feat: automatically inject OL transport info into spark jobs

docs/apache-airflow-providers-openlineage/guides/user.rst

@@ -451,6 +451,33 @@ You can enable this automation by setting ``spark_inject_parent_job_info`` optio
   AIRFLOW__OPENLINEAGE__SPARK_INJECT_PARENT_JOB_INFO=true
 
 
+Passing transport information to Spark jobs
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+OpenLineage integration can automatically inject Airflow's transport information into Spark application properties,
+for :ref:`supported Operators <supported_classes:openlineage>`.
+It allows Spark integration to send events to the same backend as Airflow integration without manual configuration.
+See `Scheduling from Airflow <https://openlineage.io/docs/integrations/spark/configuration/airflow>`_.
+
+.. note::
+
+  If any of the ``spark.openlineage.transport*`` properties are manually specified in the Spark job configuration, the integration will refrain from injecting transport properties to ensure that manually provided values are preserved.
+
+You can enable this automation by setting ``spark_inject_transport_info`` option to ``true`` in Airflow configuration.
+
+.. code-block:: ini
+
+    [openlineage]
+    transport = {"type": "http", "url": "http://example.com:5000", "endpoint": "api/v1/lineage"}
+    spark_inject_transport_info = true
+
+``AIRFLOW__OPENLINEAGE__SPARK_INJECT_TRANSPORT_INFO`` environment variable is an equivalent.
+
+.. code-block:: ini
+
+  AIRFLOW__OPENLINEAGE__SPARK_INJECT_TRANSPORT_INFO=true
+
+
 Troubleshooting
 ===============
 

docs/exts/templates/openlineage.rst.jinja2

@@ -34,12 +34,15 @@ See :ref:`automatic injection of parent job information <options:spark_inject_pa
 apache-airflow-providers-google
 """""""""""""""""""""""""""""""
 
-- :class:`~airflow.providers.google.cloud.operators.dataproc.DataprocSubmitJobOperator`
-    - Parent Job Information
 - :class:`~airflow.providers.google.cloud.operators.dataproc.DataprocCreateBatchOperator`
     - Parent Job Information
+    - Transport Information (only HTTP transport is supported for now (with api_key auth, if any))
 - :class:`~airflow.providers.google.cloud.operators.dataproc.DataprocInstantiateInlineWorkflowTemplateOperator`
     - Parent Job Information
+    - Transport Information (only HTTP transport is supported for now (with api_key auth, if any))
+- :class:`~airflow.providers.google.cloud.operators.dataproc.DataprocSubmitJobOperator`
+    - Parent Job Information
+    - Transport Information (only HTTP transport is supported for now (with api_key auth, if any))
 
 
 :class:`~airflow.providers.common.sql.operators.sql.SQLExecuteQueryOperator`

generated/provider_dependencies.json

@@ -628,7 +628,7 @@
   "google": {
     "deps": [
       "PyOpenSSL>=23.0.0",
-      "apache-airflow-providers-common-compat>=1.3.0",
+      "apache-airflow-providers-common-compat>=1.4.0",
       "apache-airflow-providers-common-sql>=1.20.0",
       "apache-airflow>=2.9.0",
       "asgiref>=3.5.2",
@@ -970,7 +970,7 @@
   },
   "openlineage": {
     "deps": [
-      "apache-airflow-providers-common-compat>=1.3.0",
+      "apache-airflow-providers-common-compat>=1.4.0",
       "apache-airflow-providers-common-sql>=1.20.0",
       "apache-airflow>=2.9.0",
       "attrs>=22.2",

providers/src/airflow/providers/common/compat/__init__.py

@@ -29,7 +29,7 @@
 
 __all__ = ["__version__"]
 
-__version__ = "1.3.0"
+__version__ = "1.4.0"
 
 if packaging.version.parse(packaging.version.parse(airflow_version).base_version) < packaging.version.parse(
     "2.9.0"

providers/src/airflow/providers/common/compat/openlineage/utils/spark.py

@@ -23,11 +23,15 @@
 log = logging.getLogger(__name__)
 
 if TYPE_CHECKING:
-    from airflow.providers.openlineage.utils.spark import inject_parent_job_information_into_spark_properties
+    from airflow.providers.openlineage.utils.spark import (
+        inject_parent_job_information_into_spark_properties,
+        inject_transport_information_into_spark_properties,
+    )
 else:
     try:
         from airflow.providers.openlineage.utils.spark import (
             inject_parent_job_information_into_spark_properties,
+            inject_transport_information_into_spark_properties,
         )
     except ImportError:
         try:
@@ -64,5 +68,63 @@ def inject_parent_job_information_into_spark_properties(properties: dict, contex
                 }
                 return {**properties, **ol_parent_job_properties}
 
