class="n">_jrdd_deserializer</span><span class="p">)</span>
</div>
    <span class="nd">@staticmethod</span>
<div class="viewcode-block" id="KafkaUtils.createRDD"><a class="viewcode-back" href="../../../pyspark.streaming.html#pyspark.streaming.kafka.KafkaUtils.createRDD">[docs]</a>    <span class="k">def</span> <span class="nf">createRDD</span><span class="p">(</span><span class="n">sc</span><span class="p">,</span> <span class="n">kafkaParams</span><span class="p">,</span> <span class="n">offsetRanges</span><span class="p">,</span> <span class="n">leaders</span><span class="o">=</span><span class="bp">None</span><span class="p">,</span>
                  <span class="n">keyDecoder</span><span class="o">=</span><span class="n">utf8_decoder</span><span class="p">,</span> <span class="n">valueDecoder</span><span class="o">=</span><span class="n">utf8_decoder</span><span class="p">):</span>
        <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">        .. note:: Experimental</span>

<span class="sd">        Create a RDD from Kafka using offset ranges for each topic and partition.</span>

<span class="sd">        :param sc:  SparkContext object</span>
<span class="sd">        :param kafkaParams: Additional params for Kafka</span>
<span class="sd">        :param offsetRanges:  list of offsetRange to specify topic:partition:[start, end) to consume</span>
<span class="sd">        :param leaders: Kafka brokers for each TopicAndPartition in offsetRanges.  May be an empty</span>
<span class="sd">            map, in which case leaders will be looked up on the driver.</span>
<span class="sd">        :param keyDecoder:  A function used to decode key (default is utf8_decoder)</span>
<span class="sd">        :param valueDecoder:  A function used to decode value (default is utf8_decoder)</span>
<span class="sd">        :return: A RDD object</span>
<span class="sd">        &quot;&quot;&quot;</span>
        <span class="k">if</span> <span class="n">leaders</span> <span class="ow">is</span> <span class="bp">None</span><span class="p">:</span>
            <span class="n">leaders</span> <span class="o">=</span> <span class="nb">dict</span><span class="p">()</span>
        <span class="k">if</span> <span class="ow">not</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">kafkaParams</span><span class="p">,</span> <span class="nb">dict</span><span class="p">):</span>
            <span class="k">raise</span> <span class="ne">TypeError</span><span class="p">(</span><span class="s">&quot;kafkaParams should be dict&quot;</span><span class="p">)</span>
        <span class="k">if</span> <span class="ow">not</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">offsetRanges</span><span class="p">,</span> <span class="nb">list</span><span class="p">):</span>
            <span class="k">raise</span> <span class="ne">TypeError</span><span class="p">(</span><span class="s">&quot;offsetRanges should be list&quot;</span><span class="p">)</span>

