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| <section id="implementing-openlineage-in-operators"> |
| <span id="guides-developer-openlineage"></span><h1>Implementing OpenLineage in Operators<a class="headerlink" href="#implementing-openlineage-in-operators" title="Link to this heading">¶</a></h1> |
| <p>OpenLineage makes adding lineage to your data pipelines easy through support of direct modification of Airflow Operators. |
| When it’s possible to modify the Operator adding lineage extraction can be as easy as adding a single method to it. |
| See <a class="reference internal" href="#openlineage-methods-openlineage"><span class="std std-ref">OpenLineage methods</span></a> for more details.</p> |
| <p>There might be some Operators that you can not modify (f.e. third party providers), but still want the lineage to be extracted from them. |
| To handle this situation, OpenLineage allows you to provide custom Extractor for any Operator. |
| See <a class="reference internal" href="#custom-extractors-openlineage"><span class="std std-ref">Custom Extractors</span></a> for more details.</p> |
| <section id="extraction-precedence"> |
| <span id="extraction-precedence-openlineage"></span><h2>Extraction precedence<a class="headerlink" href="#extraction-precedence" title="Link to this heading">¶</a></h2> |
| <p>As there are multiple possible ways of implementing OpenLineage support for the Operator, |
| it’s important to keep in mind the order in which OpenLineage looks for lineage data:</p> |
| <ol class="arabic simple"> |
| <li><p><strong>Extractor</strong> - check if there is a custom Extractor specified for Operator class name. Any custom Extractor registered by the user will take precedence over default Extractors defined in Airflow Provider source code (f.e. BashExtractor).</p></li> |
| <li><p><strong>OpenLineage methods</strong> - if there is no Extractor explicitly specified for Operator class name, DefaultExtractor is used, that looks for OpenLineage methods in Operator.</p></li> |
| <li><p><strong>Inlets and Outlets</strong> - if there are no OpenLineage methods defined in the Operator, inlets and outlets are checked.</p></li> |
| </ol> |
| <p>If all the above options are missing, no lineage data is extracted from the Operator. You will still receive OpenLineage events |
| enriched with things like general Airflow facets, proper event time and type, but the inputs/outputs will be empty |
| and Operator-specific facets will be missing.</p> |
| </section> |
| <section id="openlineage-methods"> |
| <span id="openlineage-methods-openlineage"></span><h2>OpenLineage methods<a class="headerlink" href="#openlineage-methods" title="Link to this heading">¶</a></h2> |
| <p>This approach is recommended when dealing with your own Operators, where you can directly implement OpenLineage methods. |
| When dealing with Operators that you can not modify (f.e. third party providers), but still want the lineage to be extracted from them, see <a class="reference internal" href="#custom-extractors-openlineage"><span class="std std-ref">Custom Extractors</span></a>.</p> |
| <p>OpenLineage defines a few methods for implementation in Operators. Those are referred to as OpenLineage methods.</p> |
| <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="k">def</span><span class="w"> </span><span class="nf">get_openlineage_facets_on_start</span><span class="p">()</span> <span class="o">-></span> <span class="n">OperatorLineage</span><span class="p">:</span> <span class="o">...</span> |
| |
| |
| <span class="k">def</span><span class="w"> </span><span class="nf">get_openlineage_facets_on_complete</span><span class="p">(</span><span class="n">ti</span><span class="p">:</span> <span class="n">TaskInstance</span><span class="p">)</span> <span class="o">-></span> <span class="n">OperatorLineage</span><span class="p">:</span> <span class="o">...</span> |
| |
| |
| <span class="k">def</span><span class="w"> </span><span class="nf">get_openlineage_facets_on_failure</span><span class="p">(</span><span class="n">ti</span><span class="p">:</span> <span class="n">TaskInstance</span><span class="p">)</span> <span class="o">-></span> <span class="n">OperatorLineage</span><span class="p">:</span> <span class="o">...</span> |
| </pre></div> |
| </div> |
| <p>OpenLineage methods get called respectively when task instance changes state to:</p> |
| <ul class="simple"> |
| <li><p>RUNNING -> <code class="docutils literal notranslate"><span class="pre">get_openlineage_facets_on_start()</span></code></p></li> |
| <li><p>SUCCESS -> <code class="docutils literal notranslate"><span class="pre">get_openlineage_facets_on_complete()</span></code></p></li> |
| <li><p>FAILED -> <code class="docutils literal notranslate"><span class="pre">get_openlineage_facets_on_failure()</span></code></p></li> |
| </ul> |
| <p>At least one of the following methods must be implemented: <code class="docutils literal notranslate"><span class="pre">get_openlineage_facets_on_start()</span></code> or <code class="docutils literal notranslate"><span class="pre">get_openlineage_facets_on_complete()</span></code>. |
| For more details on what methods are called when others are missing, see <a class="reference internal" href="#ol-methods-best-practices-openlineage"><span class="std std-ref">How to properly implement OpenLineage methods?</span></a>.</p> |
| <p>Instead of returning complete OpenLineage event, the provider defines <code class="docutils literal notranslate"><span class="pre">OperatorLineage</span></code> structure to be returned by Operators:</p> |
| <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="nd">@define</span> |
| <span class="k">class</span><span class="w"> </span><span class="nc">OperatorLineage</span><span class="p">:</span> |
| <span class="n">inputs</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="n">Dataset</span><span class="p">]</span> <span class="o">=</span> <span class="n">Factory</span><span class="p">(</span><span class="nb">list</span><span class="p">)</span> |
| <span class="n">outputs</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="n">Dataset</span><span class="p">]</span> <span class="o">=</span> <span class="n">Factory</span><span class="p">(</span><span class="nb">list</span><span class="p">)</span> |
| <span class="n">run_facets</span><span class="p">:</span> <span class="nb">dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">RunFacet</span><span class="p">]</span> <span class="o">=</span> <span class="n">Factory</span><span class="p">(</span><span class="nb">dict</span><span class="p">)</span> |
| <span class="n">job_facets</span><span class="p">:</span> <span class="nb">dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">BaseFacet</span><span class="p">]</span> <span class="o">=</span> <span class="n">Factory</span><span class="p">(</span><span class="nb">dict</span><span class="p">)</span> |
| </pre></div> |
| </div> |
| <p>OpenLineage integration itself takes care to enrich it with things like general Airflow facets, proper event time and type, creating proper OpenLineage RunEvent.</p> |
| <section id="how-to-properly-implement-openlineage-methods"> |
