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<blockquote>
<div></div></blockquote>
<div class="section" id="dynamic-task-mapping">
<h1>Dynamic Task Mapping<a class="headerlink" href="#dynamic-task-mapping" title="Permalink to this headline"></a></h1>
<p>Dynamic Task Mapping allows a way for a workflow to create a number of tasks at runtime based upon current data, rather than the DAG author having to know in advance how many tasks would be needed.</p>
<p>This is similar to defining your tasks in a for loop, but instead of having the DAG file fetch the data and do that itself, the scheduler can do this based on the output of a previous task. Right before a mapped task is executed the scheduler will create <em>n</em> copies of the task, one for each input.</p>
<p>It is also possible to have a task operate on the collected output of a mapped task, commonly known as map and reduce.</p>
<div class="section" id="simple-mapping">
<h2>Simple mapping<a class="headerlink" href="#simple-mapping" title="Permalink to this headline"></a></h2>
<p>In its simplest form you can map over a list defined directly in your DAG file using the <code class="docutils literal notranslate"><span class="pre">expand()</span></code> function instead of calling your task directly.</p>
<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="kn">from</span> <span class="nn">datetime</span> <span class="kn">import</span> <span class="n">datetime</span>
<span class="kn">from</span> <span class="nn">airflow</span> <span class="kn">import</span> <span class="n">DAG</span>
<span class="kn">from</span> <span class="nn">airflow.decorators</span> <span class="kn">import</span> <span class="n">task</span>
<span class="k">with</span> <span class="n">DAG</span><span class="p">(</span><span class="n">dag_id</span><span class="o">=</span><span class="s2">&quot;simple_mapping&quot;</span><span class="p">,</span> <span class="n">start_date</span><span class="o">=</span><span class="n">datetime</span><span class="p">(</span><span class="mi">2022</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">4</span><span class="p">))</span> <span class="k">as</span> <span class="n">dag</span><span class="p">:</span>
<span class="nd">@task</span>
<span class="k">def</span> <span class="nf">add_one</span><span class="p">(</span><span class="n">x</span><span class="p">:</span> <span class="nb">int</span><span class="p">):</span>
<span class="k">return</span> <span class="n">x</span> <span class="o">+</span> <span class="mi">1</span>
<span class="nd">@task</span>
<span class="k">def</span> <span class="nf">sum_it</span><span class="p">(</span><span class="n">values</span><span class="p">):</span>
<span class="n">total</span> <span class="o">=</span> <span class="nb">sum</span><span class="p">(</span><span class="n">values</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Total was </span><span class="si">{</span><span class="n">total</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
<span class="n">added_values</span> <span class="o">=</span> <span class="n">add_one</span><span class="o">.</span><span class="n">expand</span><span class="p">(</span><span class="n">x</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">])</span>
<span class="n">sum_it</span><span class="p">(</span><span class="n">added_values</span><span class="p">)</span>
</pre></div>
</div>
<p>This will show <code class="docutils literal notranslate"><span class="pre">Total</span> <span class="pre">was</span> <span class="pre">9</span></code> in the task logs when executed.</p>
<p>This is the resulting DAG structure:</p>
<img alt="../_images/mapping-simple-graph.png" src="../_images/mapping-simple-graph.png" />
<p>The grid view also provides visibility into your mapped tasks in the details panel:</p>
<img alt="../_images/mapping-simple-grid.png" src="../_images/mapping-simple-grid.png" />
<div class="admonition note">
<p class="admonition-title">Note</p>
<p>Values passed from the mapped task is a lazy proxy</p>
<p>In the above example, <code class="docutils literal notranslate"><span class="pre">values</span></code> received by <code class="docutils literal notranslate"><span class="pre">sum_it</span></code> is an aggregation of all values returned by each mapped instance of <code class="docutils literal notranslate"><span class="pre">add_one</span></code>. However, since it is impossible to know how many instances of <code class="docutils literal notranslate"><span class="pre">add_one</span></code> we will have in advance, <code class="docutils literal notranslate"><span class="pre">values</span></code> is not a normal list, but a “lazy sequence” that retrieves each individual value only when asked. Therefore, if you run <code class="docutils literal notranslate"><span class="pre">print(values)</span></code> directly, you would get something like this:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">_LazyXComAccess</span><span class="p">(</span><span class="n">dag_id</span><span class="o">=</span><span class="s1">&#39;simple_mapping&#39;</span><span class="p">,</span> <span class="n">run_id</span><span class="o">=</span><span class="s1">&#39;test_run&#39;</span><span class="p">,</span> <span class="n">task_id</span><span class="o">=</span><span class="s1">&#39;add_one&#39;</span><span class="p">)</span>
