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<h1>Source code for pyspark.streaming.context</h1><div class="highlight"><pre>
<span></span><span class="c1">#</span>
<span class="c1"># Licensed to the Apache Software Foundation (ASF) under one or more</span>
<span class="c1"># contributor license agreements. See the NOTICE file distributed with</span>
<span class="c1"># this work for additional information regarding copyright ownership.</span>
<span class="c1"># The ASF licenses this file to You under the Apache License, Version 2.0</span>
<span class="c1"># (the &quot;License&quot;); you may not use this file except in compliance with</span>
<span class="c1"># the License. You may obtain a copy of the License at</span>
<span class="c1">#</span>
<span class="c1"># http://www.apache.org/licenses/LICENSE-2.0</span>
<span class="c1">#</span>
<span class="c1"># Unless required by applicable law or agreed to in writing, software</span>
<span class="c1"># distributed under the License is distributed on an &quot;AS IS&quot; BASIS,</span>
<span class="c1"># WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.</span>
<span class="c1"># See the License for the specific language governing permissions and</span>
<span class="c1"># limitations under the License.</span>
<span class="c1">#</span>
<span class="kn">from</span> <span class="nn">typing</span> <span class="kn">import</span> <span class="n">Any</span><span class="p">,</span> <span class="n">Callable</span><span class="p">,</span> <span class="n">List</span><span class="p">,</span> <span class="n">Optional</span><span class="p">,</span> <span class="n">TypeVar</span>
<span class="kn">from</span> <span class="nn">py4j.java_gateway</span> <span class="kn">import</span> <span class="n">java_import</span><span class="p">,</span> <span class="n">is_instance_of</span><span class="p">,</span> <span class="n">JavaObject</span>
<span class="kn">from</span> <span class="nn">pyspark</span> <span class="kn">import</span> <span class="n">RDD</span><span class="p">,</span> <span class="n">SparkConf</span>
<span class="kn">from</span> <span class="nn">pyspark.serializers</span> <span class="kn">import</span> <span class="n">NoOpSerializer</span><span class="p">,</span> <span class="n">UTF8Deserializer</span><span class="p">,</span> <span class="n">CloudPickleSerializer</span>
<span class="kn">from</span> <span class="nn">pyspark.context</span> <span class="kn">import</span> <span class="n">SparkContext</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.streaming.dstream</span> <span class="kn">import</span> <span class="n">DStream</span>
<span class="kn">from</span> <span class="nn">pyspark.streaming.listener</span> <span class="kn">import</span> <span class="n">StreamingListener</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="p">,</span> <span class="n">TransformFunctionSerializer</span>
<span class="n">__all__</span> <span class="o">=</span> <span class="p">[</span><span class="s2">&quot;StreamingContext&quot;</span><span class="p">]</span>
<span class="n">T</span> <span class="o">=</span> <span class="n">TypeVar</span><span class="p">(</span><span class="s2">&quot;T&quot;</span><span class="p">)</span>
<div class="viewcode-block" id="StreamingContext"><a class="viewcode-back" href="../../../reference/api/pyspark.streaming.StreamingContext.html#pyspark.streaming.StreamingContext">[docs]</a><span class="k">class</span> <span class="nc">StreamingContext</span><span class="p">:</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Main entry point for Spark Streaming functionality. A StreamingContext</span>
<span class="sd"> represents the connection to a Spark cluster, and can be used to create</span>
<span class="sd"> :class:`DStream` various input sources. It can be from an existing :class:`SparkContext`.</span>
<span class="sd"> After creating and transforming DStreams, the streaming computation can</span>
<span class="sd"> be started and stopped using `context.start()` and `context.stop()`,</span>
<span class="sd"> respectively. `context.awaitTermination()` allows the current thread</span>
<span class="sd"> to wait for the termination of the context by `stop()` or by an exception.</span>
<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<span class="sd"> sparkContext : :class:`SparkContext`</span>
<span class="sd"> SparkContext object.</span>
<span class="sd"> batchDuration : int, optional</span>
<span class="sd"> the time interval (in seconds) at which streaming</span>
<span class="sd"> data will be divided into batches</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="n">_transformerSerializer</span> <span class="o">=</span> <span class="kc">None</span>
<span class="c1"># Reference to a currently active StreamingContext</span>
<span class="n">_activeContext</span> <span class="o">=</span> <span class="kc">None</span>
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span>
<span class="bp">self</span><span class="p">,</span>
<span class="n">sparkContext</span><span class="p">:</span> <span class="n">SparkContext</span><span class="p">,</span>
<span class="n">batchDuration</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">int</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
<span class="n">jssc</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">JavaObject</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
<span class="p">):</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_sc</span> <span class="o">=</span> <span class="n">sparkContext</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_jvm</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="bp">self</span><span class="o">.</span><span class="n">_jssc</span> <span class="o">=</span> <span class="n">jssc</span> <span class="ow">or</span> <span class="bp">self</span><span class="o">.</span><span class="n">_initialize_context</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">batchDuration</span><span class="p">)</span>
<span class="k">def</span> <span class="nf">_initialize_context</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">sc</span><span class="p">:</span> <span class="n">SparkContext</span><span class="p">,</span> <span class="n">duration</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">int</span><span class="p">])</span> <span class="o">-&gt;</span> <span class="n">JavaObject</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_ensure_initialized</span><span class="p">()</span>
