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 <li class="toctree-l1 current"><a class="current reference internal" href="#">DAG Serialization</a><ul>
 <li class="toctree-l2"><a class="reference internal" href="#enable-dag-serialization">Enable Dag Serialization</a></li>
 <li class="toctree-l2"><a class="reference internal" href="#limitations">Limitations</a></li>
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   <blockquote>
 <div></div></blockquote>
 <div class="section" id="dag-serialization">
 <h1>DAG Serialization<a class="headerlink" href="#dag-serialization" title="Permalink to this headline">¶</a></h1>
 <p>In order to make Airflow Webserver stateless (almost!), Airflow &gt;=1.10.7 supports
 DAG Serialization and DB Persistence.</p>
 <img alt="_images/dag_serialization.png" src="_images/dag_serialization.png" />
 <p>Without DAG Serialization &amp; persistence in DB, the Webserver and the Scheduler both
 needs access to the DAG files. Both the scheduler and webserver parses the DAG files.</p>
 <p>With <strong>DAG Serialization</strong> we aim to decouple the webserver from DAG parsing
 which would make the Webserver very light-weight.</p>
 <p>As shown in the image above, when using the this feature,
 the Scheduler parses the DAG files, serializes them in JSON format and saves them in the Metadata DB.</p>
 <p>The Webserver now instead of having to parse the DAG file again, reads the
 serialized DAGs in JSON, de-serializes them and create the DagBag and uses it
 to show in the UI.</p>
 <p>One of the key features that is implemented as the part of DAG Serialization is that
 instead of loading an entire DagBag when the WebServer starts we only load each DAG on demand from the
 Serialized Dag table. This helps reduce Webserver startup time and memory. The reduction is notable
 when you have large number of DAGs.</p>
 <p>Below is the screenshot of the <code class="docutils literal notranslate"><span class="pre">serialized_dag</span></code> table in Metadata DB:</p>
 <img alt="_images/serialized_dag_table.png" src="_images/serialized_dag_table.png" />
 <div class="section" id="enable-dag-serialization">
 <h2>Enable Dag Serialization<a class="headerlink" href="#enable-dag-serialization" title="Permalink to this headline">¶</a></h2>
 <p>Add the following settings in <code class="docutils literal notranslate"><span class="pre">airflow.cfg</span></code>:</p>
 <div class="highlight-ini notranslate"><div class="highlight"><pre><span></span><span class="k">[core]</span>
 <span class="na">store_serialized_dags</span> <span class="o">=</span> <span class="s">True</span>
 <span class="na">min_serialized_dag_update_interval</span> <span class="o">=</span> <span class="s">30</span>
 </pre></div>
 </div>
 <ul class="simple">
 <li><p><code class="docutils literal notranslate"><span class="pre">store_serialized_dags</span></code>: This flag decides whether to serialises DAGs and persist them in DB.
 If set to True, Webserver reads from DB instead of parsing DAG files</p></li>
 <li><p><code class="docutils literal notranslate"><span class="pre">min_serialized_dag_update_interval</span></code>: This flag sets the minimum interval (in seconds) after which
 the serialized DAG in DB should be updated. This helps in reducing database write rate.</p></li>
 </ul>
 <p>If you are updating Airflow from &lt;1.10.7, please do not forget to run <code class="docutils literal notranslate"><span class="pre">airflow</span> <span class="pre">db</span> <span class="pre">upgrade</span></code>.</p>
 </div>
 <div class="section" id="limitations">
 <h2>Limitations<a class="headerlink" href="#limitations" title="Permalink to this headline">¶</a></h2>
 <p>The Webserver will still need access to DAG files in the following cases,
 which is why we said “almost” stateless.</p>
 <ul class="simple">
 <li><p><strong>Rendered Template</strong> tab will still have to parse Python file as it needs all the details like
 the execution date and even the data passed by the upstream task using Xcom.</p></li>
 <li><p><strong>Code View</strong> will read the DAG File &amp; show it using Pygments.