</pre></div>
</div>
<p>You can use normal sequence syntax on this object (e.g. <code class="docutils literal notranslate"><span class="pre">values[0]</span></code>), or iterate through it normally with a <code class="docutils literal notranslate"><span class="pre">for</span></code> loop. <code class="docutils literal notranslate"><span class="pre">list(values)</span></code> will give you a “real” <code class="docutils literal notranslate"><span class="pre">list</span></code>, but please be aware of the potential performance implications if the list is large.</p>
</div>
<div class="admonition note">
<p class="admonition-title">Note</p>
<p>A reduce task is not required.</p>
<p>Although we show a “reduce” task here (<code class="docutils literal notranslate"><span class="pre">sum_it</span></code>) you don’t have to have one, the mapped tasks will still be executed even if they have no downstream tasks.</p>
</div>
</div>
<div class="section" id="repeated-mapping">
<h2>Repeated Mapping<a class="headerlink" href="#repeated-mapping" title="Permalink to this headline"></a></h2>
<p>The result of one mapped task can also be used as input to the next mapped task.</p>
<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="k">with</span> <span class="n">DAG</span><span class="p">(</span><span class="n">dag_id</span><span class="o">=</span><span class="s2">&quot;repeated_mapping&quot;</span><span class="p">,</span> <span class="n">start_date</span><span class="o">=</span><span class="n">datetime</span><span class="p">(</span><span class="mi">2022</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">4</span><span class="p">))</span> <span class="k">as</span> <span class="n">dag</span><span class="p">:</span>
<span class="nd">@task</span>
<span class="k">def</span> <span class="nf">add_one</span><span class="p">(</span><span class="n">x</span><span class="p">:</span> <span class="nb">int</span><span class="p">):</span>
<span class="k">return</span> <span class="n">x</span> <span class="o">+</span> <span class="mi">1</span>
<span class="n">first</span> <span class="o">=</span> <span class="n">add_one</span><span class="o">.</span><span class="n">expand</span><span class="p">(</span><span class="n">x</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">])</span>
<span class="n">second</span> <span class="o">=</span> <span class="n">add_one</span><span class="o">.</span><span class="n">expand</span><span class="p">(</span><span class="n">x</span><span class="o">=</span><span class="n">first</span><span class="p">)</span>
</pre></div>
</div>
<p>This would have a result of <code class="docutils literal notranslate"><span class="pre">[3,</span> <span class="pre">4,</span> <span class="pre">5]</span></code>.</p>
</div>
<div class="section" id="constant-parameters">
<h2>Constant parameters<a class="headerlink" href="#constant-parameters" title="Permalink to this headline"></a></h2>
<p>As well as passing arguments that get expanded at run-time, it is possible to pass arguments that don’t change – in order to clearly differentiate between the two kinds we use different functions, <code class="docutils literal notranslate"><span class="pre">expand()</span></code> for mapped arguments, and <code class="docutils literal notranslate"><span class="pre">partial()</span></code> for unmapped ones.</p>
<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="nd">@task</span>
<span class="k">def</span> <span class="nf">add</span><span class="p">(</span><span class="n">x</span><span class="p">:</span> <span class="nb">int</span><span class="p">,</span> <span class="n">y</span><span class="p">:</span> <span class="nb">int</span><span class="p">):</span>
<span class="k">return</span> <span class="n">x</span> <span class="o">+</span> <span class="n">y</span>
<span class="n">added_values</span> <span class="o">=</span> <span class="n">add</span><span class="o">.</span><span class="n">partial</span><span class="p">(</span><span class="n">y</span><span class="o">=</span><span class="mi">10</span><span class="p">)</span><span class="o">.</span><span class="n">expand</span><span class="p">(</span><span class="n">x</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">])</span>
