# 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 typing import Any, AsyncIterable, Callable, Dict, Generic, Optional, TypeVar, Union
import warnings
from azure.core.async_paging import AsyncItemPaged, AsyncList
from azure.core.exceptions import HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
from azure.core.pipeline import PipelineResponse
from azure.core.pipeline.transport import AsyncHttpResponse, HttpRequest
from azure.core.polling import AsyncLROPoller, AsyncNoPolling, AsyncPollingMethod
from azure.core.polling.async_base_polling import AsyncLROBasePolling
from ... import models
T = TypeVar('T')
ClsType = Optional[Callable[[PipelineResponse[HttpRequest, AsyncHttpResponse], T, Dict[str, Any]], Any]]
[docs]class SparkJobDefinitionOperations:
"""SparkJobDefinitionOperations async operations.
You should not instantiate this class directly. Instead, you should create a Client instance that
instantiates it for you and attaches it as an attribute.
:ivar models: Alias to model classes used in this operation group.
:type models: ~azure.synapse.artifacts.models
:param client: Client for service requests.
:param config: Configuration of service client.
:param serializer: An object model serializer.
:param deserializer: An object model deserializer.
"""
models = models
def __init__(self, client, config, serializer, deserializer) -> None:
self._client = client
self._serialize = serializer
self._deserialize = deserializer
self._config = config
[docs] def get_spark_job_definitions_by_workspace(
self,
**kwargs
) -> AsyncIterable["models.SparkJobDefinitionsListResponse"]:
"""Lists spark job definitions.
:keyword callable cls: A custom type or function that will be passed the direct response
:return: An iterator like instance of either SparkJobDefinitionsListResponse or the result of cls(response)
:rtype: ~azure.core.async_paging.AsyncItemPaged[~azure.synapse.artifacts.models.SparkJobDefinitionsListResponse]
:raises: ~azure.core.exceptions.HttpResponseError
"""
cls = kwargs.pop('cls', None) # type: ClsType["models.SparkJobDefinitionsListResponse"]
error_map = {404: ResourceNotFoundError, 409: ResourceExistsError}
error_map.update(kwargs.pop('error_map', {}))
api_version = "2019-06-01-preview"
def prepare_request(next_link=None):
# Construct headers
header_parameters = {} # type: Dict[str, Any]
header_parameters['Accept'] = 'application/json'
if not next_link:
# Construct URL
url = self.get_spark_job_definitions_by_workspace.metadata['url'] # type: ignore
path_format_arguments = {
'endpoint': self._serialize.url("self._config.endpoint", self._config.endpoint, 'str', skip_quote=True),
}
url = self._client.format_url(url, **path_format_arguments)
# Construct parameters
query_parameters = {} # type: Dict[str, Any]
query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str')
request = self._client.get(url, query_parameters, header_parameters)
else:
url = next_link
query_parameters = {} # type: Dict[str, Any]
path_format_arguments = {
'endpoint': self._serialize.url("self._config.endpoint", self._config.endpoint, 'str', skip_quote=True),
}
url = self._client.format_url(url, **path_format_arguments)
request = self._client.get(url, query_parameters, header_parameters)
return request
async def extract_data(pipeline_response):
deserialized = self._deserialize('SparkJobDefinitionsListResponse', pipeline_response)
list_of_elem = deserialized.value
if cls:
list_of_elem = cls(list_of_elem)
return deserialized.next_link or None, AsyncList(list_of_elem)
async def get_next(next_link=None):
request = prepare_request(next_link)
pipeline_response = await self._client._pipeline.run(request, stream=False, **kwargs)
response = pipeline_response.http_response
if response.status_code not in [200]:
error = self._deserialize(models.CloudError, response)
map_error(status_code=response.status_code, response=response, error_map=error_map)
raise HttpResponseError(response=response, model=error)
return pipeline_response
return AsyncItemPaged(
get_next, extract_data
)
get_spark_job_definitions_by_workspace.metadata = {'url': '/sparkJobDefinitions'} # type: ignore
[docs] async def create_or_update_spark_job_definition(
self,
spark_job_definition_name: str,
properties: "models.SparkJobDefinition",
if_match: Optional[str] = None,
**kwargs
) -> "models.SparkJobDefinitionResource":
"""Creates or updates a Spark Job Definition.