<span class="k">assert</span> <span class="bp">self</span><span class="o">.</span><span class="n">_jvm</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span> <span class="ow">and</span> <span class="n">duration</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_jvm</span><span class="o">.</span><span class="n">JavaStreamingContext</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="bp">self</span><span class="o">.</span><span class="n">_jduration</span><span class="p">(</span><span class="n">duration</span><span class="p">))</span>
<span class="k">def</span> <span class="nf">_jduration</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">seconds</span><span class="p">:</span> <span class="nb">int</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">JavaObject</span><span class="p">:</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Create Duration object given number of seconds</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">assert</span> <span class="bp">self</span><span class="o">.</span><span class="n">_jvm</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_jvm</span><span class="o">.</span><span class="n">Duration</span><span class="p">(</span><span class="nb">int</span><span class="p">(</span><span class="n">seconds</span> <span class="o">*</span> <span class="mi">1000</span><span class="p">))</span>
<span class="nd">@classmethod</span>
<span class="k">def</span> <span class="nf">_ensure_initialized</span><span class="p">(</span><span class="bp">cls</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="kc">None</span><span class="p">:</span>
<span class="n">SparkContext</span><span class="o">.</span><span class="n">_ensure_initialized</span><span class="p">()</span>
<span class="n">gw</span> <span class="o">=</span> <span class="n">SparkContext</span><span class="o">.</span><span class="n">_gateway</span>
<span class="k">assert</span> <span class="n">gw</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span>
<span class="n">java_import</span><span class="p">(</span><span class="n">gw</span><span class="o">.</span><span class="n">jvm</span><span class="p">,</span> <span class="s2">&quot;org.apache.spark.streaming.*&quot;</span><span class="p">)</span>
<span class="n">java_import</span><span class="p">(</span><span class="n">gw</span><span class="o">.</span><span class="n">jvm</span><span class="p">,</span> <span class="s2">&quot;org.apache.spark.streaming.api.java.*&quot;</span><span class="p">)</span>
<span class="n">java_import</span><span class="p">(</span><span class="n">gw</span><span class="o">.</span><span class="n">jvm</span><span class="p">,</span> <span class="s2">&quot;org.apache.spark.streaming.api.python.*&quot;</span><span class="p">)</span>
<span class="kn">from</span> <span class="nn">pyspark.java_gateway</span> <span class="kn">import</span> <span class="n">ensure_callback_server_started</span>
<span class="n">ensure_callback_server_started</span><span class="p">(</span><span class="n">gw</span><span class="p">)</span>
<span class="c1"># register serializer for TransformFunction</span>
<span class="c1"># it happens before creating SparkContext when loading from checkpointing</span>
<span class="bp">cls</span><span class="o">.</span><span class="n">_transformerSerializer</span> <span class="o">=</span> <span class="n">TransformFunctionSerializer</span><span class="p">(</span>
<span class="n">SparkContext</span><span class="o">.</span><span class="n">_active_spark_context</span><span class="p">,</span>
<span class="n">CloudPickleSerializer</span><span class="p">(),</span>
<span class="n">gw</span><span class="p">,</span>
<span class="p">)</span>
<div class="viewcode-block" id="StreamingContext.getOrCreate"><a class="viewcode-back" href="../../../reference/api/pyspark.streaming.StreamingContext.getOrCreate.html#pyspark.streaming.StreamingContext.getOrCreate">[docs]</a> <span class="nd">@classmethod</span>
<span class="k">def</span> <span class="nf">getOrCreate</span><span class="p">(</span>
<span class="bp">cls</span><span class="p">,</span> <span class="n">checkpointPath</span><span class="p">:</span> <span class="nb">str</span><span class="p">,</span> <span class="n">setupFunc</span><span class="p">:</span> <span class="n">Callable</span><span class="p">[[],</span> <span class="s2">&quot;StreamingContext&quot;</span><span class="p">]</span>
<span class="p">)</span> <span class="o">-&gt;</span> <span class="s2">&quot;StreamingContext&quot;</span><span class="p">:</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Either recreate a StreamingContext from checkpoint data or create a new StreamingContext.</span>
<span class="sd"> If checkpoint data exists in the provided `checkpointPath`, then StreamingContext will be</span>
<span class="sd"> recreated from the checkpoint data. If the data does not exist, then the provided setupFunc</span>
<span class="sd"> will be used to create a new context.</span>
<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<span class="sd"> checkpointPath : str</span>
<span class="sd"> Checkpoint directory used in an earlier streaming program</span>
<span class="sd"> setupFunc : function</span>
<span class="sd"> Function to create a new context and setup DStreams</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="bp">cls</span><span class="o">.</span><span class="n">_ensure_initialized</span><span class="p">()</span>
<span class="n">gw</span> <span class="o">=</span> <span class="n">SparkContext</span><span class="o">.</span><span class="n">_gateway</span>
<span class="k">assert</span> <span class="n">gw</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span>
<span class="c1"># Check whether valid checkpoint information exists in the given path</span>
<span class="n">ssc_option</span> <span class="o">=</span> <span class="n">gw</span><span class="o">.</span><span class="n">jvm</span><span class="o">.</span><span class="n">StreamingContextPythonHelper</span><span class="p">()</span><span class="o">.</span><span class="n">tryRecoverFromCheckpoint</span><span class="p">(</span><span class="n">checkpointPath</span><span class="p">)</span>
<span class="k">if</span> <span class="n">ssc_option</span><span class="o">.</span><span class="n">isEmpty</span><span class="p">():</span>
<span class="n">ssc</span> <span class="o">=</span> <span class="n">setupFunc</span><span class="p">()</span>
<span class="n">ssc</span><span class="o">.</span><span class="n">checkpoint</span><span class="p">(</span><span class="n">checkpointPath</span><span class="p">)</span>
<span class="k">return</span> <span class="n">ssc</span>
<span class="n">jssc</span> <span class="o">=</span> <span class="n">gw</span><span class="o">.</span><span class="n">jvm</span><span class="o">.</span><span class="n">JavaStreamingContext</span><span class="p">(</span><span class="n">ssc_option</span><span class="o">.</span><span class="n">get</span><span class="p">())</span>
