# 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.
# --------------------------------------------------------------------------
import functools
from typing import TYPE_CHECKING
import warnings
from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
from azure.core.paging import ItemPaged
from azure.core.pipeline import PipelineResponse
from azure.core.pipeline.transport import HttpResponse
from azure.core.polling import LROPoller, NoPolling, PollingMethod
from azure.core.polling.base_polling import LROBasePolling
from azure.core.rest import HttpRequest
from azure.core.tracing.decorator import distributed_trace
from msrest import Serializer
from .. import models as _models
from .._vendor import _convert_request, _format_url_section
if TYPE_CHECKING:
# pylint: disable=unused-import,ungrouped-imports
from typing import Any, Callable, Dict, Generic, Iterable, Optional, TypeVar, Union
T = TypeVar('T')
ClsType = Optional[Callable[[PipelineResponse[HttpRequest, HttpResponse], T, Dict[str, Any]], Any]]
_SERIALIZER = Serializer()
_SERIALIZER.client_side_validation = False
# fmt: off
def build_get_spark_job_definitions_by_workspace_request(
**kwargs # type: Any
):
# type: (...) -> HttpRequest
api_version = kwargs.pop('api_version', "2020-12-01") # type: str
accept = "application/json"
# Construct URL
url = kwargs.pop("template_url", '/sparkJobDefinitions')
# Construct parameters
query_parameters = kwargs.pop("params", {}) # type: Dict[str, Any]
query_parameters['api-version'] = _SERIALIZER.query("api_version", api_version, 'str')
# Construct headers
header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
return HttpRequest(
method="GET",
url=url,
params=query_parameters,
headers=header_parameters,
**kwargs
)
def build_create_or_update_spark_job_definition_request_initial(
spark_job_definition_name, # type: str
**kwargs # type: Any
):
# type: (...) -> HttpRequest
api_version = kwargs.pop('api_version', "2020-12-01") # type: str
content_type = kwargs.pop('content_type', None) # type: Optional[str]
if_match = kwargs.pop('if_match', None) # type: Optional[str]
accept = "application/json"
# Construct URL
url = kwargs.pop("template_url", '/sparkJobDefinitions/{sparkJobDefinitionName}')
path_format_arguments = {
"sparkJobDefinitionName": _SERIALIZER.url("spark_job_definition_name", spark_job_definition_name, 'str'),
}
url = _format_url_section(url, **path_format_arguments)
# Construct parameters
query_parameters = kwargs.pop("params", {}) # type: Dict[str, Any]
query_parameters['api-version'] = _SERIALIZER.query("api_version", api_version, 'str')
# Construct headers
header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
if if_match is not None:
header_parameters['If-Match'] = _SERIALIZER.header("if_match", if_match, 'str')
if content_type is not None:
header_parameters['Content-Type'] = _SERIALIZER.header("content_type", content_type, 'str')
header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
return HttpRequest(
method="PUT",
url=url,
params=query_parameters,
headers=header_parameters,
**kwargs
)
def build_get_spark_job_definition_request(
spark_job_definition_name, # type: str
**kwargs # type: Any
):
# type: (...) -> HttpRequest
api_version = kwargs.pop('api_version', "2020-12-01") # type: str
if_none_match = kwargs.pop('if_none_match', None) # type: Optional[str]
accept = "application/json"
# Construct URL
url = kwargs.pop("template_url", '/sparkJobDefinitions/{sparkJobDefinitionName}')
path_format_arguments = {
"sparkJobDefinitionName": _SERIALIZER.url("spark_job_definition_name", spark_job_definition_name, 'str'),
}
url = _format_url_section(url, **path_format_arguments)
# Construct parameters
query_parameters = kwargs.pop("params", {}) # type: Dict[str, Any]
query_parameters['api-version'] = _SERIALIZER.query("api_version", api_version, 'str')
# Construct headers
header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
if if_none_match is not None:
header_parameters['If-None-Match'] = _SERIALIZER.header("if_none_match", if_none_match, 'str')
header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
return HttpRequest(
method="GET",
url=url,
params=query_parameters,
headers=header_parameters,
**kwargs
)
def build_delete_spark_job_definition_request_initial(
spark_job_definition_name, # type: str
**kwargs # type: Any
):