+        try:
+            from airflow.providers.openlineage.plugins.listener import get_openlineage_listener
+        except ImportError:
+
+            def inject_transport_information_into_spark_properties(properties: dict, context) -> dict:
+                log.warning(
+                    "Could not import `airflow.providers.openlineage.plugins.listener`."
+                    "Skipping the injection of OpenLineage transport information into Spark properties."
+                )
+                return properties
+
+        else:
+
+            def inject_transport_information_into_spark_properties(properties: dict, context) -> dict:
+                if any(str(key).startswith("spark.openlineage.transport") for key in properties):
+                    log.info(
+                        "Some OpenLineage properties with transport information are already present "
+                        "in Spark properties. Skipping the injection of OpenLineage "
+                        "transport information into Spark properties."
+                    )
+                    return properties
+
+                transport = get_openlineage_listener().adapter.get_or_create_openlineage_client().transport
+                if transport.kind != "http":
+                    log.info(
+                        "OpenLineage transport type `%s` does not support automatic "
+                        "injection of OpenLineage transport information into Spark properties.",
+                        transport.kind,
+                    )
+                    return {}
+
+                transport_properties = {
+                    "spark.openlineage.transport.type": "http",
+                    "spark.openlineage.transport.url": transport.url,
+                    "spark.openlineage.transport.endpoint": transport.endpoint,
+                    # Timeout is converted to milliseconds, as required by Spark integration,
+                    "spark.openlineage.transport.timeoutInMillis": str(int(transport.timeout * 1000)),
+                }
+                if transport.compression:
+                    transport_properties["spark.openlineage.transport.compression"] = str(
+                        transport.compression
+                    )
+
+                if hasattr(transport.config.auth, "api_key") and transport.config.auth.get_bearer():
+                    transport_properties["spark.openlineage.transport.auth.type"] = "api_key"
+                    transport_properties["spark.openlineage.transport.auth.apiKey"] = (
+                        transport.config.auth.get_bearer()
+                    )
+
+                if hasattr(transport.config, "custom_headers") and transport.config.custom_headers:
+                    for key, value in transport.config.custom_headers.items():
+                        transport_properties[f"spark.openlineage.transport.headers.{key}"] = value
+
+                return {**properties, **transport_properties}
+
 
-__all__ = ["inject_parent_job_information_into_spark_properties"]
+__all__ = [
+    "inject_parent_job_information_into_spark_properties",
+    "inject_transport_information_into_spark_properties",
+]

providers/src/airflow/providers/common/compat/provider.yaml

@@ -25,6 +25,7 @@ state: ready
 source-date-epoch: 1731569875
 # note that those versions are maintained by release manager - do not update them manually
 versions:
+  - 1.4.0
   - 1.3.0
   - 1.2.2
   - 1.2.1

providers/src/airflow/providers/google/cloud/openlineage/utils.py

@@ -43,6 +43,7 @@
 )
 from airflow.providers.common.compat.openlineage.utils.spark import (
     inject_parent_job_information_into_spark_properties,
+    inject_transport_information_into_spark_properties,
 )
 from airflow.providers.google import __version__ as provider_version
 from airflow.providers.google.cloud.hooks.gcs import _parse_gcs_url
@@ -453,7 +454,7 @@ def _replace_dataproc_job_properties(job: dict, job_type: str, new_properties: d
 
 
 def inject_openlineage_properties_into_dataproc_job(
-    job: dict, context: Context, inject_parent_job_info: bool
+    job: dict, context: Context, inject_parent_job_info: bool, inject_transport_info: bool
 ) -> dict:
     """
     Inject OpenLineage properties into Spark job definition.
@@ -466,18 +467,19 @@ def inject_openlineage_properties_into_dataproc_job(
             - OpenLineage provider is not accessible.
             - The job type is not supported.
             - Automatic parent job information injection is disabled.
-            - Any OpenLineage properties with parent job information are already present
+            - Any OpenLineage properties with respective information are already present
               in the Spark job definition.
 
     Args:
         job: The original Dataproc job definition.
         context: The Airflow context in which the job is running.
         inject_parent_job_info: Flag indicating whether to inject parent job information.
+        inject_transport_info: Flag indicating whether to inject transport information.
 