| <span id="ol-methods-best-practices-openlineage"></span><h3>How to properly implement OpenLineage methods?<a class="headerlink" href="#how-to-properly-implement-openlineage-methods" title="Link to this heading">¶</a></h3> |
| <p>There are a couple of things worth noting when implementing OpenLineage in Operators.</p> |
| <p>First, do not import OpenLineage-related objects on top-level, but in OL method itself. |
| This allows users to use your provider even if they do not have OpenLineage provider installed.</p> |
| <p>Second important point is to make sure your provider returns OpenLineage-compliant dataset names. |
| It allows OpenLineage consumers to properly match information about datasets gathered from different sources. |
| The naming convention is described in the <a class="reference external" href="https://openlineage.io/docs/spec/naming">OpenLineage naming docs</a>.</p> |
| <p>Third, OpenLineage implementation should not waste time of users that do not use it. |
| This means not doing heavy processing or network calls in the <code class="docutils literal notranslate"><span class="pre">execute</span></code> method that aren’t used by it. |
| Better option is to save relevant information in Operator attributes - and then use it |
| in OpenLineage method. |
| Good example is <code class="docutils literal notranslate"><span class="pre">BigQueryExecuteQueryOperator</span></code>. It saves <code class="docutils literal notranslate"><span class="pre">job_ids</span></code> of queries that were executed. |
| <code class="docutils literal notranslate"><span class="pre">get_openlineage_facets_on_complete</span></code> then can call BigQuery API, asking for lineage of those tables, and transform it to OpenLineage format.</p> |
| <p>Fourth, it’s not necessary to implement all the methods. If all the datasets are known before <code class="docutils literal notranslate"><span class="pre">execute</span></code> is |
| called, and there’s no relevant runtime data, there might be no point to implementing <code class="docutils literal notranslate"><span class="pre">get_openlineage_facets_on_complete</span></code> |
| - the <code class="docutils literal notranslate"><span class="pre">get_openlineage_facets_on_start</span></code> method can provide all the data. And in reverse, if everything is unknown |
| before execute, there might be no point in writing <code class="docutils literal notranslate"><span class="pre">_on_start</span></code> method. |
| Similarly, if there’s no relevant failure data - or the failure conditions are unknown, |
| implementing <code class="docutils literal notranslate"><span class="pre">get_openlineage_facets_on_failure</span></code> is probably not worth it. In general: |
| if there’s no <code class="docutils literal notranslate"><span class="pre">on_failure</span></code> method, the <code class="docutils literal notranslate"><span class="pre">on_complete</span></code> method gets called instead. |
| If there’s no <code class="docutils literal notranslate"><span class="pre">on_failure</span></code> and <code class="docutils literal notranslate"><span class="pre">on_complete</span></code> method, the <code class="docutils literal notranslate"><span class="pre">on_start</span></code> gets called instead (both at the task start and task completion). |
| If there’s no <code class="docutils literal notranslate"><span class="pre">on_start</span></code> method the lineage information will not be included in START event, and the <code class="docutils literal notranslate"><span class="pre">on_complete</span></code> method will be called upon task completion.</p> |
| </section> |
| <section id="how-to-test-openlineage-methods"> |
| <h3>How to test OpenLineage methods?<a class="headerlink" href="#how-to-test-openlineage-methods" title="Link to this heading">¶</a></h3> |
| <p>Unit testing OpenLineage integration in Operators is very similar to testing Operators itself. |
| Objective of those tests is making sure the <code class="docutils literal notranslate"><span class="pre">get_openlineage_*</span></code> methods return proper <code class="docutils literal notranslate"><span class="pre">OperatorLineage</span></code> |
| data structure with relevant fields filled. It’s recommended to mock any external calls. |
| Authors of tests need to remember the condition of calling different OL methods is different. |
| <code class="docutils literal notranslate"><span class="pre">get_openlineage_facets_on_start</span></code> is called before <code class="docutils literal notranslate"><span class="pre">execute</span></code>, and as such, must not depend on values |
| that are set there.</p> |
| <p>See <a class="reference internal" href="#troubleshooting-openlineage"><span class="std std-ref">Troubleshooting</span></a> for details on how to troubleshoot OpenLineage locally.</p> |
| <p>There is no existing framework for system testing OpenLineage integration, but the easiest way it can be achieved is |
| by comparing emitted events (f.e. with <code class="docutils literal notranslate"><span class="pre">FileTransport</span></code>) against expected ones. |
| Objective of author of OpenLineage system test is to provide expected dictionary of event keys. |
| Event keys identify event send from particular Operator and method: they have structure <code class="docutils literal notranslate"><span class="pre"><dag_id>.<task_id>.event.<event_type></span></code>; |
| it’s always possible to identify particular event send from particular task this way. |
| The provided event structure does not have to contain all the fields that are in the resulting event. |
| Only the fields provided by test author can be compared; this allows to check only for fields particular |
| test cares about. It also allows to skip fields that are (semi) randomly generated, like <code class="docutils literal notranslate"><span class="pre">runId</span></code> or <code class="docutils literal notranslate"><span class="pre">eventTime</span></code>, |
| or just always the same in context of OpenLineage in Airflow, like <code class="docutils literal notranslate"><span class="pre">producer</span></code>.</p> |
| </section> |
| <section id="example"> |
| <h3>Example<a class="headerlink" href="#example" title="Link to this heading">¶</a></h3> |
| <p>Here’s example of properly implemented <code class="docutils literal notranslate"><span class="pre">get_openlineage_facets_on_complete</span></code> method, for <a class="reference external" href="https://github.com/apache/airflow/blob/main/providers/google/src/airflow/providers/google/cloud/transfers/gcs_to_gcs.py">GcsToGcsOperator</a>. |
| As there is some processing made in <code class="docutils literal notranslate"><span class="pre">execute</span></code> method, and there is no relevant failure data, implementing this single method is enough.</p> |
| <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="k">def</span><span class="w"> </span><span class="nf">get_openlineage_facets_on_complete</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">task_instance</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""</span> |