# type: (...) -> HttpRequest
api_version = kwargs.pop('api_version', "2020-12-01") # type: str
accept = "application/json"
# Construct URL
url = kwargs.pop("template_url", '/sparkJobDefinitions/{sparkJobDefinitionName}')
path_format_arguments = {
"sparkJobDefinitionName": _SERIALIZER.url("spark_job_definition_name", spark_job_definition_name, 'str'),
}
url = _format_url_section(url, **path_format_arguments)
# Construct parameters
query_parameters = kwargs.pop("params", {}) # type: Dict[str, Any]
query_parameters['api-version'] = _SERIALIZER.query("api_version", api_version, 'str')
# Construct headers
header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
return HttpRequest(
method="DELETE",
url=url,
params=query_parameters,
headers=header_parameters,
**kwargs
)
def build_execute_spark_job_definition_request_initial(
spark_job_definition_name, # type: str
**kwargs # type: Any
):
# type: (...) -> HttpRequest
api_version = kwargs.pop('api_version', "2020-12-01") # type: str
accept = "application/json"
# Construct URL
url = kwargs.pop("template_url", '/sparkJobDefinitions/{sparkJobDefinitionName}/execute')
path_format_arguments = {
"sparkJobDefinitionName": _SERIALIZER.url("spark_job_definition_name", spark_job_definition_name, 'str'),
}
url = _format_url_section(url, **path_format_arguments)
# Construct parameters
query_parameters = kwargs.pop("params", {}) # type: Dict[str, Any]
query_parameters['api-version'] = _SERIALIZER.query("api_version", api_version, 'str')
# Construct headers
header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
return HttpRequest(
method="POST",
url=url,
params=query_parameters,
headers=header_parameters,
**kwargs
)
def build_rename_spark_job_definition_request_initial(
spark_job_definition_name, # type: str
**kwargs # type: Any
):
# type: (...) -> HttpRequest
api_version = kwargs.pop('api_version', "2020-12-01") # type: str
content_type = kwargs.pop('content_type', None) # type: Optional[str]
accept = "application/json"
# Construct URL
url = kwargs.pop("template_url", '/sparkJobDefinitions/{sparkJobDefinitionName}/rename')
path_format_arguments = {
"sparkJobDefinitionName": _SERIALIZER.url("spark_job_definition_name", spark_job_definition_name, 'str'),
}
url = _format_url_section(url, **path_format_arguments)
# Construct parameters
query_parameters = kwargs.pop("params", {}) # type: Dict[str, Any]
query_parameters['api-version'] = _SERIALIZER.query("api_version", api_version, 'str')
# Construct headers
header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
if content_type is not None:
header_parameters['Content-Type'] = _SERIALIZER.header("content_type", content_type, 'str')
header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
return HttpRequest(
method="POST",
url=url,
params=query_parameters,
headers=header_parameters,
**kwargs
)
def build_debug_spark_job_definition_request_initial(
**kwargs # type: Any
):
# type: (...) -> HttpRequest
api_version = kwargs.pop('api_version', "2020-12-01") # type: str
content_type = kwargs.pop('content_type', None) # type: Optional[str]
accept = "application/json"
# Construct URL
url = kwargs.pop("template_url", '/debugSparkJobDefinition')
# Construct parameters
query_parameters = kwargs.pop("params", {}) # type: Dict[str, Any]
query_parameters['api-version'] = _SERIALIZER.query("api_version", api_version, 'str')
# Construct headers
header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any]
if content_type is not None:
header_parameters['Content-Type'] = _SERIALIZER.header("content_type", content_type, 'str')
header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str')
return HttpRequest(
method="POST",
url=url,
params=query_parameters,
headers=header_parameters,
**kwargs
)
# fmt: on
[docs]class SparkJobDefinitionOperations(object):
"""SparkJobDefinitionOperations 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):
self._client = client
self._serialize = serializer
self._deserialize = deserializer
self._config = config
[docs] @distributed_trace
def get_spark_job_definitions_by_workspace(
self,
**kwargs # type: Any
):
# type: (...) -> Iterable["_models.SparkJobDefinitionsListResponse"]
"""Lists spark job definitions.
:keyword api_version: Api Version. The default value is "2020-12-01". Note that overriding this
default value may result in unsupported behavior.
