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# coding=utf-8
# --------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See License.txt in the project root for
# license information.
#
# Code generated by Microsoft (R) AutoRest Code Generator.
# Changes may cause incorrect behavior and will be lost if the code is
# regenerated.
# --------------------------------------------------------------------------
from .linked_service import LinkedService
class AzureDatabricksLinkedService(LinkedService):
"""Azure Databricks linked service.
:param additional_properties: Unmatched properties from the message are
deserialized this collection
:type additional_properties: dict[str, object]
:param connect_via: The integration runtime reference.
:type connect_via:
~azure.mgmt.datafactory.models.IntegrationRuntimeReference
:param description: Linked service description.
:type description: str
:param parameters: Parameters for linked service.
:type parameters: dict[str,
~azure.mgmt.datafactory.models.ParameterSpecification]
:param annotations: List of tags that can be used for describing the
Dataset.
:type annotations: list[object]
:param type: Constant filled by server.
:type type: str
:param domain: <REGION>.azuredatabricks.net, domain name of your
Databricks deployment. Type: string (or Expression with resultType
string).
:type domain: object
:param access_token: Access token for databricks REST API. Refer to
https://docs.azuredatabricks.net/api/latest/authentication.html. Type:
string (or Expression with resultType string).
:type access_token: ~azure.mgmt.datafactory.models.SecretBase
:param existing_cluster_id: The id of an existing cluster that will be
used for all runs of this job. Type: string (or Expression with resultType
string).
:type existing_cluster_id: object
:param new_cluster_version: The Spark version of new cluster. Type: string
(or Expression with resultType string).
:type new_cluster_version: object
:param new_cluster_num_of_worker: Number of worker nodes that new cluster
should have. A string formatted Int32, like '1' means numOfWorker is 1 or
'1:10' means auto-scale from 1 as min and 10 as max. Type: string (or
Expression with resultType string).
:type new_cluster_num_of_worker: object
:param new_cluster_node_type: The node types of new cluster. Type: string
(or Expression with resultType string).
:type new_cluster_node_type: object
:param new_cluster_spark_conf: a set of optional, user-specified Spark
configuration key-value pairs.
:type new_cluster_spark_conf: dict[str, object]
:param encrypted_credential: The encrypted credential used for
authentication. Credentials are encrypted using the integration runtime
credential manager. Type: string (or Expression with resultType string).
:type encrypted_credential: object
"""
_validation = {
'type': {'required': True},
'domain': {'required': True},
'access_token': {'required': True},
}
_attribute_map = {
'additional_properties': {'key': '', 'type': '{object}'},
'connect_via': {'key': 'connectVia', 'type': 'IntegrationRuntimeReference'},
'description': {'key': 'description', 'type': 'str'},
'parameters': {'key': 'parameters', 'type': '{ParameterSpecification}'},
'annotations': {'key': 'annotations', 'type': '[object]'},
'type': {'key': 'type', 'type': 'str'},
'domain': {'key': 'typeProperties.domain', 'type': 'object'},
'access_token': {'key': 'typeProperties.accessToken', 'type': 'SecretBase'},
'existing_cluster_id': {'key': 'typeProperties.existingClusterId', 'type': 'object'},
'new_cluster_version': {'key': 'typeProperties.newClusterVersion', 'type': 'object'},
'new_cluster_num_of_worker': {'key': 'typeProperties.newClusterNumOfWorker', 'type': 'object'},
'new_cluster_node_type': {'key': 'typeProperties.newClusterNodeType', 'type': 'object'},
'new_cluster_spark_conf': {'key': 'typeProperties.newClusterSparkConf', 'type': '{object}'},
'encrypted_credential': {'key': 'typeProperties.encryptedCredential', 'type': 'object'},
}
def __init__(self, domain, access_token, additional_properties=None, connect_via=None, description=None, parameters=None, annotations=None, existing_cluster_id=None, new_cluster_version=None, new_cluster_num_of_worker=None, new_cluster_node_type=None, new_cluster_spark_conf=None, encrypted_credential=None):
super(AzureDatabricksLinkedService, self).__init__(additional_properties=additional_properties, connect_via=connect_via, description=description, parameters=parameters, annotations=annotations)
self.domain = domain
self.access_token = access_token
self.existing_cluster_id = existing_cluster_id
self.new_cluster_version = new_cluster_version
self.new_cluster_num_of_worker = new_cluster_num_of_worker
self.new_cluster_node_type = new_cluster_node_type
self.new_cluster_spark_conf = new_cluster_spark_conf
self.encrypted_credential = encrypted_credential
self.type = 'AzureDatabricks'
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