| <span class="sd"> Implementing _on_complete because execute method does preprocessing on internals.</span> |
| <span class="sd"> This means we won't have to normalize self.source_object and self.source_objects,</span> |
| <span class="sd"> destination bucket and so on.</span> |
| <span class="sd"> """</span> |
| <span class="kn">from</span><span class="w"> </span><span class="nn">airflow.providers.common.compat.openlineage.facet</span><span class="w"> </span><span class="kn">import</span> <span class="n">Dataset</span> |
| <span class="kn">from</span><span class="w"> </span><span class="nn">airflow.providers.openlineage.extractors</span><span class="w"> </span><span class="kn">import</span> <span class="n">OperatorLineage</span> |
| |
| <span class="k">return</span> <span class="n">OperatorLineage</span><span class="p">(</span> |
| <span class="n">inputs</span><span class="o">=</span><span class="p">[</span> |
| <span class="n">Dataset</span><span class="p">(</span><span class="n">namespace</span><span class="o">=</span><span class="sa">f</span><span class="s2">"gs://</span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">source_bucket</span><span class="si">}</span><span class="s2">"</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="n">source</span><span class="p">)</span> |
| <span class="k">for</span> <span class="n">source</span> <span class="ow">in</span> <span class="nb">sorted</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">resolved_source_objects</span><span class="p">)</span> |
| <span class="p">],</span> |
| <span class="n">outputs</span><span class="o">=</span><span class="p">[</span> |
| <span class="n">Dataset</span><span class="p">(</span><span class="n">namespace</span><span class="o">=</span><span class="sa">f</span><span class="s2">"gs://</span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">destination_bucket</span><span class="si">}</span><span class="s2">"</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="n">target</span><span class="p">)</span> |
| <span class="k">for</span> <span class="n">target</span> <span class="ow">in</span> <span class="nb">sorted</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">resolved_target_objects</span><span class="p">)</span> |
| <span class="p">],</span> |
| <span class="p">)</span> |
| </pre></div> |
| </div> |
| <p>For more examples of implemented OpenLineage methods, check out the source code of <a class="reference internal" href="../supported_classes.html#supported-classes-openlineage"><span class="std std-ref">Supported classes</span></a>.</p> |
| </section> |
| </section> |
| <section id="custom-extractors"> |
| <span id="custom-extractors-openlineage"></span><h2>Custom Extractors<a class="headerlink" href="#custom-extractors" title="Link to this heading">¶</a></h2> |
| <p>This approach is recommended when dealing with Operators that you can not modify (f.e. third party providers), but still want the lineage to be extracted from them. |
| If you want to extract lineage from your own Operators, you may prefer directly implementing OpenLineage methods as described in <a class="reference internal" href="#openlineage-methods-openlineage"><span class="std std-ref">OpenLineage methods</span></a>.</p> |
| <p>This approach works by detecting which Airflow Operators your Dag is using, and extracting lineage data from them using corresponding Extractors class.</p> |
| <section id="interface"> |
| <h3>Interface<a class="headerlink" href="#interface" title="Link to this heading">¶</a></h3> |
| <p>Custom Extractors have to derive from <a class="reference internal" href="../_api/airflow/providers/openlineage/extractors/base/index.html#airflow.providers.openlineage.extractors.base.BaseExtractor" title="airflow.providers.openlineage.extractors.base.BaseExtractor"><code class="xref py py-class docutils literal notranslate"><span class="pre">BaseExtractor</span></code></a> |
| and implement at least two methods: <code class="docutils literal notranslate"><span class="pre">_execute_extraction</span></code> and <code class="docutils literal notranslate"><span class="pre">get_operator_classnames</span></code>.</p> |
| <p>BaseExtractor defines three more methods: <code class="docutils literal notranslate"><span class="pre">extract</span></code>, <code class="docutils literal notranslate"><span class="pre">extract_on_complete</span></code> and <code class="docutils literal notranslate"><span class="pre">extract_on_failure</span></code>, |
| that are called and used to provide actual lineage data. |
| The difference is that <code class="docutils literal notranslate"><span class="pre">extract</span></code> is called before Operator’s <code class="docutils literal notranslate"><span class="pre">execute</span></code> method, while <code class="docutils literal notranslate"><span class="pre">extract_on_complete</span></code> and |
| <code class="docutils literal notranslate"><span class="pre">extract_on_failure</span></code> are called after - when the task either succeeds or fails, respectively. |
| By default, <code class="docutils literal notranslate"><span class="pre">extract</span></code> calls <code class="docutils literal notranslate"><span class="pre">_execute_extraction</span></code> method implemented in custom Extractor. |
| When the task succeeds, <code class="docutils literal notranslate"><span class="pre">extract_on_complete</span></code> is called and if not overwritten, by default, it delegates to <code class="docutils literal notranslate"><span class="pre">extract</span></code>. |
| When the task fails, <code class="docutils literal notranslate"><span class="pre">extract_on_failure</span></code> is called and if not overwritten, by default, it delegates to <code class="docutils literal notranslate"><span class="pre">extract_on_complete</span></code>. |
| If you want to provide some additional information available after the task execution, you can |
| override <code class="docutils literal notranslate"><span class="pre">extract_on_complete</span></code> and <code class="docutils literal notranslate"><span class="pre">extract_on_failure</span></code> methods. |
| This is useful for extracting data the Operator sets as it’s own properties during or after execution. |
| Good example is an SQL operator that sets <code class="docutils literal notranslate"><span class="pre">query_ids</span></code> after execution.</p> |
| <p>The <code class="docutils literal notranslate"><span class="pre">get_operator_classnames</span></code> is a classmethod that is used to provide list of Operators that your Extractor can get lineage from.</p> |
| <p>For example:</p> |
| <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="nd">@classmethod</span> |
| <span class="k">def</span><span class="w"> </span><span class="nf">get_operator_classnames</span><span class="p">(</span><span class="bp">cls</span><span class="p">)</span> <span class="o">-></span> <span class="n">List</span><span class="p">[</span><span class="nb">str</span><span class="p">]:</span> |
| <span class="k">return</span> <span class="p">[</span><span class="s1">'CustomPostgresOperator'</span><span class="p">]</span> |
| </pre></div> |
| </div> |