:paramtype api_version: str
: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.paging.ItemPaged[~azure.synapse.artifacts.models.SparkJobDefinitionsListResponse]
:raises: ~azure.core.exceptions.HttpResponseError
"""
api_version = kwargs.pop('api_version', "2020-12-01") # type: str
cls = kwargs.pop('cls', None) # type: ClsType["_models.SparkJobDefinitionsListResponse"]
error_map = {
401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
}
error_map.update(kwargs.pop('error_map', {}))
def prepare_request(next_link=None):
if not next_link:
request = build_get_spark_job_definitions_by_workspace_request(
api_version=api_version,
template_url=self.get_spark_job_definitions_by_workspace.metadata['url'],
)
request = _convert_request(request)
path_format_arguments = {
"endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, 'str', skip_quote=True),
}
request.url = self._client.format_url(request.url, **path_format_arguments)
else:
request = build_get_spark_job_definitions_by_workspace_request(
api_version=api_version,
template_url=next_link,
)
request = _convert_request(request)
path_format_arguments = {
"endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, 'str', skip_quote=True),
}
request.url = self._client.format_url(request.url, **path_format_arguments)
path_format_arguments = {
"endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, 'str', skip_quote=True),
}
request.method = "GET"
return request
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, iter(list_of_elem)
def get_next(next_link=None):
request = prepare_request(next_link)
pipeline_response = 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.failsafe_deserialize(_models.CloudErrorAutoGenerated, pipeline_response)
raise HttpResponseError(response=response, model=error)
return pipeline_response
return ItemPaged(
get_next, extract_data
)
get_spark_job_definitions_by_workspace.metadata = {'url': '/sparkJobDefinitions'} # type: ignore
def _create_or_update_spark_job_definition_initial(
self,
spark_job_definition_name, # type: str
properties, # type: "_models.SparkJobDefinition"
if_match=None, # type: Optional[str]
**kwargs # type: Any
):
# type: (...) -> Optional["_models.SparkJobDefinitionResource"]
cls = kwargs.pop('cls', None) # type: ClsType[Optional["_models.SparkJobDefinitionResource"]]
error_map = {
401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
}
error_map.update(kwargs.pop('error_map', {}))
api_version = kwargs.pop('api_version', "2020-12-01") # type: str
content_type = kwargs.pop('content_type', "application/json") # type: Optional[str]
_spark_job_definition = _models.SparkJobDefinitionResource(properties=properties)
_json = self._serialize.body(_spark_job_definition, 'SparkJobDefinitionResource')
request = build_create_or_update_spark_job_definition_request_initial(
spark_job_definition_name=spark_job_definition_name,
api_version=api_version,
content_type=content_type,
json=_json,
if_match=if_match,
template_url=self._create_or_update_spark_job_definition_initial.metadata['url'],
)
request = _convert_request(request)
path_format_arguments = {
"endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, 'str', skip_quote=True),
}
request.url = self._client.format_url(request.url, **path_format_arguments)
pipeline_response = 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)
raise HttpResponseError(response=response)
deserialized = None
if response.status_code == 200:
deserialized = self._deserialize('SparkJobDefinitionResource', pipeline_response)
if cls:
return cls(pipeline_response, deserialized, {})
return deserialized
_create_or_update_spark_job_definition_initial.metadata = {'url': '/sparkJobDefinitions/{sparkJobDefinitionName}'} # type: ignore
[docs] @distributed_trace
def begin_create_or_update_spark_job_definition(
self,
spark_job_definition_name, # type: str
properties, # type: "_models.SparkJobDefinition"
if_match=None, # type: Optional[str]
**kwargs # type: Any
):
# type: (...) -> LROPoller["_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 api_version: Api Version. The default value is "2020-12-01". Note that overriding this
default value may result in unsupported behavior.
:paramtype api_version: 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: By default, your polling method will be LROBasePolling. Pass in False for
this operation to not poll, or pass in your own initialized polling object for a personal
polling strategy.
:paramtype polling: bool or ~azure.core.polling.PollingMethod
:keyword int polling_interval: Default waiting time between two polls for LRO operations if no
Retry-After header is present.