<span class="c1"># If there is already an active instance of Python SparkContext use it, or create a new one</span>
<span class="k">if</span> <span class="ow">not</span> <span class="n">SparkContext</span><span class="o">.</span><span class="n">_active_spark_context</span><span class="p">:</span>
<span class="n">jsc</span> <span class="o">=</span> <span class="n">jssc</span><span class="o">.</span><span class="n">sparkContext</span><span class="p">()</span>
<span class="n">conf</span> <span class="o">=</span> <span class="n">SparkConf</span><span class="p">(</span><span class="n">_jconf</span><span class="o">=</span><span class="n">jsc</span><span class="o">.</span><span class="n">getConf</span><span class="p">())</span>
<span class="n">SparkContext</span><span class="p">(</span><span class="n">conf</span><span class="o">=</span><span class="n">conf</span><span class="p">,</span> <span class="n">gateway</span><span class="o">=</span><span class="n">gw</span><span class="p">,</span> <span class="n">jsc</span><span class="o">=</span><span class="n">jsc</span><span class="p">)</span>
<span class="n">sc</span> <span class="o">=</span> <span class="n">SparkContext</span><span class="o">.</span><span class="n">_active_spark_context</span>
<span class="k">assert</span> <span class="n">sc</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span>
<span class="c1"># update ctx in serializer</span>
<span class="k">assert</span> <span class="bp">cls</span><span class="o">.</span><span class="n">_transformerSerializer</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span>
<span class="bp">cls</span><span class="o">.</span><span class="n">_transformerSerializer</span><span class="o">.</span><span class="n">ctx</span> <span class="o">=</span> <span class="n">sc</span>
<span class="k">return</span> <span class="n">StreamingContext</span><span class="p">(</span><span class="n">sc</span><span class="p">,</span> <span class="kc">None</span><span class="p">,</span> <span class="n">jssc</span><span class="p">)</span></div>
<div class="viewcode-block" id="StreamingContext.getActive"><a class="viewcode-back" href="../../../reference/api/pyspark.streaming.StreamingContext.getActive.html#pyspark.streaming.StreamingContext.getActive">[docs]</a> <span class="nd">@classmethod</span>
<span class="k">def</span> <span class="nf">getActive</span><span class="p">(</span><span class="bp">cls</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Optional</span><span class="p">[</span><span class="s2">&quot;StreamingContext&quot;</span><span class="p">]:</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Return either the currently active StreamingContext (i.e., if there is a context started</span>
<span class="sd"> but not stopped) or None.</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="n">activePythonContext</span> <span class="o">=</span> <span class="bp">cls</span><span class="o">.</span><span class="n">_activeContext</span>
<span class="k">if</span> <span class="n">activePythonContext</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
<span class="c1"># Verify that the current running Java StreamingContext is active and is the same one</span>
<span class="c1"># backing the supposedly active Python context</span>
<span class="n">activePythonContextJavaId</span> <span class="o">=</span> <span class="n">activePythonContext</span><span class="o">.</span><span class="n">_jssc</span><span class="o">.</span><span class="n">ssc</span><span class="p">()</span><span class="o">.</span><span class="n">hashCode</span><span class="p">()</span>
<span class="n">activeJvmContextOption</span> <span class="o">=</span> <span class="n">activePythonContext</span><span class="o">.</span><span class="n">_jvm</span><span class="o">.</span><span class="n">StreamingContext</span><span class="o">.</span><span class="n">getActive</span><span class="p">()</span>
<span class="k">if</span> <span class="n">activeJvmContextOption</span><span class="o">.</span><span class="n">isEmpty</span><span class="p">():</span>
<span class="bp">cls</span><span class="o">.</span><span class="n">_activeContext</span> <span class="o">=</span> <span class="kc">None</span>
<span class="k">elif</span> <span class="n">activeJvmContextOption</span><span class="o">.</span><span class="n">get</span><span class="p">()</span><span class="o">.</span><span class="n">hashCode</span><span class="p">()</span> <span class="o">!=</span> <span class="n">activePythonContextJavaId</span><span class="p">:</span>
<span class="bp">cls</span><span class="o">.</span><span class="n">_activeContext</span> <span class="o">=</span> <span class="kc">None</span>
<span class="k">raise</span> <span class="ne">RuntimeError</span><span class="p">(</span>
<span class="s2">&quot;JVM&#39;s active JavaStreamingContext is not the JavaStreamingContext &quot;</span>
<span class="s2">&quot;backing the action Python StreamingContext. This is unexpected.&quot;</span>
<span class="p">)</span>
<span class="k">return</span> <span class="bp">cls</span><span class="o">.</span><span class="n">_activeContext</span></div>
<div class="viewcode-block" id="StreamingContext.getActiveOrCreate"><a class="viewcode-back" href="../../../reference/api/pyspark.streaming.StreamingContext.getActiveOrCreate.html#pyspark.streaming.StreamingContext.getActiveOrCreate">[docs]</a> <span class="nd">@classmethod</span>
<span class="k">def</span> <span class="nf">getActiveOrCreate</span><span class="p">(</span>
<span class="bp">cls</span><span class="p">,</span> <span class="n">checkpointPath</span><span class="p">:</span> <span class="nb">str</span><span class="p">,</span> <span class="n">setupFunc</span><span class="p">:</span> <span class="n">Callable</span><span class="p">[[],</span> <span class="s2">&quot;StreamingContext&quot;</span><span class="p">]</span>
<span class="p">)</span> <span class="o">-&gt;</span> <span class="s2">&quot;StreamingContext&quot;</span><span class="p">:</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Either return the active StreamingContext (i.e. currently started but not stopped),</span>
<span class="sd"> or recreate a StreamingContext from checkpoint data or create a new StreamingContext</span>
<span class="sd"> using the provided setupFunc function. If the checkpointPath is None or does not contain</span>
<span class="sd"> valid checkpoint data, then setupFunc will be called to create a new context and setup</span>
<span class="sd"> DStreams.</span>