| <p>If the name of the Operator matches one of the names on the list, the Extractor will be instantiated - with Operator |
| provided in the Extractor’s <code class="docutils literal notranslate"><span class="pre">self.operator</span></code> property - and both <code class="docutils literal notranslate"><span class="pre">extract</span></code> and <code class="docutils literal notranslate"><span class="pre">extract_on_complete</span></code>/<code class="docutils literal notranslate"><span class="pre">extract_on_failure</span></code> methods will be called.</p> |
| <p>Both methods return <code class="docutils literal notranslate"><span class="pre">OperatorLineage</span></code> structure:</p> |
| <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="nd">@define</span> |
| <span class="k">class</span><span class="w"> </span><span class="nc">OperatorLineage</span><span class="p">:</span> |
| <span class="w"> </span><span class="sd">"""Structure returned from lineage extraction."""</span> |
| |
| <span class="n">inputs</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="n">Dataset</span><span class="p">]</span> <span class="o">=</span> <span class="n">Factory</span><span class="p">(</span><span class="nb">list</span><span class="p">)</span> |
| <span class="n">outputs</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="n">Dataset</span><span class="p">]</span> <span class="o">=</span> <span class="n">Factory</span><span class="p">(</span><span class="nb">list</span><span class="p">)</span> |
| <span class="n">run_facets</span><span class="p">:</span> <span class="nb">dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">RunFacet</span><span class="p">]</span> <span class="o">=</span> <span class="n">Factory</span><span class="p">(</span><span class="nb">dict</span><span class="p">)</span> |
| <span class="n">job_facets</span><span class="p">:</span> <span class="nb">dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">BaseFacet</span><span class="p">]</span> <span class="o">=</span> <span class="n">Factory</span><span class="p">(</span><span class="nb">dict</span><span class="p">)</span> |
| </pre></div> |
| </div> |
| <p>Inputs and outputs are lists of plain OpenLineage datasets (<cite>openlineage.client.event_v2.Dataset</cite>).</p> |
| <p><code class="docutils literal notranslate"><span class="pre">run_facets</span></code> and <code class="docutils literal notranslate"><span class="pre">job_facets</span></code> are dictionaries of optional RunFacets and JobFacets that would be attached to the job - for example, |
| you might want to attach <code class="docutils literal notranslate"><span class="pre">SqlJobFacet</span></code> if your Operator is executing SQL.</p> |
| <p>To learn more about facets in OpenLineage see <a class="reference internal" href="#custom-facets-openlineage"><span class="std std-ref">Custom Facets</span></a>.</p> |
| </section> |
| <section id="registering-custom-extractor"> |
| <h3>Registering Custom Extractor<a class="headerlink" href="#registering-custom-extractor" title="Link to this heading">¶</a></h3> |
| <p>OpenLineage integration does not know that you’ve provided an Extractor unless you’ll register it.</p> |
| <p>It can be done by using <code class="docutils literal notranslate"><span class="pre">extractors</span></code> option in Airflow configuration.</p> |
| <div class="highlight-ini notranslate"><div class="highlight"><pre><span></span><span class="k">[openlineage]</span> |
| <span class="na">transport = {"type"</span><span class="o">:</span><span class="w"> </span><span class="s">"http"</span><span class="na">, "url"</span><span class="o">:</span><span class="w"> </span><span class="s">"http://example.com:5000"</span><span class="na">}</span> |
| <span class="na">extractors</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="s">full.path.to.ExtractorClass</span><span class="c1">;full.path.to.AnotherExtractorClass</span> |
| </pre></div> |
| </div> |
| <p><code class="docutils literal notranslate"><span class="pre">AIRFLOW__OPENLINEAGE__EXTRACTORS</span></code> environment variable is an equivalent.</p> |
| <div class="highlight-ini notranslate"><div class="highlight"><pre><span></span><span class="na">AIRFLOW__OPENLINEAGE__EXTRACTORS</span><span class="o">=</span><span class="s">'full.path.to.ExtractorClass;full.path.to.AnotherExtractorClass'</span> |
| </pre></div> |
| </div> |
| <p>Optionally, you can separate them with whitespace. It’s useful if you’re providing them as part of some YAML file.</p> |
| <div class="highlight-ini notranslate"><div class="highlight"><pre><span></span><span class="na">AIRFLOW__OPENLINEAGE__EXTRACTORS</span><span class="o">:</span><span class="w"> </span><span class="s">>-</span> |
| <span class="w"> </span><span class="na">full.path.to.FirstExtractor;</span> |
| <span class="w"> </span><span class="na">full.path.to.SecondExtractor</span> |
| </pre></div> |
| </div> |
| <p>Remember to make sure that the path is importable for scheduler and worker.</p> |
| </section> |
| <section id="debugging-custom-extractor"> |
| <h3>Debugging Custom Extractor<a class="headerlink" href="#debugging-custom-extractor" title="Link to this heading">¶</a></h3> |
| <p>There are two common problems associated with custom Extractors.</p> |
| <p>First, is wrong path provided to <code class="docutils literal notranslate"><span class="pre">extractors</span></code> option in Airflow configuration. The path needs to be exactly the same as one you’d use from your code. |
| If the path is wrong or non-importable from worker, plugin will fail to load the Extractors and proper OpenLineage events for that Operator won’t be emitted.</p> |
| <p>Second one, and maybe more insidious, are imports from Airflow. Due to the fact that OpenLineage code gets instantiated when Airflow worker itself starts, |
| any import from Airflow can be unnoticeably cyclical. This causes OpenLineage extraction to fail.</p> |
| <p>To avoid this issue, import from Airflow only locally - in <code class="docutils literal notranslate"><span class="pre">_execute_extraction</span></code> or <code class="docutils literal notranslate"><span class="pre">extract_on_complete</span></code>/<code class="docutils literal notranslate"><span class="pre">extract_on_failure</span></code> methods. |
| If you need imports for type checking, guard them behind typing.TYPE_CHECKING.</p> |
| </section> |
| <section id="testing-custom-extractor"> |
| <h3>Testing Custom Extractor<a class="headerlink" href="#testing-custom-extractor" title="Link to this heading">¶</a></h3> |
| <p>As all code, custom Extractors should be tested. This section will provide some information about the most important |
| data structures to write tests for and some notes on troubleshooting. We assume prior knowledge of writing custom Extractors. |
| To learn more about how Operators and Extractors work together under the hood, check out <a class="reference internal" href="#custom-extractors-openlineage"><span class="std std-ref">Custom Extractors</span></a>.</p> |
| <p>When testing an Extractor, we want to firstly verify if <code class="docutils literal notranslate"><span class="pre">OperatorLineage</span></code> object is being created, |