:return: An instance of LROPoller that returns either SparkJobDefinitionResource or the result
of cls(response)
:rtype:
~azure.core.polling.LROPoller[~azure.synapse.artifacts.models.SparkJobDefinitionResource]
:raises: ~azure.core.exceptions.HttpResponseError
"""
api_version = kwargs.pop('api_version', "2020-12-01") # type: str
content_type = kwargs.pop('content_type', "application/json") # type: Optional[str]
polling = kwargs.pop('polling', True) # type: Union[bool, azure.core.polling.PollingMethod]
cls = kwargs.pop('cls', None) # type: ClsType["_models.SparkJobDefinitionResource"]
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 = self._create_or_update_spark_job_definition_initial(
spark_job_definition_name=spark_job_definition_name,
properties=properties,
if_match=if_match,
api_version=api_version,
content_type=content_type,
cls=lambda x,y,z: x,
**kwargs
)
kwargs.pop('error_map', None)
def get_long_running_output(pipeline_response):
response = pipeline_response.http_response
deserialized = self._deserialize('SparkJobDefinitionResource', pipeline_response)
if cls:
return cls(pipeline_response, deserialized, {})
return deserialized
path_format_arguments = {
"endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, 'str', skip_quote=True),
}
if polling is True: polling_method = LROBasePolling(lro_delay, path_format_arguments=path_format_arguments, **kwargs)
elif polling is False: polling_method = NoPolling()
else: polling_method = polling
if cont_token:
return LROPoller.from_continuation_token(
polling_method=polling_method,
continuation_token=cont_token,
client=self._client,
deserialization_callback=get_long_running_output
)
else:
return LROPoller(self._client, raw_result, get_long_running_output, polling_method)
begin_create_or_update_spark_job_definition.metadata = {'url': '/sparkJobDefinitions/{sparkJobDefinitionName}'} # type: ignore
[docs] @distributed_trace
def get_spark_job_definition(
self,
spark_job_definition_name, # type: str
if_none_match=None, # type: Optional[str]
**kwargs # type: Any
):
# type: (...) -> 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 api_version: Api Version. The default value is "2020-12-01". Note that overriding this
default value may result in unsupported behavior.
:paramtype api_version: 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 = {
401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
}
error_map.update(kwargs.pop('error_map', {}))
api_version = kwargs.pop('api_version', "2020-12-01") # type: str
request = build_get_spark_job_definition_request(
spark_job_definition_name=spark_job_definition_name,
api_version=api_version,
if_none_match=if_none_match,
template_url=self.get_spark_job_definition.metadata['url'],
)
request = _convert_request(request)
path_format_arguments = {
"endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, 'str', skip_quote=True),
}
request.url = self._client.format_url(request.url, **path_format_arguments)
pipeline_response = 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.failsafe_deserialize(_models.CloudErrorAutoGenerated, pipeline_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
def _delete_spark_job_definition_initial(
self,
spark_job_definition_name, # type: str
**kwargs # type: Any
):
# type: (...) -> None
cls = kwargs.pop('cls', None) # type: ClsType[None]
error_map = {
401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
}
error_map.update(kwargs.pop('error_map', {}))
api_version = kwargs.pop('api_version', "2020-12-01") # type: str
request = build_delete_spark_job_definition_request_initial(
spark_job_definition_name=spark_job_definition_name,
api_version=api_version,
template_url=self._delete_spark_job_definition_initial.metadata['url'],
)
request = _convert_request(request)
path_format_arguments = {
"endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, 'str', skip_quote=True),
}
request.url = self._client.format_url(request.url, **path_format_arguments)
pipeline_response = self._client._pipeline.run(request, stream=False, **kwargs)
response = pipeline_response.http_response
if response.status_code not in [200, 202, 204]:
map_error(status_code=response.status_code, response=response, error_map=error_map)
raise HttpResponseError(response=response)
if cls:
return cls(pipeline_response, None, {})
_delete_spark_job_definition_initial.metadata = {'url': '/sparkJobDefinitions/{sparkJobDefinitionName}'} # type: ignore
[docs] @distributed_trace
def begin_delete_spark_job_definition(
self,
spark_job_definition_name, # type: str
**kwargs # type: Any
):
# type: (...) -> LROPoller[None]
"""Deletes a Spark Job Definition.
:param spark_job_definition_name: The spark job definition name.
:type spark_job_definition_name: str
:keyword api_version: Api Version. The default value is "2020-12-01". Note that overriding this
default value may result in unsupported behavior.
:paramtype api_version: 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: By default, your polling method will be LROBasePolling. Pass in False for
this operation to not poll, or pass in your own initialized polling object for a personal
polling strategy.
:paramtype polling: bool or ~azure.core.polling.PollingMethod
:keyword int polling_interval: Default waiting time between two polls for LRO operations if no
Retry-After header is present.