<span class="c1"># This results in add function being expanded to</span>
<span class="c1"># add(x=1, y=10)</span>
<span class="c1"># add(x=2, y=10)</span>
<span class="c1"># add(x=3, y=10)</span>
</pre></div>
</div>
<p>This would result in values of 11, 12, and 13.</p>
<p>This is also useful for passing things such as connection IDs, database table names, or bucket names to tasks.</p>
</div>
<div class="section" id="mapping-over-multiple-parameters">
<h2>Mapping over multiple parameters<a class="headerlink" href="#mapping-over-multiple-parameters" title="Permalink to this headline"></a></h2>
<p>As well as a single parameter it is possible to pass multiple parameters to expand. This will have the effect of creating a “cross product”, calling the mapped task with each combination of parameters.</p>
<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="nd">@task</span>
<span class="k">def</span> <span class="nf">add</span><span class="p">(</span><span class="n">x</span><span class="p">:</span> <span class="nb">int</span><span class="p">,</span> <span class="n">y</span><span class="p">:</span> <span class="nb">int</span><span class="p">):</span>
<span class="k">return</span> <span class="n">x</span> <span class="o">+</span> <span class="n">y</span>
<span class="n">added_values</span> <span class="o">=</span> <span class="n">add</span><span class="o">.</span><span class="n">expand</span><span class="p">(</span><span class="n">x</span><span class="o">=</span><span class="p">[</span><span class="mi">2</span><span class="p">,</span> <span class="mi">4</span><span class="p">,</span> <span class="mi">8</span><span class="p">],</span> <span class="n">y</span><span class="o">=</span><span class="p">[</span><span class="mi">5</span><span class="p">,</span> <span class="mi">10</span><span class="p">])</span>
<span class="c1"># This results in the add function being called with</span>
<span class="c1"># add(x=2, y=5)</span>
<span class="c1"># add(x=2, y=10)</span>
<span class="c1"># add(x=4, y=5)</span>
<span class="c1"># add(x=4, y=10)</span>
<span class="c1"># add(x=8, y=5)</span>
<span class="c1"># add(x=8, y=10)</span>
</pre></div>
</div>
<p>This would result in the add task being called 6 times. Please note however that the order of expansion is not guaranteed.</p>
<p>It is not possible to achieve an effect similar to Python’s <code class="docutils literal notranslate"><span class="pre">zip</span></code> function with mapped arguments.</p>
</div>
<div class="section" id="task-generated-mapping">
<h2>Task-generated Mapping<a class="headerlink" href="#task-generated-mapping" title="Permalink to this headline"></a></h2>
<p>Up until now the examples we’ve shown could all be achieved with a <code class="docutils literal notranslate"><span class="pre">for</span></code> loop in the DAG file, but the real power of dynamic task mapping comes from being able to have a task generate the list to iterate over.</p>
<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="nd">@task</span>
<span class="k">def</span> <span class="nf">make_list</span><span class="p">():</span>
<span class="c1"># This can also be from an API call, checking a database, -- almost anything you like, as long as the</span>
<span class="c1"># resulting list/dictionary can be stored in the current XCom backend.</span>
<span class="k">return</span> <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="p">{</span><span class="s2">&quot;a&quot;</span><span class="p">:</span> <span class="s2">&quot;b&quot;</span><span class="p">},</span> <span class="s2">&quot;str&quot;</span><span class="p">]</span>
<span class="nd">@task</span>
<span class="k">def</span> <span class="nf">consumer</span><span class="p">(</span><span class="n">arg</span><span class="p">):</span>
<span class="nb">print</span><span class="p">(</span><span class="nb">list</span><span class="p">(</span><span class="n">arg</span><span class="p">))</span>
<span class="k">with</span> <span class="n">DAG</span><span class="p">(</span><span class="n">dag_id</span><span class="o">=</span><span class="s2">&quot;dynamic-map&quot;</span><span class="p">,</span> <span class="n">start_date</span><span class="o">=</span><span class="n">datetime</span><span class="p">(</span><span class="mi">2022</span><span class="p">,</span> <span class="mi">4</span><span class="p">,</span> <span class="mi">2</span><span class="p">))</span> <span class="k">as</span> <span class="n">dag</span><span class="p">:</span>
<span class="n">consumer</span><span class="o">.</span><span class="n">expand</span><span class="p">(</span><span class="n">arg</span><span class="o">=</span><span class="n">make_list</span><span class="p">())</span>
</pre></div>
</div>