| specifically verifying that the object is being built with the correct input and output datasets and relevant facets. |
| This is done in OpenLineage via pytest, with appropriate mocking and patching for connections and objects. |
| Check out <a class="reference external" href="https://github.com/apache/airflow/blob/main/providers/openlineage/tests/unit/openlineage/extractors/test_base.py">example tests</a>.</p> |
| <p>Testing each facet is also important, as data or graphs in the UI can render incorrectly if the facets are wrong. |
| For example, if the facet name is created incorrectly in the Extractor, then the Operator’s task will not show up in the lineage graph, |
| creating a gap in pipeline observability.</p> |
| <p>Even with unit tests, an Extractor may still not be operating as expected. |
| The easiest way to tell if data isn’t coming through correctly is if the UI elements are not showing up correctly in the Lineage tab.</p> |
| <p>See <a class="reference internal" href="#troubleshooting-openlineage"><span class="std std-ref">Troubleshooting</span></a> for details on how to troubleshoot OpenLineage locally.</p> |
| </section> |
| <section id="id1"> |
| <h3>Example<a class="headerlink" href="#id1" title="Link to this heading">¶</a></h3> |
| <p>This is an example of a simple Extractor for an Operator that executes export Query in BigQuery and saves the result to S3 file. |
| Some information is known before Operator’s <code class="docutils literal notranslate"><span class="pre">execute</span></code> method is called, and we can already extract some lineage in <code class="docutils literal notranslate"><span class="pre">_execute_extraction</span></code> method. |
| After Operator’s <code class="docutils literal notranslate"><span class="pre">execute</span></code> method is called, in <code class="docutils literal notranslate"><span class="pre">extract_on_complete</span></code>, we can simply attach some additional Facets |
| f.e. with Bigquery Job ID to what we’ve prepared earlier. We can also implement <code class="docutils literal notranslate"><span class="pre">extract_on_failure</span></code> method, if there is |
| a need to include some information only when task fails. This way, we get all possible information from the Operator.</p> |
| <p>Please note that this is just an example. There are some OpenLineage built-in features that can facilitate different processes, |
| like extracting column level lineage and inputs/outputs from SQL query with SQL parser.</p> |
| <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="kn">from</span><span class="w"> </span><span class="nn">airflow.models.baseoperator</span><span class="w"> </span><span class="kn">import</span> <span class="n">BaseOperator</span> |
| <span class="kn">from</span><span class="w"> </span><span class="nn">airflow.providers.openlineage.extractors.base</span><span class="w"> </span><span class="kn">import</span> <span class="n">BaseExtractor</span><span class="p">,</span> <span class="n">OperatorLineage</span> |
| <span class="kn">from</span><span class="w"> </span><span class="nn">airflow.providers.common.compat.openlineage.facet</span><span class="w"> </span><span class="kn">import</span> <span class="p">(</span> |
| <span class="n">Dataset</span><span class="p">,</span> |
| <span class="n">ExternalQueryRunFacet</span><span class="p">,</span> |
| <span class="n">ErrorMessageRunFacet</span><span class="p">,</span> |
| <span class="n">SQLJobFacet</span><span class="p">,</span> |
| <span class="p">)</span> |
| |
| |
| <span class="k">class</span><span class="w"> </span><span class="nc">ExampleOperator</span><span class="p">(</span><span class="n">BaseOperator</span><span class="p">):</span> |
| <span class="k">def</span><span class="w"> </span><span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">query</span><span class="p">,</span> <span class="n">bq_table_reference</span><span class="p">,</span> <span class="n">s3_path</span><span class="p">)</span> <span class="o">-></span> <span class="kc">None</span><span class="p">:</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">bq_table_reference</span> <span class="o">=</span> <span class="n">bq_table_reference</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">s3_path</span> <span class="o">=</span> <span class="n">s3_path</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">s3_file_name</span> <span class="o">=</span> <span class="n">s3_file_name</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">_job_id</span> <span class="o">=</span> <span class="kc">None</span> |
| |
| <span class="k">def</span><span class="w"> </span><span class="nf">execute</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">context</span><span class="p">)</span> <span class="o">-></span> <span class="n">Any</span><span class="p">:</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">_job_id</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">_error_message</span> <span class="o">=</span> <span class="n">run_query</span><span class="p">(</span><span class="n">query</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">query</span><span class="p">)</span> |
| |
| |
| <span class="k">class</span><span class="w"> </span><span class="nc">ExampleExtractor</span><span class="p">(</span><span class="n">BaseExtractor</span><span class="p">):</span> |
| <span class="nd">@classmethod</span> |
| <span class="k">def</span><span class="w"> </span><span class="nf">get_operator_classnames</span><span class="p">(</span><span class="bp">cls</span><span class="p">):</span> |
| <span class="k">return</span> <span class="p">[</span><span class="s2">"ExampleOperator"</span><span class="p">]</span> |
| |
| <span class="k">def</span><span class="w"> </span><span class="nf">_execute_extraction</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-></span> <span class="n">OperatorLineage</span><span class="p">:</span> |
| <span class="w"> </span><span class="sd">"""Define what we know before Operator's extract is called."""</span> |
| <span class="k">return</span> <span class="n">OperatorLineage</span><span class="p">(</span> |
| <span class="n">inputs</span><span class="o">=</span><span class="p">[</span><span class="n">Dataset</span><span class="p">(</span><span class="n">namespace</span><span class="o">=</span><span class="s2">"bigquery"</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">operator</span><span class="o">.</span><span class="n">bq_table_reference</span><span class="p">)],</span> |
| <span class="n">outputs</span><span class="o">=</span><span class="p">[</span><span class="n">Dataset</span><span class="p">(</span><span class="n">namespace</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">operator</span><span class="o">.</span><span class="n">s3_path</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">operator</span><span class="o">.</span><span class="n">s3_file_name</span><span class="p">)],</span> |
| <span class="n">job_facets</span><span class="o">=</span><span class="p">{</span> |
| <span class="s2">"sql"</span><span class="p">:</span> <span class="n">SQLJobFacet</span><span class="p">(</span> |