        <span class="k">try</span><span class="p">:</span>
            <span class="n">helperClass</span> <span class="o">=</span> <span class="n">sc</span><span class="o">.</span><span class="n">_jvm</span><span class="o">.</span><span class="n">java</span><span class="o">.</span><span class="n">lang</span><span class="o">.</span><span class="n">Thread</span><span class="o">.</span><span class="n">currentThread</span><span class="p">()</span><span class="o">.</span><span class="n">getContextClassLoader</span><span class="p">()</span> \
                <span class="o">.</span><span class="n">loadClass</span><span class="p">(</span><span class="s">&quot;org.apache.spark.streaming.kafka.KafkaUtilsPythonHelper&quot;</span><span class="p">)</span>
            <span class="n">helper</span> <span class="o">=</span> <span class="n">helperClass</span><span class="o">.</span><span class="n">newInstance</span><span class="p">()</span>
            <span class="n">joffsetRanges</span> <span class="o">=</span> <span class="p">[</span><span class="n">o</span><span class="o">.</span><span class="n">_jOffsetRange</span><span class="p">(</span><span class="n">helper</span><span class="p">)</span> <span class="k">for</span> <span class="n">o</span> <span class="ow">in</span> <span class="n">offsetRanges</span><span class="p">]</span>
            <span class="n">jleaders</span> <span class="o">=</span> <span class="nb">dict</span><span class="p">([(</span><span class="n">k</span><span class="o">.</span><span class="n">_jTopicAndPartition</span><span class="p">(</span><span class="n">helper</span><span class="p">),</span>
                              <span class="n">v</span><span class="o">.</span><span class="n">_jBroker</span><span class="p">(</span><span class="n">helper</span><span class="p">))</span> <span class="k">for</span> <span class="p">(</span><span class="n">k</span><span class="p">,</span> <span class="n">v</span><span class="p">)</span> <span class="ow">in</span> <span class="n">leaders</span><span class="o">.</span><span class="n">items</span><span class="p">()])</span>
            <span class="n">jrdd</span> <span class="o">=</span> <span class="n">helper</span><span class="o">.</span><span class="n">createRDD</span><span class="p">(</span><span class="n">sc</span><span class="o">.</span><span class="n">_jsc</span><span class="p">,</span> <span class="n">kafkaParams</span><span class="p">,</span> <span class="n">joffsetRanges</span><span class="p">,</span> <span class="n">jleaders</span><span class="p">)</span>
        <span class="k">except</span> <span class="n">Py4JJavaError</span> <span class="k">as</span> <span class="n">e</span><span class="p">:</span>
            <span class="k">if</span> <span class="s">&#39;ClassNotFoundException&#39;</span> <span class="ow">in</span> <span class="nb">str</span><span class="p">(</span><span class="n">e</span><span class="o">.</span><span class="n">java_exception</span><span class="p">):</span>
                <span class="n">KafkaUtils</span><span class="o">.</span><span class="n">_printErrorMsg</span><span class="p">(</span><span class="n">sc</span><span class="p">)</span>
            <span class="k">raise</span> <span class="n">e</span>

        <span class="n">ser</span> <span class="o">=</span> <span class="n">PairDeserializer</span><span class="p">(</span><span class="n">NoOpSerializer</span><span class="p">(),</span> <span class="n">NoOpSerializer</span><span class="p">())</span>
        <span class="n">rdd</span> <span class="o">=</span> <span class="n">RDD</span><span class="p">(</span><span class="n">jrdd</span><span class="p">,</span> <span class="n">sc</span><span class="p">,</span> <span class="n">ser</span><span class="p">)</span><span class="o">.</span><span class="n">map</span><span class="p">(</span><span class="k">lambda</span> <span class="n">k_v</span><span class="p">:</span> <span class="p">(</span><span class="n">keyDecoder</span><span class="p">(</span><span class="n">k_v</span><span class="p">[</span><span class="mi">0</span><span class="p">]),</span> <span class="n">valueDecoder</span><span class="p">(</span><span class="n">k_v</span><span class="p">[</span><span class="mi">1</span><span class="p">])))</span>
        <span class="k">return</span> <span class="n">KafkaRDD</span><span class="p">(</span><span class="n">rdd</span><span class="o">.</span><span class="n">_jrdd</span><span class="p">,</span> <span class="n">rdd</span><span class="o">.</span><span class="n">ctx</span><span class="p">,</span> <span class="n">rdd</span><span class="o">.</span><span class="n">_jrdd_deserializer</span><span class="p">)</span>
</div>
    <span class="nd">@staticmethod</span>
    <span class="k">def</span> <span class="nf">_printErrorMsg</span><span class="p">(</span><span class="n">sc</span><span class="p">):</span>
        <span class="k">print</span><span class="p">(</span><span class="s">&quot;&quot;&quot;</span>
<span class="s">________________________________________________________________________________________________</span>

<span class="s">  Spark Streaming&#39;s Kafka libraries not found in class path. Try one of the following.</span>

<span class="s">  1. Include the Kafka library and its dependencies with in the</span>
<span class="s">     spark-submit command as</span>

<span class="s">     $ bin/spark-submit --packages org.apache.spark:spark-streaming-kafka:</span><span class="si">%s</span><span class="s"> ...</span>