:param spark_job_definition_name: The spark job definition name.
:type spark_job_definition_name: str
:param properties: Properties of spark job definition.
:type properties: ~azure.synapse.artifacts.models.SparkJobDefinition
:param if_match: ETag of the Spark Job Definition entity. Should only be specified for update,
for which it should match existing entity or can be * for unconditional update.
:type if_match: str
:keyword callable cls: A custom type or function that will be passed the direct response
:return: SparkJobDefinitionResource, or the result of cls(response)
:rtype: ~azure.synapse.artifacts.models.SparkJobDefinitionResource
:raises: ~azure.core.exceptions.HttpResponseError
"""
cls = kwargs.pop('cls', None) # type: ClsType["models.SparkJobDefinitionResource"]
error_map = {404: ResourceNotFoundError, 409: ResourceExistsError}
error_map.update(kwargs.pop('error_map', {}))
_spark_job_definition = models.SparkJobDefinitionResource(properties=properties)
api_version = "2019-06-01-preview"
content_type = kwargs.pop("content_type", "application/json")
# Construct URL
url = self.create_or_update_spark_job_definition.metadata['url'] # type: ignore
path_format_arguments = {
'endpoint': self._serialize.url("self._config.endpoint", self._config.endpoint, 'str', skip_quote=True),
'sparkJobDefinitionName': self._serialize.url("spark_job_definition_name", spark_job_definition_name, 'str'),
}
url = self._client.format_url(url, **path_format_arguments)
# Construct parameters
query_parameters = {} # type: Dict[str, Any]
query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str')
# Construct headers
header_parameters = {} # type: Dict[str, Any]
if if_match is not None:
header_parameters['If-Match'] = self._serialize.header("if_match", if_match, 'str')
header_parameters['Content-Type'] = self._serialize.header("content_type", content_type, 'str')
header_parameters['Accept'] = 'application/json'
body_content_kwargs = {} # type: Dict[str, Any]
body_content = self._serialize.body(_spark_job_definition, 'SparkJobDefinitionResource')
body_content_kwargs['content'] = body_content
request = self._client.put(url, query_parameters, header_parameters, **body_content_kwargs)
pipeline_response = await self._client._pipeline.run(request, stream=False, **kwargs)
response = pipeline_response.http_response
if response.status_code not in [200]:
map_error(status_code=response.status_code, response=response, error_map=error_map)
error = self._deserialize(models.CloudError, response)
raise HttpResponseError(response=response, model=error)
deserialized = self._deserialize('SparkJobDefinitionResource', pipeline_response)
if cls:
return cls(pipeline_response, deserialized, {})
return deserialized
create_or_update_spark_job_definition.metadata = {'url': '/sparkJobDefinitions/{sparkJobDefinitionName}'} # type: ignore
[docs] async def get_spark_job_definition(
self,
spark_job_definition_name: str,
if_none_match: Optional[str] = None,
**kwargs
) -> Optional["models.SparkJobDefinitionResource"]:
"""Gets a Spark Job Definition.
:param spark_job_definition_name: The spark job definition name.
:type spark_job_definition_name: str
:param if_none_match: ETag of the Spark Job Definition entity. Should only be specified for
get. If the ETag matches the existing entity tag, or if * was provided, then no content will be
returned.