<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<span class="sd"> checkpointPath : str</span>
<span class="sd"> Checkpoint directory used in an earlier streaming program. Can be</span>
<span class="sd"> None if the intention is to always create a new context when there</span>
<span class="sd"> is no active context.</span>
<span class="sd"> setupFunc : function</span>
<span class="sd"> Function to create a new JavaStreamingContext and setup DStreams</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">if</span> <span class="ow">not</span> <span class="n">callable</span><span class="p">(</span><span class="n">setupFunc</span><span class="p">):</span>
<span class="k">raise</span> <span class="ne">TypeError</span><span class="p">(</span><span class="s2">&quot;setupFunc should be callable.&quot;</span><span class="p">)</span>
<span class="n">activeContext</span> <span class="o">=</span> <span class="bp">cls</span><span class="o">.</span><span class="n">getActive</span><span class="p">()</span>
<span class="k">if</span> <span class="n">activeContext</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
<span class="k">return</span> <span class="n">activeContext</span>
<span class="k">elif</span> <span class="n">checkpointPath</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
<span class="k">return</span> <span class="bp">cls</span><span class="o">.</span><span class="n">getOrCreate</span><span class="p">(</span><span class="n">checkpointPath</span><span class="p">,</span> <span class="n">setupFunc</span><span class="p">)</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">return</span> <span class="n">setupFunc</span><span class="p">()</span></div>
<span class="nd">@property</span>
<span class="k">def</span> <span class="nf">sparkContext</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">SparkContext</span><span class="p">:</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Return SparkContext which is associated with this StreamingContext.</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_sc</span>
<div class="viewcode-block" id="StreamingContext.start"><a class="viewcode-back" href="../../../reference/api/pyspark.streaming.StreamingContext.start.html#pyspark.streaming.StreamingContext.start">[docs]</a> <span class="k">def</span> <span class="nf">start</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="kc">None</span><span class="p">:</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Start the execution of the streams.</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_jssc</span><span class="o">.</span><span class="n">start</span><span class="p">()</span>
<span class="n">StreamingContext</span><span class="o">.</span><span class="n">_activeContext</span> <span class="o">=</span> <span class="bp">self</span></div>
<div class="viewcode-block" id="StreamingContext.awaitTermination"><a class="viewcode-back" href="../../../reference/api/pyspark.streaming.StreamingContext.awaitTermination.html#pyspark.streaming.StreamingContext.awaitTermination">[docs]</a> <span class="k">def</span> <span class="nf">awaitTermination</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">timeout</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">int</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="kc">None</span><span class="p">:</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Wait for the execution to stop.</span>
<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<span class="sd"> timeout : int, optional</span>
<span class="sd"> time to wait in seconds</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">if</span> <span class="n">timeout</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_jssc</span><span class="o">.</span><span class="n">awaitTermination</span><span class="p">()</span>
<span class="k">else</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_jssc</span><span class="o">.</span><span class="n">awaitTerminationOrTimeout</span><span class="p">(</span><span class="nb">int</span><span class="p">(</span><span class="n">timeout</span> <span class="o">*</span> <span class="mi">1000</span><span class="p">))</span></div>
<div class="viewcode-block" id="StreamingContext.awaitTerminationOrTimeout"><a class="viewcode-back" href="../../../reference/api/pyspark.streaming.StreamingContext.awaitTerminationOrTimeout.html#pyspark.streaming.StreamingContext.awaitTerminationOrTimeout">[docs]</a> <span class="k">def</span> <span class="nf">awaitTerminationOrTimeout</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">timeout</span><span class="p">:</span> <span class="nb">int</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="kc">None</span><span class="p">:</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Wait for the execution to stop. Return `true` if it&#39;s stopped; or</span>
<span class="sd"> throw the reported error during the execution; or `false` if the</span>
<span class="sd"> waiting time elapsed before returning from the method.</span>
<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<span class="sd"> timeout : int</span>
<span class="sd"> time to wait in seconds</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_jssc</span><span class="o">.</span><span class="n">awaitTerminationOrTimeout</span><span class="p">(</span><span class="nb">int</span><span class="p">(</span><span class="n">timeout</span> <span class="o">*</span> <span class="mi">1000</span><span class="p">))</span></div>
<div class="viewcode-block" id="StreamingContext.stop"><a class="viewcode-back" href="../../../reference/api/pyspark.streaming.StreamingContext.stop.html#pyspark.streaming.StreamingContext.stop">[docs]</a> <span class="k">def</span> <span class="nf">stop</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">stopSparkContext</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">True</span><span class="p">,</span> <span class="n">stopGraceFully</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="kc">None</span><span class="p">:</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Stop the execution of the streams, with option of ensuring all</span>
<span class="sd"> received data has been processed.</span>
<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<span class="sd"> stopSparkContext : bool, optional</span>
<span class="sd"> Stop the associated SparkContext or not</span>
<span class="sd"> stopGracefully : bool, optional</span>
<span class="sd"> Stop gracefully by waiting for the processing of all received</span>