<span class="s">  2. Download the JAR of the artifact from Maven Central http://search.maven.org/,</span>
<span class="s">     Group Id = org.apache.spark, Artifact Id = spark-streaming-kafka-assembly, Version = </span><span class="si">%s</span><span class="s">.</span>
<span class="s">     Then, include the jar in the spark-submit command as</span>

<span class="s">     $ bin/spark-submit --jars &lt;spark-streaming-kafka-assembly.jar&gt; ...</span>

<span class="s">________________________________________________________________________________________________</span>

<span class="s">&quot;&quot;&quot;</span> <span class="o">%</span> <span class="p">(</span><span class="n">sc</span><span class="o">.</span><span class="n">version</span><span class="p">,</span> <span class="n">sc</span><span class="o">.</span><span class="n">version</span><span class="p">))</span>

</div>
<div class="viewcode-block" id="OffsetRange"><a class="viewcode-back" href="../../../pyspark.streaming.html#pyspark.streaming.kafka.OffsetRange">[docs]</a><span class="k">class</span> <span class="nc">OffsetRange</span><span class="p">(</span><span class="nb">object</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">    Represents a range of offsets from a single Kafka TopicAndPartition.</span>
<span class="sd">    &quot;&quot;&quot;</span>

    <span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">topic</span><span class="p">,</span> <span class="n">partition</span><span class="p">,</span> <span class="n">fromOffset</span><span class="p">,</span> <span class="n">untilOffset</span><span class="p">):</span>
        <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">        Create a OffsetRange to represent  range of offsets</span>
<span class="sd">        :param topic: Kafka topic name.</span>
<span class="sd">        :param partition: Kafka partition id.</span>
<span class="sd">        :param fromOffset: Inclusive starting offset.</span>
<span class="sd">        :param untilOffset: Exclusive ending offset.</span>
<span class="sd">        &quot;&quot;&quot;</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">topic</span> <span class="o">=</span> <span class="n">topic</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">partition</span> <span class="o">=</span> <span class="n">partition</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">fromOffset</span> <span class="o">=</span> <span class="n">fromOffset</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">untilOffset</span> <span class="o">=</span> <span class="n">untilOffset</span>

    <span class="k">def</span> <span class="nf">__eq__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">):</span>
        <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">other</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">__class__</span><span class="p">):</span>
            <span class="k">return</span> <span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">topic</span> <span class="o">==</span> <span class="n">other</span><span class="o">.</span><span class="n">topic</span>
                    <span class="ow">and</span> <span class="bp">self</span><span class="o">.</span><span class="n">partition</span> <span class="o">==</span> <span class="n">other</span><span class="o">.</span><span class="n">partition</span>
                    <span class="ow">and</span> <span class="bp">self</span><span class="o">.</span><span class="n">fromOffset</span> <span class="o">==</span> <span class="n">other</span><span class="o">.</span><span class="n">fromOffset</span>
                    <span class="ow">and</span> <span class="bp">self</span><span class="o">.</span><span class="n">untilOffset</span> <span class="o">==</span> <span class="n">other</span><span class="o">.</span><span class="n">untilOffset</span><span class="p">)</span>
        <span class="k">else</span><span class="p">:</span>
            <span class="k">return</span> <span class="bp">False</span>

    <span class="k">def</span> <span class="nf">__ne__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">):</span>
        <span class="k">return</span> <span class="ow">not</span> <span class="bp">self</span><span class="o">.</span><span class="n">__eq__</span><span class="p">(</span><span class="n">other</span><span class="p">)</span>

    <span class="k">def</span> <span class="nf">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
        <span class="k">return</span> <span class="s">&quot;OffsetRange(topic: </span><span class="si">%s</span><span class="s">, partition: </span><span class="si">%d</span><span class="s">, range: [</span><span class="si">%d</span><span class="s"> -&gt; </span><span class="si">%d</span><span class="s">]&quot;</span> \
               <span class="o">%</span> <span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">topic</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">partition</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">fromOffset</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">untilOffset</span><span class="p">)</span>