     Returns:
         The modified job definition with OpenLineage properties injected, if applicable.
     """
-    if not inject_parent_job_info:
+    if not inject_parent_job_info and not inject_transport_info:
         log.debug("Automatic injection of OpenLineage information is disabled.")
         return job
 
@@ -497,7 +499,17 @@ def inject_openlineage_properties_into_dataproc_job(
 
     properties = job[job_type].get("properties", {})
 
-    properties = inject_parent_job_information_into_spark_properties(properties=properties, context=context)
+    if inject_parent_job_info:
+        log.debug("Injecting OpenLineage parent job information into Spark properties.")
+        properties = inject_parent_job_information_into_spark_properties(
+            properties=properties, context=context
+        )
+
+    if inject_transport_info:
+        log.debug("Injecting OpenLineage transport information into Spark properties.")
+        properties = inject_transport_information_into_spark_properties(
+            properties=properties, context=context
+        )
 
     job_with_ol_config = _replace_dataproc_job_properties(
         job=job, job_type=job_type, new_properties=properties
@@ -587,7 +599,7 @@ def _replace_dataproc_batch_properties(batch: dict | Batch, new_properties: dict
 
 
 def inject_openlineage_properties_into_dataproc_batch(
-    batch: dict | Batch, context: Context, inject_parent_job_info: bool
+    batch: dict | Batch, context: Context, inject_parent_job_info: bool, inject_transport_info: bool
 ) -> dict | Batch:
     """
     Inject OpenLineage properties into Dataproc batch definition.
@@ -600,18 +612,19 @@ def inject_openlineage_properties_into_dataproc_batch(
             - OpenLineage provider is not accessible.
             - The batch type is not supported.
             - Automatic parent job information injection is disabled.
-            - Any OpenLineage properties with parent job information are already present
+            - Any OpenLineage properties with respective information are already present
               in the Spark job configuration.
 
     Args:
         batch: The original Dataproc batch definition.
         context: The Airflow context in which the job is running.
         inject_parent_job_info: Flag indicating whether to inject parent job information.
+        inject_transport_info: Flag indicating whether to inject transport information.
 
     Returns:
         The modified batch definition with OpenLineage properties injected, if applicable.
     """
-    if not inject_parent_job_info:
+    if not inject_parent_job_info and not inject_transport_info:
         log.debug("Automatic injection of OpenLineage information is disabled.")
         return batch
 
@@ -631,14 +644,24 @@ def inject_openlineage_properties_into_dataproc_batch(
 
     properties = _extract_dataproc_batch_properties(batch)
 
-    properties = inject_parent_job_information_into_spark_properties(properties=properties, context=context)
+    if inject_parent_job_info:
+        log.debug("Injecting OpenLineage parent job information into Spark properties.")
+        properties = inject_parent_job_information_into_spark_properties(
+            properties=properties, context=context
+        )
+
+    if inject_transport_info:
+        log.debug("Injecting OpenLineage transport information into Spark properties.")
+        properties = inject_transport_information_into_spark_properties(
+            properties=properties, context=context
+        )
 
     batch_with_ol_config = _replace_dataproc_batch_properties(batch=batch, new_properties=properties)
     return batch_with_ol_config
 
 
 def inject_openlineage_properties_into_dataproc_workflow_template(
-    template: dict, context: Context, inject_parent_job_info: bool
+    template: dict, context: Context, inject_parent_job_info: bool, inject_transport_info: bool
 ) -> dict:
     """
     Inject OpenLineage properties into Spark jobs in Workflow Template.
@@ -658,11 +681,12 @@ def inject_openlineage_properties_into_dataproc_workflow_template(
         template: The original Dataproc Workflow Template definition.
         context: The Airflow context in which the job is running.
         inject_parent_job_info: Flag indicating whether to inject parent job information.
+        inject_transport_info: Flag indicating whether to inject transport information.
 
     Returns:
         The modified Workflow Template definition with OpenLineage properties injected, if applicable.
     """
-    if not inject_parent_job_info:
+    if not inject_parent_job_info and not inject_transport_info:
         log.debug("Automatic injection of OpenLineage information is disabled.")
         return template
 
@@ -688,9 +712,17 @@ def inject_openlineage_properties_into_dataproc_workflow_template(
 
         properties = single_job_definition[job_type].get("properties", {})
 
-        properties = inject_parent_job_information_into_spark_properties(
-            properties=properties, context=context
-        )
+        if inject_parent_job_info:
+            log.debug("Injecting OpenLineage parent job information into Spark properties.")
+            properties = inject_parent_job_information_into_spark_properties(
+                properties=properties, context=context
+            )
+
+        if inject_transport_info:
+            log.debug("Injecting OpenLineage transport information into Spark properties.")
+            properties = inject_transport_information_into_spark_properties(
+                properties=properties, context=context
+            )
 
         job_with_ol_config = _replace_dataproc_job_properties(
             job=single_job_definition, job_type=job_type, new_properties=properties