<span class="sd"> data to be completed</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_jssc</span><span class="o">.</span><span class="n">stop</span><span class="p">(</span><span class="n">stopSparkContext</span><span class="p">,</span> <span class="n">stopGraceFully</span><span class="p">)</span>
<span class="n">StreamingContext</span><span class="o">.</span><span class="n">_activeContext</span> <span class="o">=</span> <span class="kc">None</span>
<span class="k">if</span> <span class="n">stopSparkContext</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_sc</span><span class="o">.</span><span class="n">stop</span><span class="p">()</span></div>
<div class="viewcode-block" id="StreamingContext.remember"><a class="viewcode-back" href="../../../reference/api/pyspark.streaming.StreamingContext.remember.html#pyspark.streaming.StreamingContext.remember">[docs]</a> <span class="k">def</span> <span class="nf">remember</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">duration</span><span class="p">:</span> <span class="nb">int</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="kc">None</span><span class="p">:</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Set each DStreams in this context to remember RDDs it generated</span>
<span class="sd"> in the last given duration. DStreams remember RDDs only for a</span>
<span class="sd"> limited duration of time and releases them for garbage collection.</span>
<span class="sd"> This method allows the developer to specify how long to remember</span>
<span class="sd"> the RDDs (if the developer wishes to query old data outside the</span>
<span class="sd"> DStream computation).</span>
<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<span class="sd"> duration : int</span>
<span class="sd"> Minimum duration (in seconds) that each DStream should remember its RDDs</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_jssc</span><span class="o">.</span><span class="n">remember</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_jduration</span><span class="p">(</span><span class="n">duration</span><span class="p">))</span></div>
<div class="viewcode-block" id="StreamingContext.checkpoint"><a class="viewcode-back" href="../../../reference/api/pyspark.streaming.StreamingContext.checkpoint.html#pyspark.streaming.StreamingContext.checkpoint">[docs]</a> <span class="k">def</span> <span class="nf">checkpoint</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">directory</span><span class="p">:</span> <span class="nb">str</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="kc">None</span><span class="p">:</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Sets the context to periodically checkpoint the DStream operations for master</span>
<span class="sd"> fault-tolerance. The graph will be checkpointed every batch interval.</span>
<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<span class="sd"> directory : str</span>
<span class="sd"> HDFS-compatible directory where the checkpoint data will be reliably stored</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_jssc</span><span class="o">.</span><span class="n">checkpoint</span><span class="p">(</span><span class="n">directory</span><span class="p">)</span></div>
<div class="viewcode-block" id="StreamingContext.socketTextStream"><a class="viewcode-back" href="../../../reference/api/pyspark.streaming.StreamingContext.socketTextStream.html#pyspark.streaming.StreamingContext.socketTextStream">[docs]</a> <span class="k">def</span> <span class="nf">socketTextStream</span><span class="p">(</span>
<span class="bp">self</span><span class="p">,</span> <span class="n">hostname</span><span class="p">:</span> <span class="nb">str</span><span class="p">,</span> <span class="n">port</span><span class="p">:</span> <span class="nb">int</span><span class="p">,</span> <span class="n">storageLevel</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_2</span>
<span class="p">)</span> <span class="o">-&gt;</span> <span class="s2">&quot;DStream[str]&quot;</span><span class="p">:</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Create an input from TCP source hostname:port. Data is received using</span>
<span class="sd"> a TCP socket and receive byte is interpreted as UTF8 encoded ``\\n`` delimited</span>
<span class="sd"> lines.</span>
<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<span class="sd"> hostname : str</span>
<span class="sd"> Hostname to connect to for receiving data</span>
<span class="sd"> port : int</span>
<span class="sd"> Port to connect to for receiving data</span>
<span class="sd"> storageLevel : :class:`pyspark.StorageLevel`, optional</span>
<span class="sd"> Storage level to use for storing the received objects</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="n">jlevel</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">_getJavaStorageLevel</span><span class="p">(</span><span class="n">storageLevel</span><span class="p">)</span>
<span class="k">return</span> <span class="n">DStream</span><span class="p">(</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_jssc</span><span class="o">.</span><span class="n">socketTextStream</span><span class="p">(</span><span class="n">hostname</span><span class="p">,</span> <span class="n">port</span><span class="p">,</span> <span class="n">jlevel</span><span class="p">),</span> <span class="bp">self</span><span class="p">,</span> <span class="n">UTF8Deserializer</span><span class="p">()</span>
<span class="p">)</span></div>
<div class="viewcode-block" id="StreamingContext.textFileStream"><a class="viewcode-back" href="../../../reference/api/pyspark.streaming.StreamingContext.textFileStream.html#pyspark.streaming.StreamingContext.textFileStream">[docs]</a> <span class="k">def</span> <span class="nf">textFileStream</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">directory</span><span class="p">:</span> <span class="nb">str</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="s2">&quot;DStream[str]&quot;</span><span class="p">:</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Create an input stream that monitors a Hadoop-compatible file system</span>
<span class="sd"> for new files and reads them as text files. Files must be written to the</span>
<span class="sd"> monitored directory by &quot;moving&quot; them from another location within the same</span>
<span class="sd"> file system. File names starting with . are ignored.</span>
<span class="sd"> The text files must be encoded as UTF-8.</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">return</span> <span class="n">DStream</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_jssc</span><span class="o">.</span><span class="n">textFileStream</span><span class="p">(</span><span class="n">directory</span><span class="p">),</span> <span class="bp">self</span><span class="p">,</span> <span class="n">UTF8Deserializer</span><span class="p">())</span></div>