    <span class="k">def</span> <span class="nf">_jOffsetRange</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">helper</span><span class="p">):</span>
        <span class="k">return</span> <span class="n">helper</span><span class="o">.</span><span class="n">createOffsetRange</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">topic</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">partition</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">fromOffset</span><span class="p">,</span>
                                        <span class="bp">self</span><span class="o">.</span><span class="n">untilOffset</span><span class="p">)</span>

</div>
<div class="viewcode-block" id="TopicAndPartition"><a class="viewcode-back" href="../../../pyspark.streaming.html#pyspark.streaming.kafka.TopicAndPartition">[docs]</a><span class="k">class</span> <span class="nc">TopicAndPartition</span><span class="p">(</span><span class="nb">object</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">    Represents a specific top and partition for Kafka.</span>
<span class="sd">    &quot;&quot;&quot;</span>

    <span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">topic</span><span class="p">,</span> <span class="n">partition</span><span class="p">):</span>
        <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">        Create a Python TopicAndPartition to map to the Java related object</span>
<span class="sd">        :param topic: Kafka topic name.</span>
<span class="sd">        :param partition: Kafka partition id.</span>
<span class="sd">        &quot;&quot;&quot;</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">_topic</span> <span class="o">=</span> <span class="n">topic</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">_partition</span> <span class="o">=</span> <span class="n">partition</span>

    <span class="k">def</span> <span class="nf">_jTopicAndPartition</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">helper</span><span class="p">):</span>
        <span class="k">return</span> <span class="n">helper</span><span class="o">.</span><span class="n">createTopicAndPartition</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_topic</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">_partition</span><span class="p">)</span>

</div>
<div class="viewcode-block" id="Broker"><a class="viewcode-back" href="../../../pyspark.streaming.html#pyspark.streaming.kafka.Broker">[docs]</a><span class="k">class</span> <span class="nc">Broker</span><span class="p">(</span><span class="nb">object</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">    Represent the host and port info for a Kafka broker.</span>
<span class="sd">    &quot;&quot;&quot;</span>

    <span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">host</span><span class="p">,</span> <span class="n">port</span><span class="p">):</span>
        <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">        Create a Python Broker to map to the Java related object.</span>
<span class="sd">        :param host: Broker&#39;s hostname.</span>
<span class="sd">        :param port: Broker&#39;s port.</span>
<span class="sd">        &quot;&quot;&quot;</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">_host</span> <span class="o">=</span> <span class="n">host</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">_port</span> <span class="o">=</span> <span class="n">port</span>

    <span class="k">def</span> <span class="nf">_jBroker</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">helper</span><span class="p">):</span>
        <span class="k">return</span> <span class="n">helper</span><span class="o">.</span><span class="n">createBroker</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_host</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">_port</span><span class="p">)</span>

</div>
<span class="k">class</span> <span class="nc">KafkaRDD</span><span class="p">(</span><span class="n">RDD</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">    A Python wrapper of KafkaRDD, to provide additional information on normal RDD.</span>
<span class="sd">    &quot;&quot;&quot;</span>

    <span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">jrdd</span><span class="p">,</span> <span class="n">ctx</span><span class="p">,</span> <span class="n">jrdd_deserializer</span><span class="p">):</span>
        <span class="n">RDD</span><span class="o">.</span><span class="n">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">jrdd</span><span class="p">,</span> <span class="n">ctx</span><span class="p">,</span> <span class="n">jrdd_deserializer</span><span class="p">)</span>