 However, it does not need to Parse the Python file so it is still a small operation.</p></li>
 </ul>
 </div>
 <div class="section" id="using-a-different-json-library">
 <h2>Using a different JSON Library<a class="headerlink" href="#using-a-different-json-library" title="Permalink to this headline">¶</a></h2>
 <p>To use a different JSON library instead of the standard <code class="docutils literal notranslate"><span class="pre">json</span></code> library like <code class="docutils literal notranslate"><span class="pre">ujson</span></code>, you need to
 define a <code class="docutils literal notranslate"><span class="pre">json</span></code> variable in local Airflow settings (<code class="docutils literal notranslate"><span class="pre">airflow_local_settings.py</span></code>) file as follows:</p>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="kn">import</span> <span class="nn">ujson</span>
 <span class="n">json</span> <span class="o">=</span> <span class="n">ujson</span>
 </pre></div>
 </div>
 </div>
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	<li class="toctree-l1 current"><a class="current reference internal" href="#">DAG Serialization</a><ul>
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	<blockquote>
	<div></div></blockquote>
	<div class="section" id="dag-serialization">
	<h1>DAG Serialization<a class="headerlink" href="#dag-serialization" title="Permalink to this headline">¶</a></h1>
	<p>In order to make Airflow Webserver stateless (almost!), Airflow >=1.10.7 supports
	DAG Serialization and DB Persistence.</p>
	<img alt="_images/dag_serialization.png" src="_images/dag_serialization.png" />
	<p>Without DAG Serialization & persistence in DB, the Webserver and the Scheduler both
	needs access to the DAG files. Both the scheduler and webserver parses the DAG files.</p>
	<p>With <strong>DAG Serialization</strong> we aim to decouple the webserver from DAG parsing
	which would make the Webserver very light-weight.</p>
	<p>As shown in the image above, when using the this feature,
	the Scheduler parses the DAG files, serializes them in JSON format and saves them in the Metadata DB.</p>
	<p>The Webserver now instead of having to parse the DAG file again, reads the
	serialized DAGs in JSON, de-serializes them and create the DagBag and uses it
	to show in the UI.</p>
	<p>One of the key features that is implemented as the part of DAG Serialization is that
	instead of loading an entire DagBag when the WebServer starts we only load each DAG on demand from the
	Serialized Dag table. This helps reduce Webserver startup time and memory. The reduction is notable
	when you have large number of DAGs.</p>
	<p>Below is the screenshot of the <code class="docutils literal notranslate"><span class="pre">serialized_dag</span></code> table in Metadata DB:</p>
	<img alt="_images/serialized_dag_table.png" src="_images/serialized_dag_table.png" />
	<div class="section" id="enable-dag-serialization">
	<h2>Enable Dag Serialization<a class="headerlink" href="#enable-dag-serialization" title="Permalink to this headline">¶</a></h2>
	<p>Add the following settings in <code class="docutils literal notranslate"><span class="pre">airflow.cfg</span></code>:</p>
	<div class="highlight-ini notranslate"><div class="highlight"><pre><span></span><span class="k">[core]</span>
	<span class="na">store_serialized_dags</span> <span class="o">=</span> <span class="s">True</span>
	<span class="na">min_serialized_dag_update_interval</span> <span class="o">=</span> <span class="s">30</span>
	</pre></div>
	</div>
	<ul class="simple">
	<li><p><code class="docutils literal notranslate"><span class="pre">store_serialized_dags</span></code>: This flag decides whether to serialises DAGs and persist them in DB.
	If set to True, Webserver reads from DB instead of parsing DAG files</p></li>
	<li><p><code class="docutils literal notranslate"><span class="pre">min_serialized_dag_update_interval</span></code>: This flag sets the minimum interval (in seconds) after which
	the serialized DAG in DB should be updated. This helps in reducing database write rate.</p></li>
	</ul>
	<p>If you are updating Airflow from <1.10.7, please do not forget to run <code class="docutils literal notranslate"><span class="pre">airflow</span> <span class="pre">db</span> <span class="pre">upgrade</span></code>.</p>
	</div>
	<div class="section" id="limitations">
	<h2>Limitations<a class="headerlink" href="#limitations" title="Permalink to this headline">¶</a></h2>
	<p>The Webserver will still need access to DAG files in the following cases,
	which is why we said “almost” stateless.</p>
	<ul class="simple">
	<li><p><strong>Rendered Template</strong> tab will still have to parse Python file as it needs all the details like
	the execution date and even the data passed by the upstream task using Xcom.</p></li>
	<li><p><strong>Code View</strong> will read the DAG File & show it using Pygments.
	However, it does not need to Parse the Python file so it is still a small operation.</p></li>
	</ul>
	</div>
	<div class="section" id="using-a-different-json-library">
	<h2>Using a different JSON Library<a class="headerlink" href="#using-a-different-json-library" title="Permalink to this headline">¶</a></h2>
	<p>To use a different JSON library instead of the standard <code class="docutils literal notranslate"><span class="pre">json</span></code> library like <code class="docutils literal notranslate"><span class="pre">ujson</span></code>, you need to
	define a <code class="docutils literal notranslate"><span class="pre">json</span></code> variable in local Airflow settings (<code class="docutils literal notranslate"><span class="pre">airflow_local_settings.py</span></code>) file as follows:</p>
	<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="kn">import</span> <span class="nn">ujson</span>
	<span class="n">json</span> <span class="o">=</span> <span class="n">ujson</span>
	</pre></div>
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