| <span class="n">query</span><span class="o">=</span><span class="s2">"EXPORT INTO ... OPTIONS(FORMAT=csv, SEP=';' ...) AS SELECT * FROM ... "</span> |
| <span class="p">)</span> |
| <span class="p">},</span> |
| <span class="p">)</span> |
| |
| <span class="k">def</span><span class="w"> </span><span class="nf">extract_on_complete</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">task_instance</span><span class="p">)</span> <span class="o">-></span> <span class="n">OperatorLineage</span><span class="p">:</span> |
| <span class="w"> </span><span class="sd">"""Add what we received after Operator's extract call."""</span> |
| <span class="n">lineage_metadata</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">extract</span><span class="p">()</span> |
| <span class="n">lineage_metadata</span><span class="o">.</span><span class="n">run_facets</span> <span class="o">=</span> <span class="p">{</span> |
| <span class="s2">"parent"</span><span class="p">:</span> <span class="n">ExternalQueryRunFacet</span><span class="p">(</span><span class="n">externalQueryId</span><span class="o">=</span><span class="n">task_instance</span><span class="o">.</span><span class="n">task</span><span class="o">.</span><span class="n">_job_id</span><span class="p">,</span> <span class="n">source</span><span class="o">=</span><span class="s2">"bigquery"</span><span class="p">)</span> |
| <span class="p">}</span> |
| <span class="k">return</span> <span class="n">lineage_metadata</span> |
| |
| <span class="k">def</span><span class="w"> </span><span class="nf">extract_on_failure</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">task_instance</span><span class="p">)</span> <span class="o">-></span> <span class="n">OperatorLineage</span><span class="p">:</span> |
| <span class="w"> </span><span class="sd">"""Add any failure-specific information."""</span> |
| <span class="n">lineage_metadata</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">extract_on_complete</span><span class="p">(</span><span class="n">task_instance</span><span class="p">)</span> |
| <span class="n">lineage_metadata</span><span class="o">.</span><span class="n">run_facets</span> <span class="o">=</span> <span class="p">{</span> |
| <span class="s2">"error"</span><span class="p">:</span> <span class="n">ErrorMessageRunFacet</span><span class="p">(</span> |
| <span class="n">message</span><span class="o">=</span><span class="n">task_instance</span><span class="o">.</span><span class="n">task</span><span class="o">.</span><span class="n">_error_message</span><span class="p">,</span> <span class="n">programmingLanguage</span><span class="o">=</span><span class="s2">"python"</span> |
| <span class="p">)</span> |
| <span class="p">}</span> |
| <span class="k">return</span> <span class="n">lineage_metadata</span> |
| </pre></div> |
| </div> |
| <p>For more examples of OpenLineage Extractors, check out the source code of |
| <a class="reference external" href="https://github.com/apache/airflow/blob/main/providers/openlineage/src/airflow/providers/openlineage/extractors/bash.py">BashExtractor</a> or |
| <a class="reference external" href="https://github.com/apache/airflow/blob/main/providers/openlineage/src/airflow/providers/openlineage/extractors/python.py">PythonExtractor</a>.</p> |
| </section> |
| </section> |
| <section id="custom-facets"> |
| <span id="custom-facets-openlineage"></span><h2>Custom Facets<a class="headerlink" href="#custom-facets" title="Link to this heading">¶</a></h2> |
| <p>To learn more about facets in OpenLineage, please refer to <a class="reference external" href="https://openlineage.io/docs/spec/facets/">facet documentation</a>. |
| Also check out <a class="reference external" href="https://github.com/OpenLineage/OpenLineage/blob/main/client/python/src/openlineage/client/facet.py">available facets</a> |
| and a blog post about <a class="reference external" href="https://openlineage.io/blog/extending-with-facets/">extending with facets</a>.</p> |
| <p>The OpenLineage spec might not contain all the facets you need to write your extractor, |
| in which case you will have to make your own <a class="reference external" href="https://openlineage.io/docs/spec/facets/custom-facets">custom facets</a>.</p> |
| <p>You can also inject your own custom facets in the lineage event’s run facet using the <code class="docutils literal notranslate"><span class="pre">custom_run_facets</span></code> Airflow configuration.</p> |
| <p>Steps to be taken,</p> |
| <ol class="arabic simple"> |
| <li><p>Write a function that returns the custom facets. You can write as many custom facet functions as needed.</p></li> |
| <li><p>Register the functions using the <code class="docutils literal notranslate"><span class="pre">custom_run_facets</span></code> Airflow configuration.</p></li> |
| </ol> |
| <p>Airflow OpenLineage listener will automatically execute these functions during the lineage event generation and append their return values to the run facet in the lineage event.</p> |
| <section id="writing-a-custom-facet-function"> |
| <h3>Writing a custom facet function<a class="headerlink" href="#writing-a-custom-facet-function" title="Link to this heading">¶</a></h3> |
| <ul class="simple"> |
| <li><p><strong>Input arguments:</strong> The function should accept two input arguments: <code class="docutils literal notranslate"><span class="pre">TaskInstance</span></code> and <code class="docutils literal notranslate"><span class="pre">TaskInstanceState</span></code>.</p></li> |
| <li><p><strong>Function body:</strong> Perform the logic needed to generate the custom facets. The custom facets must inherit from the <code class="docutils literal notranslate"><span class="pre">RunFacet</span></code> for the <code class="docutils literal notranslate"><span class="pre">_producer</span></code> and <code class="docutils literal notranslate"><span class="pre">_schemaURL</span></code> to be automatically added for the facet.</p></li> |
| <li><p><strong>Return value:</strong> The custom facets to be added to the lineage event. Return type should be <code class="docutils literal notranslate"><span class="pre">dict[str,</span> <span class="pre">RunFacet]</span></code> or <code class="docutils literal notranslate"><span class="pre">None</span></code>. You may choose to return <code class="docutils literal notranslate"><span class="pre">None</span></code>, if you do not want to add custom facets for certain criteria.</p></li> |
| </ul> |
| <p><strong>Example custom facet function</strong></p> |
| <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="kn">import</span><span class="w"> </span><span class="nn">attrs</span> |
| <span class="kn">from</span><span class="w"> </span><span class="nn">airflow.models.taskinstance</span><span class="w"> </span><span class="kn">import</span> <span class="n">TaskInstance</span><span class="p">,</span> <span class="n">TaskInstanceState</span> |
| <span class="kn">from</span><span class="w"> </span><span class="nn">airflow.providers.common.compat.openlineage.facet</span><span class="w"> </span><span class="kn">import</span> <span class="n">RunFacet</span> |