<p>The <code class="docutils literal notranslate"><span class="pre">make_list</span></code> task runs as a normal task and must return a list or dict (see <a class="reference internal" href="#what-data-types-can-be-expanded">What data types can be expanded?</a>), and then the <code class="docutils literal notranslate"><span class="pre">consumer</span></code> task will be called four times, once with each value in the return of <code class="docutils literal notranslate"><span class="pre">make_list</span></code>.</p>
</div>
<div class="section" id="mapping-with-non-taskflow-operators">
<h2>Mapping with non-TaskFlow operators<a class="headerlink" href="#mapping-with-non-taskflow-operators" title="Permalink to this headline"></a></h2>
<p>It is possible to use <code class="docutils literal notranslate"><span class="pre">partial</span></code> and <code class="docutils literal notranslate"><span class="pre">expand</span></code> with classic style operators as well. Some arguments are not mappable and must be passed to <code class="docutils literal notranslate"><span class="pre">partial()</span></code>, such as <code class="docutils literal notranslate"><span class="pre">task_id</span></code>, <code class="docutils literal notranslate"><span class="pre">queue</span></code>, <code class="docutils literal notranslate"><span class="pre">pool</span></code>, and most other arguments to <code class="docutils literal notranslate"><span class="pre">BaseOperator</span></code>.</p>
<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">BashOperator</span><span class="o">.</span><span class="n">partial</span><span class="p">(</span><span class="n">task_id</span><span class="o">=</span><span class="s2">&quot;bash&quot;</span><span class="p">,</span> <span class="n">do_xcom_push</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span><span class="o">.</span><span class="n">expand</span><span class="p">(</span>
<span class="n">bash_command</span><span class="o">=</span><span class="p">[</span><span class="s2">&quot;echo 1&quot;</span><span class="p">,</span> <span class="s2">&quot;echo 2&quot;</span><span class="p">]</span>
<span class="p">)</span>
</pre></div>
</div>
<div class="section" id="mapping-over-result-of-classic-operators">
<h3>Mapping over result of classic operators<a class="headerlink" href="#mapping-over-result-of-classic-operators" title="Permalink to this headline"></a></h3>
<p>If you want to map over the result of a classic operator you will need to create an <code class="docutils literal notranslate"><span class="pre">XComArg</span></code> object manually.</p>
<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="kn">from</span> <span class="nn">airflow</span> <span class="kn">import</span> <span class="n">XComArg</span>
<span class="n">task</span> <span class="o">=</span> <span class="n">MyOperator</span><span class="p">(</span><span class="n">task_id</span><span class="o">=</span><span class="s2">&quot;source&quot;</span><span class="p">)</span>
<span class="n">downstream</span> <span class="o">=</span> <span class="n">MyOperator2</span><span class="o">.</span><span class="n">partial</span><span class="p">(</span><span class="n">task_id</span><span class="o">=</span><span class="s2">&quot;consumer&quot;</span><span class="p">)</span><span class="o">.</span><span class="n">expand</span><span class="p">(</span><span class="nb">input</span><span class="o">=</span><span class="n">XComArg</span><span class="p">(</span><span class="n">task</span><span class="p">))</span>
</pre></div>
</div>
</div>
</div>
<div class="section" id="putting-it-all-together">
<h2>Putting it all together<a class="headerlink" href="#putting-it-all-together" title="Permalink to this headline"></a></h2>
<p>In this example you have a regular data delivery to an S3 bucket and want to apply the same processing to every file that arrives, no matter how many arrive each time.</p>
<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="kn">from</span> <span class="nn">datetime</span> <span class="kn">import</span> <span class="n">datetime</span>
<span class="kn">from</span> <span class="nn">airflow</span> <span class="kn">import</span> <span class="n">DAG</span><span class="p">,</span> <span class="n">XComArg</span>
<span class="kn">from</span> <span class="nn">airflow.decorators</span> <span class="kn">import</span> <span class="n">task</span>
<span class="kn">from</span> <span class="nn">airflow.providers.amazon.aws.hooks.s3</span> <span class="kn">import</span> <span class="n">S3Hook</span>
<span class="kn">from</span> <span class="nn">airflow.providers.amazon.aws.operators.s3</span> <span class="kn">import</span> <span class="n">S3ListOperator</span>
