new commit

docs/content/_navigation.json

@@ -875,6 +875,11 @@
           {
             "title": "Details and customization",
             "path": "/guides/dagster-pipes/dagster-pipes-details-and-customization"
+          },
+          {
+            "title": "Integrating Databricks with Dagster Pipes",
+            "path": "/guides/dagster-pipes/databricks"
+
           }
         ]
       },

docs/screenshots/guides/dagster-pipes/databricks.yaml

@@ -0,0 +1,6 @@
+- id: run.png
+  workspace: examples/docs_snippets/docs_snippets/legacy/dagster_pandas_guide/workspace.yaml
+  steps:
+    - materialize the `databricks_asset`
+    - go to the Run page for the launched run
+

examples/docs_snippets/docs_snippets/guides/dagster/dagster_pipes/databricks/databricks_asset_client.py

@@ -0,0 +1,70 @@
+# start_databricks_asset
+### dagster_databricks_pipes.py
+
+import os
+import sys
+
+from dagster_databricks import PipesDatabricksClient
+
+from dagster import AssetExecutionContext, Definitions, EnvVar, asset
+from databricks.sdk import WorkspaceClient
+from databricks.sdk.service import jobs
+
+
+@asset
+def databricks_asset(
+    context: AssetExecutionContext, pipes_databricks: PipesDatabricksClient
+):
+    task = jobs.SubmitTask.from_dict(
+        {
+            # The cluster settings below are somewhat arbitrary. Dagster Pipes is
+            # not dependent on a specific spark version, node type, or number of
+            # workers.
+            "new_cluster": {
+                "spark_version": "12.2.x-scala2.12",
+                "node_type_id": "i3.xlarge",
+                "num_workers": 0,
+                "cluster_log_conf": {
+                    "dbfs": {"destination": "dbfs:/cluster-logs-dir-noexist"},
+                },
+            },
+            "libraries": [
+                # Include the latest published version of dagster-pipes on PyPI
+                # in the task environment
+                {"pypi": {"package": "dagster-pipes"}},
+            ],
+            "task_key": "some-key",
+            "spark_python_task": {
+                "python_file": "dbfs:/my_python_script.py",  # location of target code file
+                "source": jobs.Source.WORKSPACE,
+            },
+        }
+    )
+
+    print("This will be forwarded back to Dagster stdout")  # noqa: T201
+    print("This will be forwarded back to Dagster stderr", file=sys.stderr)  # noqa: T201
+
+    extras = {"some_parameter": 100}
+
+    return pipes_databricks.run(
+        task=task,
+        context=context,
+        extras=extras,
+    ).get_materialize_result()
+
+
+# end_databricks_asset
+
+# start_definitions
+
+pipes_databricks_resource = PipesDatabricksClient(
+    client=WorkspaceClient(
+        host=os.getenv("DATABRICKS_HOST"),
+        token=os.getenv("DATABRICKS_TOKEN"),
+    )
+)
+
+defs = Definitions(
+    assets=[databricks_asset], resources={"pipes_databricks": pipes_databricks_resource}
+)
+# end_definitions