<div class="viewcode-block" id="StreamingContext.binaryRecordsStream"><a class="viewcode-back" href="../../../reference/api/pyspark.streaming.StreamingContext.binaryRecordsStream.html#pyspark.streaming.StreamingContext.binaryRecordsStream">[docs]</a> <span class="k">def</span> <span class="nf">binaryRecordsStream</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">directory</span><span class="p">:</span> <span class="nb">str</span><span class="p">,</span> <span class="n">recordLength</span><span class="p">:</span> <span class="nb">int</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="s2">&quot;DStream[bytes]&quot;</span><span class="p">:</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Create an input stream that monitors a Hadoop-compatible file system</span>
<span class="sd"> for new files and reads them as flat binary files with records of</span>
<span class="sd"> fixed length. Files must be written to the monitored directory by &quot;moving&quot;</span>
<span class="sd"> them from another location within the same file system.</span>
<span class="sd"> File names starting with . are ignored.</span>
<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<span class="sd"> directory : str</span>
<span class="sd"> Directory to load data from</span>
<span class="sd"> recordLength : int</span>
<span class="sd"> Length of each record in bytes</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">return</span> <span class="n">DStream</span><span class="p">(</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_jssc</span><span class="o">.</span><span class="n">binaryRecordsStream</span><span class="p">(</span><span class="n">directory</span><span class="p">,</span> <span class="n">recordLength</span><span class="p">),</span> <span class="bp">self</span><span class="p">,</span> <span class="n">NoOpSerializer</span><span class="p">()</span>
<span class="p">)</span></div>
<span class="k">def</span> <span class="nf">_check_serializers</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">rdds</span><span class="p">:</span> <span class="n">List</span><span class="p">[</span><span class="n">RDD</span><span class="p">[</span><span class="n">T</span><span class="p">]])</span> <span class="o">-&gt;</span> <span class="kc">None</span><span class="p">:</span>
<span class="c1"># make sure they have same serializer</span>
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="nb">set</span><span class="p">(</span><span class="n">rdd</span><span class="o">.</span><span class="n">_jrdd_deserializer</span> <span class="k">for</span> <span class="n">rdd</span> <span class="ow">in</span> <span class="n">rdds</span><span class="p">))</span> <span class="o">&gt;</span> <span class="mi">1</span><span class="p">:</span>
<span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">rdds</span><span class="p">)):</span>
<span class="c1"># reset them to sc.serializer</span>
<span class="n">rdds</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="o">=</span> <span class="n">rdds</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="o">.</span><span class="n">_reserialize</span><span class="p">()</span>
<div class="viewcode-block" id="StreamingContext.queueStream"><a class="viewcode-back" href="../../../reference/api/pyspark.streaming.StreamingContext.queueStream.html#pyspark.streaming.StreamingContext.queueStream">[docs]</a> <span class="k">def</span> <span class="nf">queueStream</span><span class="p">(</span>
<span class="bp">self</span><span class="p">,</span>
<span class="n">rdds</span><span class="p">:</span> <span class="n">List</span><span class="p">[</span><span class="n">RDD</span><span class="p">[</span><span class="n">T</span><span class="p">]],</span>
<span class="n">oneAtATime</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">True</span><span class="p">,</span>
<span class="n">default</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">RDD</span><span class="p">[</span><span class="n">T</span><span class="p">]]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
<span class="p">)</span> <span class="o">-&gt;</span> <span class="s2">&quot;DStream[T]&quot;</span><span class="p">:</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Create an input stream from a queue of RDDs or list. In each batch,</span>
<span class="sd"> it will process either one or all of the RDDs returned by the queue.</span>
<span class="sd"> Parameters</span>
<span class="sd"> ----------</span>
<span class="sd"> rdds : list</span>
<span class="sd"> Queue of RDDs</span>
<span class="sd"> oneAtATime : bool, optional</span>
<span class="sd"> pick one rdd each time or pick all of them once.</span>
<span class="sd"> default : :class:`pyspark.RDD`, optional</span>
<span class="sd"> The default rdd if no more in rdds</span>
<span class="sd"> Notes</span>
<span class="sd"> -----</span>
<span class="sd"> Changes to the queue after the stream is created will not be recognized.</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">if</span> <span class="n">default</span> <span class="ow">and</span> <span class="ow">not</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">default</span><span class="p">,</span> <span class="n">RDD</span><span class="p">):</span>
<span class="n">default</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">parallelize</span><span class="p">(</span><span class="n">default</span><span class="p">)</span> <span class="c1"># type: ignore[arg-type]</span>
<span class="k">if</span> <span class="ow">not</span> <span class="n">rdds</span> <span class="ow">and</span> <span class="n">default</span><span class="p">:</span>
<span class="n">rdds</span> <span class="o">=</span> <span class="p">[</span><span class="n">rdds</span><span class="p">]</span> <span class="c1"># type: ignore[list-item]</span>
<span class="k">if</span> <span class="n">rdds</span> <span class="ow">and</span> <span class="ow">not</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">rdds</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">RDD</span><span class="p">):</span>
<span class="n">rdds</span> <span class="o">=</span> <span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">_sc</span><span class="o">.</span><span class="n">parallelize</span><span class="p">(</span><span class="nb">input</span><span class="p">)</span> <span class="k">for</span> <span class="nb">input</span> <span class="ow">in</span> <span class="n">rdds</span><span class="p">]</span> <span class="c1"># type: ignore[arg-type]</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_check_serializers</span><span class="p">(</span><span class="n">rdds</span><span class="p">)</span>
