Run dashboard on Ray port and set Dashboard link

dask_databricks/_version.py

@@ -0,0 +1,17 @@
+# file generated by setuptools_scm
+# don't change, don't track in version control
+TYPE_CHECKING = False
+if TYPE_CHECKING:
+    from typing import Tuple, Union
+
+    VERSION_TUPLE = Tuple[Union[int, str], ...]
+else:
+    VERSION_TUPLE = object
+
+version: str
+__version__: str
+__version_tuple__: VERSION_TUPLE
+version_tuple: VERSION_TUPLE
+
+__version__ = version = '0.1.dev15+g4d11272.d20231108'
+__version_tuple__ = version_tuple = (0, 1, 'dev15', 'g4d11272.d20231108')

dask_databricks/cli.py

@@ -38,7 +38,7 @@ def run():
 
     if DB_IS_DRIVER == "TRUE":
         log.info("This node is the Dask scheduler.")
-        subprocess.Popen(["dask", "scheduler"])
+        subprocess.Popen(["dask", "scheduler", "--dashboard-address", ":8265"])
     else:
         log.info("This node is a Dask worker.")
         log.info(f"Connecting to Dask scheduler at {DB_DRIVER_IP}:8786")

dask_databricks/databrickscluster.py

@@ -39,6 +39,13 @@ async def _start(self):
         self.scheduler_comm = rpc(f"{self.spark_local_ip}:8786")
         await super()._start()
 
+    def dashboard_link(self):
+        if spark is None:
+            raise RuntimeError("Unable to locate spark session. Are you running this on a Databricks driver node?")
+        cluster_id = spark.conf.get("spark.databricks.clusterUsageTags.clusterId")
+        org_id = spark.conf.get("spark.databricks.clusterUsageTags.orgId")
+        return f"https://dbc-dp-{org_id}.cloud.databricks.com/driver-proxy/o/{org_id}/{cluster_id}/8265/status"
+
 
 def get_client():
     """Get a Dask client connected to a Databricks cluster."""