Add Databricks config to Spark Job

plugins/flytekit-spark/flytekitplugins/spark/models.py

@@ -1,5 +1,5 @@
 import enum
-import typing
+from typing import Dict, Optional
 
 from flyteidl.plugins import spark_pb2 as _spark_task
 
@@ -22,6 +22,7 @@ def __init__(
         main_class,
         spark_conf,
         hadoop_conf,
+        databricks_conf,
         executor_path,
     ):
         """
@@ -37,22 +38,30 @@ def __init__(
         self._executor_path = executor_path
         self._spark_conf = spark_conf
         self._hadoop_conf = hadoop_conf
+        self._databricks_conf = databricks_conf
 
     def with_overrides(
-        self, new_spark_conf: typing.Dict[str, str] = None, new_hadoop_conf: typing.Dict[str, str] = None
+        self,
+        new_spark_conf: Optional[Dict[str, str]] = None,
+        new_hadoop_conf: Optional[Dict[str, str]] = None,
+        new_databricks_conf: Optional[str] = None,
     ) -> "SparkJob":
         if not new_spark_conf:
             new_spark_conf = self.spark_conf
 
         if not new_hadoop_conf:
             new_hadoop_conf = self.hadoop_conf
 
+        if not new_databricks_conf:
+            new_databricks_conf = self.databricks_conf
+
         return SparkJob(
             spark_type=self.spark_type,
             application_file=self.application_file,
             main_class=self.main_class,
             spark_conf=new_spark_conf,
             hadoop_conf=new_hadoop_conf,
+            databricks_conf=new_databricks_conf,
             executor_path=self.executor_path,
         )
 
@@ -104,6 +113,10 @@ def hadoop_conf(self):
         """
         return self._hadoop_conf
 
+    @property
+    def databricks_conf(self) -> str:
+        return self._databricks_conf
+
     def to_flyte_idl(self):
         """
         :rtype: flyteidl.plugins.spark_pb2.SparkJob
@@ -127,6 +140,7 @@ def to_flyte_idl(self):
             executorPath=self.executor_path,
             sparkConf=self.spark_conf,
             hadoopConf=self.hadoop_conf,
+            databricksConf=self.databricks_conf,
         )
 
     @classmethod
@@ -151,4 +165,5 @@ def from_flyte_idl(cls, pb2_object):
             main_class=pb2_object.mainClass,
             hadoop_conf=pb2_object.hadoopConf,
             executor_path=pb2_object.executorPath,
+            databricks_conf=pb2_object.databricksConf,
         )

plugins/flytekit-spark/flytekitplugins/spark/task.py

@@ -1,3 +1,5 @@
+import base64
+import json
 import os
 import typing
 from dataclasses import dataclass
@@ -27,6 +29,7 @@ class Spark(object):
 
     spark_conf: Optional[Dict[str, str]] = None
     hadoop_conf: Optional[Dict[str, str]] = None
+    databricks_conf: typing.Optional[dict] = None
 
     def __post_init__(self):
         if self.spark_conf is None:
@@ -35,6 +38,9 @@ def __post_init__(self):
         if self.hadoop_conf is None:
             self.hadoop_conf = {}
 
+        if self.databricks_conf is None:
+            self.databricks_conf = {}
+
 
 # This method does not reset the SparkSession since it's a bit hard to handle multiple
 # Spark sessions in a single application as it's described in:
@@ -95,6 +101,7 @@ def get_custom(self, settings: SerializationSettings) -> Dict[str, Any]:
         job = SparkJob(
             spark_conf=self.task_config.spark_conf,
             hadoop_conf=self.task_config.hadoop_conf,
+            databricks_conf=base64.b64encode(json.dumps(self.task_config.databricks_conf).encode()).decode(),
             application_file="local://" + settings.entrypoint_settings.path,
             executor_path=settings.python_interpreter,
             main_class="",

plugins/flytekit-spark/tests/test_spark_task.py

@@ -19,14 +19,32 @@ def reset_spark_session() -> None:
 
 
 def test_spark_task(reset_spark_session):
-    @task(task_config=Spark(spark_conf={"spark": "1"}))
+    databricks_conf = {
+        "name": "flytekit databricks plugin example",
+        "new_cluster": {
+            "spark_version": "11.0.x-scala2.12",
+            "node_type_id": "r3.xlarge",
+            "aws_attributes": {"availability": "ON_DEMAND"},
+            "num_workers": 4,
+            "docker_image": {"url": "pingsutw/databricks:latest"},
+        },
+        "timeout_seconds": 3600,
+        "max_retries": 1,
+        "spark_python_task": {
+            "python_file": "dbfs:///FileStore/tables/entrypoint-1.py",
+            "parameters": "ls",
+        },
+    }
+
+    @task(task_config=Spark(spark_conf={"spark": "1"}, databricks_conf=databricks_conf))
     def my_spark(a: str) -> int:
         session = flytekit.current_context().spark_session
         assert session.sparkContext.appName == "FlyteSpark: ex:local:local:local"
         return 10
 
     assert my_spark.task_config is not None
     assert my_spark.task_config.spark_conf == {"spark": "1"}
+    assert my_spark.task_config.databricks_conf == databricks_conf
 
     default_img = Image(name="default", fqn="test", tag="tag")
     settings = SerializationSettings(