<span class="k">assert</span> <span class="bp">self</span><span class="o">.</span><span class="n">_jvm</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span>
<span class="n">queue</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_jvm</span><span class="o">.</span><span class="n">PythonDStream</span><span class="o">.</span><span class="n">toRDDQueue</span><span class="p">([</span><span class="n">r</span><span class="o">.</span><span class="n">_jrdd</span> <span class="k">for</span> <span class="n">r</span> <span class="ow">in</span> <span class="n">rdds</span><span class="p">])</span>
<span class="k">if</span> <span class="n">default</span><span class="p">:</span>
<span class="n">default</span> <span class="o">=</span> <span class="n">default</span><span class="o">.</span><span class="n">_reserialize</span><span class="p">(</span><span class="n">rdds</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">_jrdd_deserializer</span><span class="p">)</span>
<span class="k">assert</span> <span class="n">default</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span>
<span class="n">jdstream</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_jssc</span><span class="o">.</span><span class="n">queueStream</span><span class="p">(</span><span class="n">queue</span><span class="p">,</span> <span class="n">oneAtATime</span><span class="p">,</span> <span class="n">default</span><span class="o">.</span><span class="n">_jrdd</span><span class="p">)</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">jdstream</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_jssc</span><span class="o">.</span><span class="n">queueStream</span><span class="p">(</span><span class="n">queue</span><span class="p">,</span> <span class="n">oneAtATime</span><span class="p">)</span>
<span class="k">return</span> <span class="n">DStream</span><span class="p">(</span><span class="n">jdstream</span><span class="p">,</span> <span class="bp">self</span><span class="p">,</span> <span class="n">rdds</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">_jrdd_deserializer</span><span class="p">)</span></div>
<div class="viewcode-block" id="StreamingContext.transform"><a class="viewcode-back" href="../../../reference/api/pyspark.streaming.StreamingContext.transform.html#pyspark.streaming.StreamingContext.transform">[docs]</a> <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">dstreams</span><span class="p">:</span> <span class="n">List</span><span class="p">[</span><span class="s2">&quot;DStream[Any]&quot;</span><span class="p">],</span> <span class="n">transformFunc</span><span class="p">:</span> <span class="n">Callable</span><span class="p">[</span><span class="o">...</span><span class="p">,</span> <span class="n">RDD</span><span class="p">[</span><span class="n">T</span><span class="p">]]</span>
<span class="p">)</span> <span class="o">-&gt;</span> <span class="s2">&quot;DStream[T]&quot;</span><span class="p">:</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Create a new DStream in which each RDD is generated by applying</span>
<span class="sd"> a function on RDDs of the DStreams. The order of the JavaRDDs in</span>
<span class="sd"> the transform function parameter will be the same as the order</span>
<span class="sd"> of corresponding DStreams in the list.</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="n">jdstreams</span> <span class="o">=</span> <span class="p">[</span><span class="n">d</span><span class="o">.</span><span class="n">_jdstream</span> <span class="k">for</span> <span class="n">d</span> <span class="ow">in</span> <span class="n">dstreams</span><span class="p">]</span>
<span class="c1"># change the final serializer to sc.serializer</span>
<span class="n">func</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="k">lambda</span> <span class="n">t</span><span class="p">,</span> <span class="o">*</span><span class="n">rdds</span><span class="p">:</span> <span class="n">transformFunc</span><span class="p">(</span><span class="n">rdds</span><span class="p">),</span>
<span class="o">*</span><span class="p">[</span><span class="n">d</span><span class="o">.</span><span class="n">_jrdd_deserializer</span> <span class="k">for</span> <span class="n">d</span> <span class="ow">in</span> <span class="n">dstreams</span><span class="p">],</span>
<span class="p">)</span>
<span class="k">assert</span> <span class="bp">self</span><span class="o">.</span><span class="n">_jvm</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span>
<span class="n">jfunc</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_jvm</span><span class="o">.</span><span class="n">TransformFunction</span><span class="p">(</span><span class="n">func</span><span class="p">)</span>
<span class="n">jdstream</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_jssc</span><span class="o">.</span><span class="n">transform</span><span class="p">(</span><span class="n">jdstreams</span><span class="p">,</span> <span class="n">jfunc</span><span class="p">)</span>
<span class="k">return</span> <span class="n">DStream</span><span class="p">(</span><span class="n">jdstream</span><span class="p">,</span> <span class="bp">self</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">_sc</span><span class="o">.</span><span class="n">serializer</span><span class="p">)</span></div>
<div class="viewcode-block" id="StreamingContext.union"><a class="viewcode-back" href="../../../reference/api/pyspark.streaming.StreamingContext.union.html#pyspark.streaming.StreamingContext.union">[docs]</a> <span class="k">def</span> <span class="nf">union</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">dstreams</span><span class="p">:</span> <span class="s2">&quot;DStream[T]&quot;</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="s2">&quot;DStream[T]&quot;</span><span class="p">:</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Create a unified DStream from multiple DStreams of the same</span>
<span class="sd"> type and same slide duration.</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">if</span> <span class="ow">not</span> <span class="n">dstreams</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="s2">&quot;should have at least one DStream to union&quot;</span><span class="p">)</span>
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">dstreams</span><span class="p">)</span> <span class="o">==</span> <span class="mi">1</span><span class="p">:</span>