:type if_none_match: str
:keyword callable cls: A custom type or function that will be passed the direct response
:return: SparkJobDefinitionResource, or the result of cls(response)
:rtype: ~azure.synapse.artifacts.models.SparkJobDefinitionResource or None
:raises: ~azure.core.exceptions.HttpResponseError
"""
cls = kwargs.pop('cls', None) # type: ClsType[Optional["models.SparkJobDefinitionResource"]]
error_map = {404: ResourceNotFoundError, 409: ResourceExistsError}
error_map.update(kwargs.pop('error_map', {}))
api_version = "2019-06-01-preview"
# Construct URL
url = self.get_spark_job_definition.metadata['url'] # type: ignore
path_format_arguments = {
'endpoint': self._serialize.url("self._config.endpoint", self._config.endpoint, 'str', skip_quote=True),
'sparkJobDefinitionName': self._serialize.url("spark_job_definition_name", spark_job_definition_name, 'str'),
}
url = self._client.format_url(url, **path_format_arguments)
# Construct parameters
query_parameters = {} # type: Dict[str, Any]
query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str')
# Construct headers
header_parameters = {} # type: Dict[str, Any]
if if_none_match is not None:
header_parameters['If-None-Match'] = self._serialize.header("if_none_match", if_none_match, 'str')
header_parameters['Accept'] = 'application/json'
request = self._client.get(url, query_parameters, header_parameters)
pipeline_response = await self._client._pipeline.run(request, stream=False, **kwargs)
response = pipeline_response.http_response
if response.status_code not in [200, 304]:
map_error(status_code=response.status_code, response=response, error_map=error_map)
error = self._deserialize(models.CloudError, response)
raise HttpResponseError(response=response, model=error)
deserialized = None
if response.status_code == 200:
deserialized = self._deserialize('SparkJobDefinitionResource', pipeline_response)
if cls:
return cls(pipeline_response, deserialized, {})
return deserialized
get_spark_job_definition.metadata = {'url': '/sparkJobDefinitions/{sparkJobDefinitionName}'} # type: ignore
[docs] async def delete_spark_job_definition(
self,
spark_job_definition_name: str,
**kwargs
) -> None:
"""Deletes a Spark Job Definition.
:param spark_job_definition_name: The spark job definition name.
:type spark_job_definition_name: str
:keyword callable cls: A custom type or function that will be passed the direct response
:return: None, or the result of cls(response)
:rtype: None
:raises: ~azure.core.exceptions.HttpResponseError
"""
cls = kwargs.pop('cls', None) # type: ClsType[None]
error_map = {404: ResourceNotFoundError, 409: ResourceExistsError}
error_map.update(kwargs.pop('error_map', {}))
api_version = "2019-06-01-preview"
# Construct URL
url = self.delete_spark_job_definition.metadata['url'] # type: ignore
path_format_arguments = {
'endpoint': self._serialize.url("self._config.endpoint", self._config.endpoint, 'str', skip_quote=True),
'sparkJobDefinitionName': self._serialize.url("spark_job_definition_name", spark_job_definition_name, 'str'),
}
url = self._client.format_url(url, **path_format_arguments)
# Construct parameters
query_parameters = {} # type: Dict[str, Any]
query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str')
# Construct headers
header_parameters = {} # type: Dict[str, Any]
request = self._client.delete(url, query_parameters, header_parameters)
pipeline_response = await self._client._pipeline.run(request, stream=False, **kwargs)
response = pipeline_response.http_response
if response.status_code not in [200, 204]:
map_error(status_code=response.status_code, response=response, error_map=error_map)
error = self._deserialize(models.CloudError, response)
raise HttpResponseError(response=response, model=error)
if cls:
return cls(pipeline_response, None, {})
delete_spark_job_definition.metadata = {'url': '/sparkJobDefinitions/{sparkJobDefinitionName}'} # type: ignore
async def _execute_spark_job_definition_initial(
self,
spark_job_definition_name: str,
**kwargs
) -> "models.SparkBatchJob":
cls = kwargs.pop('cls', None) # type: ClsType["models.SparkBatchJob"]
error_map = {404: ResourceNotFoundError, 409: ResourceExistsError}
error_map.update(kwargs.pop('error_map', {}))