| |
| |
| <span class="nd">@attrs</span><span class="o">.</span><span class="n">define</span> |
| <span class="k">class</span><span class="w"> </span><span class="nc">MyCustomRunFacet</span><span class="p">(</span><span class="n">RunFacet</span><span class="p">):</span> |
| <span class="w"> </span><span class="sd">"""Define a custom facet."""</span> |
| |
| <span class="n">name</span><span class="p">:</span> <span class="nb">str</span> |
| <span class="n">jobState</span><span class="p">:</span> <span class="nb">str</span> |
| <span class="n">uniqueName</span><span class="p">:</span> <span class="nb">str</span> |
| <span class="n">displayName</span><span class="p">:</span> <span class="nb">str</span> |
| <span class="n">dagId</span><span class="p">:</span> <span class="nb">str</span> |
| <span class="n">taskId</span><span class="p">:</span> <span class="nb">str</span> |
| <span class="n">cluster</span><span class="p">:</span> <span class="nb">str</span> |
| <span class="n">custom_metadata</span><span class="p">:</span> <span class="nb">dict</span> |
| |
| |
| <span class="k">def</span><span class="w"> </span><span class="nf">get_my_custom_facet</span><span class="p">(</span> |
| <span class="n">task_instance</span><span class="p">:</span> <span class="n">TaskInstance</span><span class="p">,</span> <span class="n">ti_state</span><span class="p">:</span> <span class="n">TaskInstanceState</span> |
| <span class="p">)</span> <span class="o">-></span> <span class="nb">dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">RunFacet</span><span class="p">]</span> <span class="o">|</span> <span class="kc">None</span><span class="p">:</span> |
| <span class="n">operator_name</span> <span class="o">=</span> <span class="n">task_instance</span><span class="o">.</span><span class="n">task</span><span class="o">.</span><span class="n">operator_name</span> |
| <span class="n">custom_metadata</span> <span class="o">=</span> <span class="p">{}</span> |
| <span class="k">if</span> <span class="n">operator_name</span> <span class="o">==</span> <span class="s2">"BashOperator"</span><span class="p">:</span> |
| <span class="k">return</span> <span class="kc">None</span> |
| <span class="k">if</span> <span class="n">ti_state</span> <span class="o">==</span> <span class="n">TaskInstanceState</span><span class="o">.</span><span class="n">FAILED</span><span class="p">:</span> |
| <span class="n">custom_metadata</span><span class="p">[</span><span class="s2">"custom_key_failed"</span><span class="p">]</span> <span class="o">=</span> <span class="s2">"custom_value"</span> |
| <span class="n">job_unique_name</span> <span class="o">=</span> <span class="sa">f</span><span class="s2">"TEST.</span><span class="si">{</span><span class="n">task_instance</span><span class="o">.</span><span class="n">dag_id</span><span class="si">}</span><span class="s2">.</span><span class="si">{</span><span class="n">task_instance</span><span class="o">.</span><span class="n">task_id</span><span class="si">}</span><span class="s2">"</span> |
| <span class="k">return</span> <span class="p">{</span> |
| <span class="s2">"additional_run_facet"</span><span class="p">:</span> <span class="n">MyCustomRunFacet</span><span class="p">(</span> |
| <span class="n">name</span><span class="o">=</span><span class="s2">"test-lineage-namespace"</span><span class="p">,</span> |
| <span class="n">jobState</span><span class="o">=</span><span class="n">task_instance</span><span class="o">.</span><span class="n">state</span><span class="p">,</span> |
| <span class="n">uniqueName</span><span class="o">=</span><span class="n">job_unique_name</span><span class="p">,</span> |
| <span class="n">displayName</span><span class="o">=</span><span class="sa">f</span><span class="s2">"</span><span class="si">{</span><span class="n">task_instance</span><span class="o">.</span><span class="n">dag_id</span><span class="si">}</span><span class="s2">.</span><span class="si">{</span><span class="n">task_instance</span><span class="o">.</span><span class="n">task_id</span><span class="si">}</span><span class="s2">"</span><span class="p">,</span> |
| <span class="n">dagId</span><span class="o">=</span><span class="n">task_instance</span><span class="o">.</span><span class="n">dag_id</span><span class="p">,</span> |
| <span class="n">taskId</span><span class="o">=</span><span class="n">task_instance</span><span class="o">.</span><span class="n">task_id</span><span class="p">,</span> |
| <span class="n">cluster</span><span class="o">=</span><span class="s2">"TEST"</span><span class="p">,</span> |
| <span class="n">custom_metadata</span><span class="o">=</span><span class="n">custom_metadata</span><span class="p">,</span> |
| <span class="p">)</span> |
| <span class="p">}</span> |
| </pre></div> |
| </div> |
| </section> |
| <section id="register-the-custom-facet-functions"> |
| <h3>Register the custom facet functions<a class="headerlink" href="#register-the-custom-facet-functions" title="Link to this heading">¶</a></h3> |
| <p>Use the <code class="docutils literal notranslate"><span class="pre">custom_run_facets</span></code> Airflow configuration to register the custom run facet functions by passing |
| a string of semicolon separated full import path to the functions.</p> |
| <div class="highlight-ini notranslate"><div class="highlight"><pre><span></span><span class="k">[openlineage]</span> |
| <span class="na">transport = {"type"</span><span class="o">:</span><span class="w"> </span><span class="s">"http"</span><span class="na">, "url"</span><span class="o">:</span><span class="w"> </span><span class="s">"http://example.com:5000"</span><span class="na">, "endpoint"</span><span class="o">:</span><span class="w"> </span><span class="s">"api/v1/lineage"</span><span class="na">}</span> |
| <span class="na">custom_run_facets</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="s">full.path.to.get_my_custom_facet</span><span class="c1">;full.path.to.another_custom_facet_function</span> |
| </pre></div> |
| </div> |
| <p><code class="docutils literal notranslate"><span class="pre">AIRFLOW__OPENLINEAGE__CUSTOM_RUN_FACETS</span></code> environment variable is an equivalent.</p> |
| <div class="highlight-ini notranslate"><div class="highlight"><pre><span></span><span class="na">AIRFLOW__OPENLINEAGE__CUSTOM_RUN_FACETS</span><span class="o">=</span><span class="s">'full.path.to.get_my_custom_facet;full.path.to.another_custom_facet_function'</span> |
| </pre></div> |
| </div> |
| <div class="admonition note"> |
| <p class="admonition-title">Note</p> |
| <ul class="simple"> |
| <li><p>The custom facet functions are executed both at the START and COMPLETE/FAIL of the TaskInstance and added to the corresponding OpenLineage event.</p></li> |
| <li><p>When creating conditions on TaskInstance state, you should use second argument provided (<code class="docutils literal notranslate"><span class="pre">TaskInstanceState</span></code>) that will contain the state the task should be in. This may vary from ti.current_state() as the OpenLineage listener may get called before the TaskInstance’s state is updated in Airflow database.</p></li> |