<span class="k">return</span> <span class="n">dstreams</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="nb">set</span><span class="p">(</span><span class="n">s</span><span class="o">.</span><span class="n">_jrdd_deserializer</span> <span class="k">for</span> <span class="n">s</span> <span class="ow">in</span> <span class="n">dstreams</span><span class="p">))</span> <span class="o">&gt;</span> <span class="mi">1</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="s2">&quot;All DStreams should have same serializer&quot;</span><span class="p">)</span>
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="nb">set</span><span class="p">(</span><span class="n">s</span><span class="o">.</span><span class="n">_slideDuration</span> <span class="k">for</span> <span class="n">s</span> <span class="ow">in</span> <span class="n">dstreams</span><span class="p">))</span> <span class="o">&gt;</span> <span class="mi">1</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="s2">&quot;All DStreams should have same slide duration&quot;</span><span class="p">)</span>
<span class="k">assert</span> <span class="n">SparkContext</span><span class="o">.</span><span class="n">_jvm</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span>
<span class="n">jdstream_cls</span> <span class="o">=</span> <span class="n">SparkContext</span><span class="o">.</span><span class="n">_jvm</span><span class="o">.</span><span class="n">org</span><span class="o">.</span><span class="n">apache</span><span class="o">.</span><span class="n">spark</span><span class="o">.</span><span class="n">streaming</span><span class="o">.</span><span class="n">api</span><span class="o">.</span><span class="n">java</span><span class="o">.</span><span class="n">JavaDStream</span>
<span class="n">jpair_dstream_cls</span> <span class="o">=</span> <span class="n">SparkContext</span><span class="o">.</span><span class="n">_jvm</span><span class="o">.</span><span class="n">org</span><span class="o">.</span><span class="n">apache</span><span class="o">.</span><span class="n">spark</span><span class="o">.</span><span class="n">streaming</span><span class="o">.</span><span class="n">api</span><span class="o">.</span><span class="n">java</span><span class="o">.</span><span class="n">JavaPairDStream</span>
<span class="n">gw</span> <span class="o">=</span> <span class="n">SparkContext</span><span class="o">.</span><span class="n">_gateway</span>
<span class="k">if</span> <span class="n">is_instance_of</span><span class="p">(</span><span class="n">gw</span><span class="p">,</span> <span class="n">dstreams</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">_jdstream</span><span class="p">,</span> <span class="n">jdstream_cls</span><span class="p">):</span>
<span class="bp">cls</span> <span class="o">=</span> <span class="n">jdstream_cls</span>
<span class="k">elif</span> <span class="n">is_instance_of</span><span class="p">(</span><span class="n">gw</span><span class="p">,</span> <span class="n">dstreams</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">_jdstream</span><span class="p">,</span> <span class="n">jpair_dstream_cls</span><span class="p">):</span>
<span class="bp">cls</span> <span class="o">=</span> <span class="n">jpair_dstream_cls</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">cls_name</span> <span class="o">=</span> <span class="n">dstreams</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">_jdstream</span><span class="o">.</span><span class="n">getClass</span><span class="p">()</span><span class="o">.</span><span class="n">getCanonicalName</span><span class="p">()</span>
<span class="k">raise</span> <span class="ne">TypeError</span><span class="p">(</span><span class="s2">&quot;Unsupported Java DStream class </span><span class="si">%s</span><span class="s2">&quot;</span> <span class="o">%</span> <span class="n">cls_name</span><span class="p">)</span>
<span class="k">assert</span> <span class="n">gw</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span>
<span class="n">jdstreams</span> <span class="o">=</span> <span class="n">gw</span><span class="o">.</span><span class="n">new_array</span><span class="p">(</span><span class="bp">cls</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">dstreams</span><span class="p">))</span>
<span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">dstreams</span><span class="p">)):</span>
<span class="n">jdstreams</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="o">=</span> <span class="n">dstreams</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="o">.</span><span class="n">_jdstream</span>
<span class="k">return</span> <span class="n">DStream</span><span class="p">(</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_jssc</span><span class="o">.</span><span class="n">union</span><span class="p">(</span><span class="n">jdstreams</span><span class="p">),</span>
<span class="bp">self</span><span class="p">,</span>
<span class="n">dstreams</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">_jrdd_deserializer</span><span class="p">,</span>
<span class="p">)</span></div>
<div class="viewcode-block" id="StreamingContext.addStreamingListener"><a class="viewcode-back" href="../../../reference/api/pyspark.streaming.StreamingContext.addStreamingListener.html#pyspark.streaming.StreamingContext.addStreamingListener">[docs]</a> <span class="k">def</span> <span class="nf">addStreamingListener</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">streamingListener</span><span class="p">:</span> <span class="n">StreamingListener</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="kc">None</span><span class="p">:</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Add a [[org.apache.spark.streaming.scheduler.StreamingListener]] object for</span>
<span class="sd"> receiving system events related to streaming.</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">assert</span> <span class="bp">self</span><span class="o">.</span><span class="n">_jvm</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_jssc</span><span class="o">.</span><span class="n">addStreamingListener</span><span class="p">(</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_jvm</span><span class="o">.</span><span class="n">JavaStreamingListenerWrapper</span><span class="p">(</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_jvm</span><span class="o">.</span><span class="n">PythonStreamingListenerWrapper</span><span class="p">(</span><span class="n">streamingListener</span><span class="p">)</span>
<span class="p">)</span>
<span class="p">)</span></div></div>
</pre></div>
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