<span class="k">with</span> <span class="n">DAG</span><span class="p">(</span><span class="n">dag_id</span><span class="o">=</span><span class="s2">&quot;mapped_s3&quot;</span><span class="p">,</span> <span class="n">start_date</span><span class="o">=</span><span class="n">datetime</span><span class="p">(</span><span class="mi">2020</span><span class="p">,</span> <span class="mi">4</span><span class="p">,</span> <span class="mi">7</span><span class="p">))</span> <span class="k">as</span> <span class="n">dag</span><span class="p">:</span>
<span class="n">files</span> <span class="o">=</span> <span class="n">S3ListOperator</span><span class="p">(</span>
<span class="n">task_id</span><span class="o">=</span><span class="s2">&quot;get_input&quot;</span><span class="p">,</span>
<span class="n">bucket</span><span class="o">=</span><span class="s2">&quot;example-bucket&quot;</span><span class="p">,</span>
<span class="n">prefix</span><span class="o">=</span><span class="s1">&#39;incoming/provider_a/{{ data_interval_start.strftime(&quot;%Y-%m-</span><span class="si">%d</span><span class="s1">&quot;) }}&#39;</span><span class="p">,</span>
<span class="p">)</span>
<span class="nd">@task</span>
<span class="k">def</span> <span class="nf">count_lines</span><span class="p">(</span><span class="n">aws_conn_id</span><span class="p">,</span> <span class="n">bucket</span><span class="p">,</span> <span class="n">file</span><span class="p">):</span>
<span class="n">hook</span> <span class="o">=</span> <span class="n">S3Hook</span><span class="p">(</span><span class="n">aws_conn_id</span><span class="o">=</span><span class="n">aws_conn_id</span><span class="p">)</span>
<span class="k">return</span> <span class="nb">len</span><span class="p">(</span><span class="n">hook</span><span class="o">.</span><span class="n">read_key</span><span class="p">(</span><span class="n">file</span><span class="p">,</span> <span class="n">bucket</span><span class="p">)</span><span class="o">.</span><span class="n">splitlines</span><span class="p">())</span>
<span class="nd">@task</span>
<span class="k">def</span> <span class="nf">total</span><span class="p">(</span><span class="n">lines</span><span class="p">):</span>
<span class="k">return</span> <span class="nb">sum</span><span class="p">(</span><span class="n">lines</span><span class="p">)</span>
<span class="n">counts</span> <span class="o">=</span> <span class="n">count_lines</span><span class="o">.</span><span class="n">partial</span><span class="p">(</span><span class="n">aws_conn_id</span><span class="o">=</span><span class="s2">&quot;aws_default&quot;</span><span class="p">,</span> <span class="n">bucket</span><span class="o">=</span><span class="n">files</span><span class="o">.</span><span class="n">bucket</span><span class="p">)</span><span class="o">.</span><span class="n">expand</span><span class="p">(</span>
<span class="n">file</span><span class="o">=</span><span class="n">XComArg</span><span class="p">(</span><span class="n">files</span><span class="p">)</span>
<span class="p">)</span>
<span class="n">total</span><span class="p">(</span><span class="n">lines</span><span class="o">=</span><span class="n">counts</span><span class="p">)</span>
</pre></div>
</div>
</div>
<div class="section" id="what-data-types-can-be-expanded">
<h2>What data types can be expanded?<a class="headerlink" href="#what-data-types-can-be-expanded" title="Permalink to this headline"></a></h2>
<p>Currently it is only possible to map against a dict, a list, or one of those types stored in XCom as the result of a task.</p>
<p>If an upstream task returns an unmappable type, the mapped task will fail at run-time with an <code class="docutils literal notranslate"><span class="pre">UnmappableXComTypePushed</span></code> exception. For instance, you can’t have the upstream task return a plain string – it must be a list or a dict.</p>
</div>
<div class="section" id="how-do-templated-fields-and-mapped-arguments-interact">
<h2>How do templated fields and mapped arguments interact?<a class="headerlink" href="#how-do-templated-fields-and-mapped-arguments-interact" title="Permalink to this headline"></a></h2>
<p>All arguments to an operator can be mapped, even those that do not accept templated parameters.</p>
<p>If a field is marked as being templated and is mapped, it <strong>will not be templated</strong>.</p>
<p>For example, this will print <code class="docutils literal notranslate"><span class="pre">{{</span> <span class="pre">ds</span> <span class="pre">}}</span></code> and not a date stamp:</p>
<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="nd">@task</span>
<span class="k">def</span> <span class="nf">make_list</span><span class="p">():</span>
<span class="k">return</span> <span class="p">[</span><span class="s2">&quot;{{ ds }}&quot;</span><span class="p">]</span>