api_version = "2019-06-01-preview"
# Construct URL
url = self._execute_spark_job_definition_initial.metadata['url'] # type: ignore
path_format_arguments = {
'endpoint': self._serialize.url("self._config.endpoint", self._config.endpoint, 'str', skip_quote=True),
'sparkJobDefinitionName': self._serialize.url("spark_job_definition_name", spark_job_definition_name, 'str'),
}
url = self._client.format_url(url, **path_format_arguments)
# Construct parameters
query_parameters = {} # type: Dict[str, Any]
query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str')
# Construct headers
header_parameters = {} # type: Dict[str, Any]
header_parameters['Accept'] = 'application/json'
request = self._client.post(url, query_parameters, header_parameters)
pipeline_response = await self._client._pipeline.run(request, stream=False, **kwargs)
response = pipeline_response.http_response
if response.status_code not in [200, 202]:
map_error(status_code=response.status_code, response=response, error_map=error_map)
error = self._deserialize(models.CloudError, response)
raise HttpResponseError(response=response, model=error)
if response.status_code == 200:
deserialized = self._deserialize('SparkBatchJob', pipeline_response)
if response.status_code == 202:
deserialized = self._deserialize('SparkBatchJob', pipeline_response)
if cls:
return cls(pipeline_response, deserialized, {})
return deserialized
_execute_spark_job_definition_initial.metadata = {'url': '/sparkJobDefinitions/{sparkJobDefinitionName}/execute'} # type: ignore
[docs] async def begin_execute_spark_job_definition(
self,
spark_job_definition_name: str,
**kwargs
) -> AsyncLROPoller["models.SparkBatchJob"]:
"""Executes the spark job definition.
:param spark_job_definition_name: The spark job definition name.
:type spark_job_definition_name: str
:keyword callable cls: A custom type or function that will be passed the direct response
:keyword str continuation_token: A continuation token to restart a poller from a saved state.
:keyword polling: True for ARMPolling, False for no polling, or a
polling object for personal polling strategy
:paramtype polling: bool or ~azure.core.polling.AsyncPollingMethod
:keyword int polling_interval: Default waiting time between two polls for LRO operations if no Retry-After header is present.
:return: An instance of AsyncLROPoller that returns either SparkBatchJob or the result of cls(response)
:rtype: ~azure.core.polling.AsyncLROPoller[~azure.synapse.artifacts.models.SparkBatchJob]
:raises ~azure.core.exceptions.HttpResponseError:
"""
polling = kwargs.pop('polling', False) # type: Union[bool, AsyncPollingMethod]
cls = kwargs.pop('cls', None) # type: ClsType["models.SparkBatchJob"]
lro_delay = kwargs.pop(
'polling_interval',
self._config.polling_interval
)
cont_token = kwargs.pop('continuation_token', None) # type: Optional[str]
if cont_token is None:
raw_result = await self._execute_spark_job_definition_initial(
spark_job_definition_name=spark_job_definition_name,
cls=lambda x,y,z: x,
**kwargs
)
kwargs.pop('error_map', None)
kwargs.pop('content_type', None)
def get_long_running_output(pipeline_response):
deserialized = self._deserialize('SparkBatchJob', pipeline_response)
if cls:
return cls(pipeline_response, deserialized, {})
return deserialized
if polling is True: polling_method = AsyncLROBasePolling(lro_delay, lro_options={'final-state-via': 'location'}, **kwargs)
elif polling is False: polling_method = AsyncNoPolling()
else: polling_method = polling
if cont_token:
return AsyncLROPoller.from_continuation_token(
polling_method=polling_method,
continuation_token=cont_token,
client=self._client,
deserialization_callback=get_long_running_output
)
else:
return AsyncLROPoller(self._client, raw_result, get_long_running_output, polling_method)
begin_execute_spark_job_definition.metadata = {'url': '/sparkJobDefinitions/{sparkJobDefinitionName}/execute'} # type: ignore
async def _debug_spark_job_definition_initial(
self,
properties: "models.SparkJobDefinition",
**kwargs
) -> "models.SparkBatchJob":
cls = kwargs.pop('cls', None) # type: ClsType["models.SparkBatchJob"]
error_map = {404: ResourceNotFoundError, 409: ResourceExistsError}
error_map.update(kwargs.pop('error_map', {}))