    <span class="k">def</span> <span class="nf">offsetRanges</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
        <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">        Get the OffsetRange of specific KafkaRDD.</span>
<span class="sd">        :return: A list of OffsetRange</span>
<span class="sd">        &quot;&quot;&quot;</span>
        <span class="k">try</span><span class="p">:</span>
            <span class="n">helperClass</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">ctx</span><span class="o">.</span><span class="n">_jvm</span><span class="o">.</span><span class="n">java</span><span class="o">.</span><span class="n">lang</span><span class="o">.</span><span class="n">Thread</span><span class="o">.</span><span class="n">currentThread</span><span class="p">()</span><span class="o">.</span><span class="n">getContextClassLoader</span><span class="p">()</span> \
                <span class="o">.</span><span class="n">loadClass</span><span class="p">(</span><span class="s">&quot;org.apache.spark.streaming.kafka.KafkaUtilsPythonHelper&quot;</span><span class="p">)</span>
            <span class="n">helper</span> <span class="o">=</span> <span class="n">helperClass</span><span class="o">.</span><span class="n">newInstance</span><span class="p">()</span>
            <span class="n">joffsetRanges</span> <span class="o">=</span> <span class="n">helper</span><span class="o">.</span><span class="n">offsetRangesOfKafkaRDD</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_jrdd</span><span class="o">.</span><span class="n">rdd</span><span class="p">())</span>
        <span class="k">except</span> <span class="n">Py4JJavaError</span> <span class="k">as</span> <span class="n">e</span><span class="p">:</span>
            <span class="k">if</span> <span class="s">&#39;ClassNotFoundException&#39;</span> <span class="ow">in</span> <span class="nb">str</span><span class="p">(</span><span class="n">e</span><span class="o">.</span><span class="n">java_exception</span><span class="p">):</span>
                <span class="n">KafkaUtils</span><span class="o">.</span><span class="n">_printErrorMsg</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">ctx</span><span class="p">)</span>
            <span class="k">raise</span> <span class="n">e</span>

        <span class="n">ranges</span> <span class="o">=</span> <span class="p">[</span><span class="n">OffsetRange</span><span class="p">(</span><span class="n">o</span><span class="o">.</span><span class="n">topic</span><span class="p">(),</span> <span class="n">o</span><span class="o">.</span><span class="n">partition</span><span class="p">(),</span> <span class="n">o</span><span class="o">.</span><span class="n">fromOffset</span><span class="p">(),</span> <span class="n">o</span><span class="o">.</span><span class="n">untilOffset</span><span class="p">())</span>
                  <span class="k">for</span> <span class="n">o</span> <span class="ow">in</span> <span class="n">joffsetRanges</span><span class="p">]</span>
        <span class="k">return</span> <span class="n">ranges</span>


<span class="k">class</span> <span class="nc">KafkaDStream</span><span class="p">(</span><span class="n">DStream</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">    A Python wrapper of KafkaDStream</span>
<span class="sd">    &quot;&quot;&quot;</span>

    <span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">jdstream</span><span class="p">,</span> <span class="n">ssc</span><span class="p">,</span> <span class="n">jrdd_deserializer</span><span class="p">):</span>
        <span class="n">DStream</span><span class="o">.</span><span class="n">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">jdstream</span><span class="p">,</span> <span class="n">ssc</span><span class="p">,</span> <span class="n">jrdd_deserializer</span><span class="p">)</span>

    <span class="k">def</span> <span class="nf">foreachRDD</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">func</span><span class="p">):</span>
        <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">        Apply a function to each RDD in this DStream.</span>
<span class="sd">        &quot;&quot;&quot;</span>
        <span class="k">if</span> <span class="n">func</span><span class="o">.</span><span class="n">__code__</span><span class="o">.</span><span class="n">co_argcount</span> <span class="o">==</span> <span class="mi">1</span><span class="p">:</span>
            <span class="n">old_func</span> <span class="o">=</span> <span class="n">func</span>
            <span class="n">func</span> <span class="o">=</span> <span class="k">lambda</span> <span class="n">r</span><span class="p">,</span> <span class="n">rdd</span><span class="p">:</span> <span class="n">old_func</span><span class="p">(</span><span class="n">rdd</span><span class="p">)</span>
        <span class="n">jfunc</span> <span class="o">=</span> <span class="n">TransformFunction</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_sc</span><span class="p">,</span> <span class="n">func</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">_jrdd_deserializer</span><span class="p">)</span> \
            <span class="o">.</span><span class="n">rdd_wrapper</span><span class="p">(</span><span class="k">lambda</span> <span class="n">jrdd</span><span class="p">,</span> <span class="n">ctx</span><span class="p">,</span> <span class="n">ser</span><span class="p">:</span> <span class="n">KafkaRDD</span><span class="p">(</span><span class="n">jrdd</span><span class="p">,</span> <span class="n">ctx</span><span class="p">,</span> <span class="n">ser</span><span class="p">))</span>
        <span class="n">api</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_ssc</span><span class="o">.</span><span class="n">_jvm</span><span class="o">.</span><span class="n">PythonDStream</span>
        <span class="n">api</span><span class="o">.</span><span class="n">callForeachRDD</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_jdstream</span><span class="p">,</span> <span class="n">jfunc</span><span class="p">)</span>