<span class="nd">@task</span>
<span class="k">def</span> <span class="nf">printer</span><span class="p">(</span><span class="n">val</span><span class="p">):</span>
<span class="nb">print</span><span class="p">(</span><span class="n">val</span><span class="p">)</span>
<span class="n">printer</span><span class="o">.</span><span class="n">expand</span><span class="p">(</span><span class="n">val</span><span class="o">=</span><span class="n">make_list</span><span class="p">())</span>
</pre></div>
</div>
<p>If you want to interpolate values either call <code class="docutils literal notranslate"><span class="pre">task.render_template</span></code> yourself, or use interpolation:</p>
<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="nd">@task</span>
<span class="k">def</span> <span class="nf">make_list</span><span class="p">(</span><span class="n">ds</span><span class="p">):</span>
<span class="k">return</span> <span class="p">[</span><span class="n">ds</span><span class="p">]</span>
<span class="nd">@task</span>
<span class="k">def</span> <span class="nf">make_list</span><span class="p">(</span><span class="o">**</span><span class="n">context</span><span class="p">):</span>
<span class="k">return</span> <span class="p">[</span><span class="n">context</span><span class="p">[</span><span class="s2">&quot;task&quot;</span><span class="p">]</span><span class="o">.</span><span class="n">render_template</span><span class="p">(</span><span class="s2">&quot;{{ ds }}&quot;</span><span class="p">,</span> <span class="n">context</span><span class="p">)]</span>
</pre></div>
</div>
</div>
<div class="section" id="placing-limits-on-mapped-tasks">
<h2>Placing limits on mapped tasks<a class="headerlink" href="#placing-limits-on-mapped-tasks" title="Permalink to this headline"></a></h2>
<p>There are two limits that you can place on a task:</p>
<blockquote>
<div><ol class="arabic simple">
<li><p>the number of mapped task instances can be created as the result of expansion.</p></li>
<li><p>The number of the mapped task can run at once.</p></li>
</ol>
</div></blockquote>
<ul>
<li><p><strong>Limiting number of mapped task</strong></p>
<p>The [core] <code class="docutils literal notranslate"><span class="pre">max_map_length</span></code> config option is the maximum number of tasks that <code class="docutils literal notranslate"><span class="pre">expand</span></code> can create – the default value is 1024.</p>
<p>If a source task (<code class="docutils literal notranslate"><span class="pre">make_list</span></code> in our earlier example) returns a list longer than this it will result in <em>that</em> task failing.</p>
</li>
<li><p><strong>Limiting parallel copies of a mapped task</strong></p>
<p>If you wish to not have a large mapped task consume all available runner slots you can use the <code class="docutils literal notranslate"><span class="pre">max_active_tis_per_dag</span></code> setting on the task to restrict how many can be running at the same time.</p>
<p>Note however that this applies to all copies of that task against all active DagRuns, not just to this one specific DagRun.</p>
<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="nd">@task</span><span class="p">(</span><span class="n">max_active_tis_per_dag</span><span class="o">=</span><span class="mi">16</span><span class="p">)</span>
<span class="k">def</span> <span class="nf">add_one</span><span class="p">(</span><span class="n">x</span><span class="p">:</span> <span class="nb">int</span><span class="p">):</span>
<span class="k">return</span> <span class="n">x</span> <span class="o">+</span> <span class="mi">1</span>
<span class="n">BashOperator</span><span class="o">.</span><span class="n">partial</span><span class="p">(</span><span class="n">task_id</span><span class="o">=</span><span class="s2">&quot;my_task&quot;</span><span class="p">,</span> <span class="n">max_active_tis_per_dag</span><span class="o">=</span><span class="mi">16</span><span class="p">)</span><span class="o">.</span><span class="n">expand</span><span class="p">(</span>
<span class="n">bash_command</span><span class="o">=</span><span class="n">commands</span>
<span class="p">)</span>
</pre></div>
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<div class="section" id="automatically-skipping-zero-length-maps">
<h2>Automatically skipping zero-length maps<a class="headerlink" href="#automatically-skipping-zero-length-maps" title="Permalink to this headline"></a></h2>
<p>If the input is empty (zero length), no new tasks will be created and the mapped task will be marked as <code class="docutils literal notranslate"><span class="pre">SKIPPED</span></code>.</p>
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