_spark_job_definition_azure_resource = models.SparkJobDefinitionResource(properties=properties)
api_version = "2019-06-01-preview"
content_type = kwargs.pop("content_type", "application/json")
# Construct URL
url = self._debug_spark_job_definition_initial.metadata['url'] # type: ignore
path_format_arguments = {
'endpoint': self._serialize.url("self._config.endpoint", self._config.endpoint, 'str', skip_quote=True),
}
url = self._client.format_url(url, **path_format_arguments)
# Construct parameters
query_parameters = {} # type: Dict[str, Any]
query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str')
# Construct headers
header_parameters = {} # type: Dict[str, Any]
header_parameters['Content-Type'] = self._serialize.header("content_type", content_type, 'str')
header_parameters['Accept'] = 'application/json'
body_content_kwargs = {} # type: Dict[str, Any]
body_content = self._serialize.body(_spark_job_definition_azure_resource, 'SparkJobDefinitionResource')
body_content_kwargs['content'] = body_content
request = self._client.post(url, query_parameters, header_parameters, **body_content_kwargs)
pipeline_response = await self._client._pipeline.run(request, stream=False, **kwargs)
response = pipeline_response.http_response
if response.status_code not in [200, 202]:
map_error(status_code=response.status_code, response=response, error_map=error_map)
error = self._deserialize(models.CloudError, response)
raise HttpResponseError(response=response, model=error)
if response.status_code == 200:
deserialized = self._deserialize('SparkBatchJob', pipeline_response)
if response.status_code == 202:
deserialized = self._deserialize('SparkBatchJob', pipeline_response)
if cls:
return cls(pipeline_response, deserialized, {})
return deserialized
_debug_spark_job_definition_initial.metadata = {'url': '/debugSparkJobDefinition'} # type: ignore
[docs] async def begin_debug_spark_job_definition(
self,
properties: "models.SparkJobDefinition",
**kwargs
) -> AsyncLROPoller["models.SparkBatchJob"]:
"""Debug the spark job definition.
:param properties: Properties of spark job definition.
:type properties: ~azure.synapse.artifacts.models.SparkJobDefinition
:keyword callable cls: A custom type or function that will be passed the direct response
:keyword str continuation_token: A continuation token to restart a poller from a saved state.
:keyword polling: True for ARMPolling, False for no polling, or a
polling object for personal polling strategy
:paramtype polling: bool or ~azure.core.polling.AsyncPollingMethod
:keyword int polling_interval: Default waiting time between two polls for LRO operations if no Retry-After header is present.
:return: An instance of AsyncLROPoller that returns either SparkBatchJob or the result of cls(response)
:rtype: ~azure.core.polling.AsyncLROPoller[~azure.synapse.artifacts.models.SparkBatchJob]
:raises ~azure.core.exceptions.HttpResponseError:
"""
polling = kwargs.pop('polling', False) # type: Union[bool, AsyncPollingMethod]
cls = kwargs.pop('cls', None) # type: ClsType["models.SparkBatchJob"]
lro_delay = kwargs.pop(
'polling_interval',
self._config.polling_interval
)
cont_token = kwargs.pop('continuation_token', None) # type: Optional[str]
if cont_token is None:
raw_result = await self._debug_spark_job_definition_initial(
properties=properties,
cls=lambda x,y,z: x,
**kwargs
)
kwargs.pop('error_map', None)
kwargs.pop('content_type', None)
def get_long_running_output(pipeline_response):
deserialized = self._deserialize('SparkBatchJob', pipeline_response)
if cls:
return cls(pipeline_response, deserialized, {})
return deserialized
if polling is True: polling_method = AsyncLROBasePolling(lro_delay, lro_options={'final-state-via': 'location'}, **kwargs)
elif polling is False: polling_method = AsyncNoPolling()
else: polling_method = polling
if cont_token:
return AsyncLROPoller.from_continuation_token(
polling_method=polling_method,
continuation_token=cont_token,
client=self._client,
deserialization_callback=get_long_running_output
)
else:
return AsyncLROPoller(self._client, raw_result, get_long_running_output, polling_method)
begin_debug_spark_job_definition.metadata = {'url': '/debugSparkJobDefinition'} # type: ignore