| <li><p>When path to a single function is registered more than once, it will still be executed only once.</p></li> |
| <li><p>When duplicate custom facet keys are returned by multiple functions registered, the result of random function result will be added to the lineage event. Please avoid using duplicate facet keys as it can produce unexpected behaviour.</p></li> |
| </ul> |
| </div> |
| </section> |
| </section> |
| <section id="job-hierarchy"> |
| <span id="job-hierarchy-openlineage"></span><h2>Job Hierarchy<a class="headerlink" href="#job-hierarchy" title="Link to this heading">¶</a></h2> |
| <p>Apache Airflow features an inherent job hierarchy: Dags, large and independently schedulable units, comprise smaller, executable tasks.</p> |
| <p>OpenLineage reflects this structure in its Job Hierarchy model.</p> |
| <ul class="simple"> |
| <li><p>Upon Dag scheduling, a START event is emitted.</p></li> |
| <li><p>Subsequently, following Airflow’s task order, each task triggers:</p> |
| <ul> |
| <li><p>START events at TaskInstance start.</p></li> |
| <li><p>COMPLETE/FAILED events upon completion.</p></li> |
| </ul> |
| </li> |
| <li><p>Finally, upon Dag termination, a completion event (COMPLETE or FAILED) is emitted.</p></li> |
| </ul> |
| <p>TaskInstance events’ ParentRunFacet references the originating Dag run.</p> |
| </section> |
| <section id="troubleshooting"> |
| <span id="troubleshooting-openlineage"></span><h2>Troubleshooting<a class="headerlink" href="#troubleshooting" title="Link to this heading">¶</a></h2> |
| <p>When testing code locally, <a class="reference external" href="https://marquezproject.ai/docs/quickstart">Marquez</a> can be used to inspect the data being emitted—or not being emitted. |
| Using Marquez will allow you to figure out if the error is being caused by the Extractor or the API. |
| If data is being emitted from the Extractor as expected but isn’t making it to the UI, |
| then the Extractor is fine and an issue should be opened up in OpenLineage. However, if data is not being emitted properly, |
| it is likely that more unit tests are needed to cover Extractor behavior. |
| Marquez can help you pinpoint which facets are not being formed properly so you know where to add test coverage.</p> |
| <section id="debug-settings"> |
| <h3>Debug settings<a class="headerlink" href="#debug-settings" title="Link to this heading">¶</a></h3> |
| <p>For debugging purposes, ensure that both <a class="reference external" href="https://airflow.apache.org/docs/apache-airflow/stable/configurations-ref.html#logging-level">Airflow logging level</a> |
| and <a class="reference external" href="https://openlineage.io/docs/client/python#environment-variables">OpenLineage client logging level</a> is set to <code class="docutils literal notranslate"><span class="pre">DEBUG</span></code>. |
| The latest provider auto-syncs Airflow’s logging level with the OpenLineage client, removing the need for manual configuration.</p> |
| <p>For DebugFacet, containing additional information (e.g., list of all packages installed), to be appended to all OL events |
| enable <a class="reference internal" href="user.html#options-debug-mode"><span class="std std-ref">debug_mode</span></a> for OpenLineage integration.</p> |
| <p>Keep in mind that enabling these settings will increase the detail in Airflow logs (which will increase their size) and |
| add extra information to OpenLineage events. It’s recommended to use them temporarily, primarily for debugging purposes.</p> |
| <p>When seeking help with debugging, always try to provide the following:</p> |
| <ul class="simple"> |
| <li><p>Airflow scheduler logs with the logging level set to DEBUG</p></li> |
| <li><p>Airflow worker logs (task logs) with the logging level set to DEBUG</p></li> |
| <li><p>OpenLineage events with debug_mode enabled</p></li> |
| <li><p>Information about Airflow version and OpenLineage provider version</p></li> |
| <li><p>Information about any custom modifications made to the deployment environment where the Airflow is running</p></li> |
| </ul> |
| </section> |
| </section> |
| <section id="where-can-i-learn-more"> |
| <h2>Where can I learn more?<a class="headerlink" href="#where-can-i-learn-more" title="Link to this heading">¶</a></h2> |
| <ul class="simple"> |
| <li><p>Check out <a class="reference external" href="https://openlineage.io">OpenLineage website</a>.</p></li> |
| <li><p>Visit our <a class="reference external" href="https://github.com/OpenLineage/OpenLineage">GitHub repository</a>.</p></li> |
| <li><p>Watch multiple <a class="reference external" href="https://openlineage.io/resources#conference-talks">talks</a> about OpenLineage.</p></li> |
| </ul> |
| </section> |
| <section id="feedback"> |
| <h2>Feedback<a class="headerlink" href="#feedback" title="Link to this heading">¶</a></h2> |
| <p>You can reach out to us on <a class="reference external" href="http://bit.ly/OpenLineageSlack">slack</a> and leave us feedback!</p> |
| </section> |
| <section id="how-to-contribute"> |
| <h2>How to contribute<a class="headerlink" href="#how-to-contribute" title="Link to this heading">¶</a></h2> |
| <p>We welcome your contributions! OpenLineage is an Open Source project under active development, and we’d love your help!</p> |
| <p>Sounds fun? Check out our <a class="reference external" href="https://github.com/OpenLineage/OpenLineage/blob/main/CONTRIBUTING.md">new contributor guide</a> to get started.</p> |
| </section> |
| </section> |
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| <ul> |
| <li><a class="reference internal" href="#">Implementing OpenLineage in Operators</a><ul> |
| <li><a class="reference internal" href="#extraction-precedence">Extraction precedence</a></li> |
| <li><a class="reference internal" href="#openlineage-methods">OpenLineage methods</a><ul> |
| <li><a class="reference internal" href="#how-to-properly-implement-openlineage-methods">How to properly implement OpenLineage methods?</a></li> |
| <li><a class="reference internal" href="#how-to-test-openlineage-methods">How to test OpenLineage methods?</a></li> |
| <li><a class="reference internal" href="#example">Example</a></li> |
| </ul> |
| </li> |
| <li><a class="reference internal" href="#custom-extractors">Custom Extractors</a><ul> |
| <li><a class="reference internal" href="#interface">Interface</a></li> |
| <li><a class="reference internal" href="#registering-custom-extractor">Registering Custom Extractor</a></li> |
| <li><a class="reference internal" href="#debugging-custom-extractor">Debugging Custom Extractor</a></li> |
| <li><a class="reference internal" href="#testing-custom-extractor">Testing Custom Extractor</a></li> |
| <li><a class="reference internal" href="#id1">Example</a></li> |
| </ul> |
| </li> |
| <li><a class="reference internal" href="#custom-facets">Custom Facets</a><ul> |
| <li><a class="reference internal" href="#writing-a-custom-facet-function">Writing a custom facet function</a></li> |
| <li><a class="reference internal" href="#register-the-custom-facet-functions">Register the custom facet functions</a></li> |
| </ul> |
| </li> |
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