    <span class="k">def</span> <span class="nf">transform</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">func</span><span class="p">):</span>
        <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">        Return a new DStream in which each RDD is generated by applying a function</span>
<span class="sd">        on each RDD of this DStream.</span>

<span class="sd">        `func` can have one argument of `rdd`, or have two arguments of</span>
<span class="sd">        (`time`, `rdd`)</span>
<span class="sd">        &quot;&quot;&quot;</span>
        <span class="k">if</span> <span class="n">func</span><span class="o">.</span><span class="n">__code__</span><span class="o">.</span><span class="n">co_argcount</span> <span class="o">==</span> <span class="mi">1</span><span class="p">:</span>
            <span class="n">oldfunc</span> <span class="o">=</span> <span class="n">func</span>
            <span class="n">func</span> <span class="o">=</span> <span class="k">lambda</span> <span class="n">t</span><span class="p">,</span> <span class="n">rdd</span><span class="p">:</span> <span class="n">oldfunc</span><span class="p">(</span><span class="n">rdd</span><span class="p">)</span>
        <span class="k">assert</span> <span class="n">func</span><span class="o">.</span><span class="n">__code__</span><span class="o">.</span><span class="n">co_argcount</span> <span class="o">==</span> <span class="mi">2</span><span class="p">,</span> <span class="s">&quot;func should take one or two arguments&quot;</span>

        <span class="k">return</span> <span class="n">KafkaTransformedDStream</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">func</span><span class="p">)</span>


<span class="k">class</span> <span class="nc">KafkaTransformedDStream</span><span class="p">(</span><span class="n">TransformedDStream</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">    Kafka specific wrapper of TransformedDStream to transform on Kafka RDD.</span>
<span class="sd">    &quot;&quot;&quot;</span>

    <span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">prev</span><span class="p">,</span> <span class="n">func</span><span class="p">):</span>
        <span class="n">TransformedDStream</span><span class="o">.</span><span class="n">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">prev</span><span class="p">,</span> <span class="n">func</span><span class="p">)</span>

    <span class="nd">@property</span>
    <span class="k">def</span> <span class="nf">_jdstream</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
        <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">_jdstream_val</span> <span class="ow">is</span> <span class="ow">not</span> <span class="bp">None</span><span class="p">:</span>
            <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_jdstream_val</span>

        <span class="n">jfunc</span> <span class="o">=</span> <span class="n">TransformFunction</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_sc</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">func</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">prev</span><span class="o">.</span><span class="n">_jrdd_deserializer</span><span class="p">)</span> \
            <span class="o">.</span><span class="n">rdd_wrapper</span><span class="p">(</span><span class="k">lambda</span> <span class="n">jrdd</span><span class="p">,</span> <span class="n">ctx</span><span class="p">,</span> <span class="n">ser</span><span class="p">:</span> <span class="n">KafkaRDD</span><span class="p">(</span><span class="n">jrdd</span><span class="p">,</span> <span class="n">ctx</span><span class="p">,</span> <span class="n">ser</span><span class="p">))</span>
        <span class="n">dstream</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_sc</span><span class="o">.</span><span class="n">_jvm</span><span class="o">.</span><span class="n">PythonTransformedDStream</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">prev</span><span class="o">.</span><span class="n">_jdstream</span><span class="o">.</span><span class="n">dstream</span><span class="p">(),</span> <span class="n">jfunc</span><span class="p">)</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">_jdstream_val</span> <span class="o">=</span> <span class="n">dstream</span><span class="o">.</span><span class="n">asJavaDStream</span><span class="p">()</span>
        <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_jdstream_val</span>
</pre></div>

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