feature: Enable default role for Spark processors (#3801)

Author: ivan-khvostishkov

src/sagemaker/spark/processing.py

@@ -122,11 +122,11 @@ def __init__(
             framework_version (str): The version of SageMaker PySpark.
             py_version (str): The version of python.
             container_version (str): The version of spark container.
-            role (str): An AWS IAM role name or ARN. The Amazon SageMaker training jobs
-                and APIs that create Amazon SageMaker endpoints use this role
-                to access training data and model artifacts. After the endpoint
-                is created, the inference code might use the IAM role, if it
-                needs to access an AWS resource.
+            role (str): An AWS IAM role name or ARN. Amazon SageMaker Processing
+                uses this role to access AWS resources, such as
+                data stored in Amazon S3 (default: None).
+                If not specified, the value from the defaults configuration file
+                will be used.
             instance_type (str): Type of EC2 instance to use for
                 processing, for example, 'ml.c4.xlarge'.
             instance_count (int): The number of instances to run
@@ -741,9 +741,9 @@ class PySparkProcessor(_SparkProcessorBase):
 
     def __init__(
         self,
-        role: str,
-        instance_type: Union[str, PipelineVariable],
-        instance_count: Union[int, PipelineVariable],
+        role: str = None,
+        instance_type: Union[str, PipelineVariable] = None,
+        instance_count: Union[int, PipelineVariable] = None,
         framework_version: Optional[str] = None,
         py_version: Optional[str] = None,
         container_version: Optional[str] = None,
@@ -769,11 +769,11 @@ def __init__(
             framework_version (str): The version of SageMaker PySpark.
             py_version (str): The version of python.
             container_version (str): The version of spark container.
-            role (str): An AWS IAM role name or ARN. The Amazon SageMaker training jobs
-                and APIs that create Amazon SageMaker endpoints use this role
-                to access training data and model artifacts. After the endpoint
-                is created, the inference code might use the IAM role, if it
-                needs to access an AWS resource.
+            role (str): An AWS IAM role name or ARN. Amazon SageMaker Processing
+                uses this role to access AWS resources, such as
+                data stored in Amazon S3 (default: None).
+                If not specified, the value from the defaults configuration file
+                will be used.
             instance_type (str or PipelineVariable): Type of EC2 instance to use for
                 processing, for example, 'ml.c4.xlarge'.
             instance_count (int or PipelineVariable): The number of instances to run
@@ -1018,9 +1018,9 @@ class SparkJarProcessor(_SparkProcessorBase):
 
     def __init__(
         self,
-        role: str,
-        instance_type: Union[str, PipelineVariable],
-        instance_count: Union[int, PipelineVariable],
+        role: str = None,
+        instance_type: Union[str, PipelineVariable] = None,
+        instance_count: Union[int, PipelineVariable] = None,
         framework_version: Optional[str] = None,
         py_version: Optional[str] = None,
         container_version: Optional[str] = None,
@@ -1046,11 +1046,11 @@ def __init__(
             framework_version (str): The version of SageMaker PySpark.
             py_version (str): The version of python.
             container_version (str): The version of spark container.
-            role (str): An AWS IAM role name or ARN. The Amazon SageMaker training jobs
-                and APIs that create Amazon SageMaker endpoints use this role
-                to access training data and model artifacts. After the endpoint
-                is created, the inference code might use the IAM role, if it
-                needs to access an AWS resource.
+            role (str): An AWS IAM role name or ARN. Amazon SageMaker Processing
+                uses this role to access AWS resources, such as
+                data stored in Amazon S3 (default: None).
+                If not specified, the value from the defaults configuration file
+                will be used.
             instance_type (str or PipelineVariable): Type of EC2 instance to use for
                 processing, for example, 'ml.c4.xlarge'.
             instance_count (int or PipelineVariable): The number of instances to run