:return: An instance of LROPoller that returns either None or the result of cls(response)
:rtype: ~azure.core.polling.LROPoller[None]
:raises: ~azure.core.exceptions.HttpResponseError
"""
api_version = kwargs.pop('api_version', "2020-12-01") # type: str
polling = kwargs.pop('polling', True) # type: Union[bool, azure.core.polling.PollingMethod]
cls = kwargs.pop('cls', None) # type: ClsType[None]
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 = self._delete_spark_job_definition_initial(
spark_job_definition_name=spark_job_definition_name,
api_version=api_version,
cls=lambda x,y,z: x,
**kwargs
)
kwargs.pop('error_map', None)
def get_long_running_output(pipeline_response):
if cls:
return cls(pipeline_response, None, {})
path_format_arguments = {
"endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, 'str', skip_quote=True),
}
if polling is True: polling_method = LROBasePolling(lro_delay, path_format_arguments=path_format_arguments, **kwargs)
elif polling is False: polling_method = NoPolling()
else: polling_method = polling
if cont_token:
return LROPoller.from_continuation_token(
polling_method=polling_method,
continuation_token=cont_token,
client=self._client,
deserialization_callback=get_long_running_output
)
else:
return LROPoller(self._client, raw_result, get_long_running_output, polling_method)
begin_delete_spark_job_definition.metadata = {'url': '/sparkJobDefinitions/{sparkJobDefinitionName}'} # type: ignore
def _execute_spark_job_definition_initial(
self,
spark_job_definition_name, # type: str
**kwargs # type: Any
):
# type: (...) -> "_models.SparkBatchJob"
cls = kwargs.pop('cls', None) # type: ClsType["_models.SparkBatchJob"]
error_map = {
401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
}
error_map.update(kwargs.pop('error_map', {}))
api_version = kwargs.pop('api_version', "2020-12-01") # type: str
request = build_execute_spark_job_definition_request_initial(
spark_job_definition_name=spark_job_definition_name,
api_version=api_version,
template_url=self._execute_spark_job_definition_initial.metadata['url'],
)
request = _convert_request(request)
path_format_arguments = {
"endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, 'str', skip_quote=True),
}
request.url = self._client.format_url(request.url, **path_format_arguments)
pipeline_response = 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)
raise HttpResponseError(response=response)
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] @distributed_trace
def begin_execute_spark_job_definition(
self,
spark_job_definition_name, # type: str
**kwargs # type: Any
):
# type: (...) -> LROPoller["_models.SparkBatchJob"]
"""Executes the spark job definition.
:param spark_job_definition_name: The spark job definition name.
:type spark_job_definition_name: str
:keyword api_version: Api Version. The default value is "2020-12-01". Note that overriding this
default value may result in unsupported behavior.
:paramtype api_version: 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: By default, your polling method will be LROBasePolling. Pass in False for
this operation to not poll, or pass in your own initialized polling object for a personal
polling strategy.
:paramtype polling: bool or ~azure.core.polling.PollingMethod
:keyword int polling_interval: Default waiting time between two polls for LRO operations if no
Retry-After header is present.
:return: An instance of LROPoller that returns either SparkBatchJob or the result of
cls(response)
:rtype: ~azure.core.polling.LROPoller[~azure.synapse.artifacts.models.SparkBatchJob]
:raises: ~azure.core.exceptions.HttpResponseError
"""
api_version = kwargs.pop('api_version', "2020-12-01") # type: str
polling = kwargs.pop('polling', True) # type: Union[bool, azure.core.polling.PollingMethod]
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 = self._execute_spark_job_definition_initial(
spark_job_definition_name=spark_job_definition_name,
api_version=api_version,
cls=lambda x,y,z: x,
**kwargs
)
kwargs.pop('error_map', None)
def get_long_running_output(pipeline_response):
response = pipeline_response.http_response
deserialized = self._deserialize('SparkBatchJob', pipeline_response)
if cls:
return cls(pipeline_response, deserialized, {})
return deserialized
path_format_arguments = {
"endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, 'str', skip_quote=True),
}
if polling is True: polling_method = LROBasePolling(lro_delay, lro_options={'final-state-via': 'location'}, path_format_arguments=path_format_arguments, **kwargs)
elif polling is False: polling_method = NoPolling()
else: polling_method = polling
if cont_token:
return LROPoller.from_continuation_token(
polling_method=polling_method,
continuation_token=cont_token,
client=self._client,
deserialization_callback=get_long_running_output
)
else:
return LROPoller(self._client, raw_result, get_long_running_output, polling_method)
begin_execute_spark_job_definition.metadata = {'url': '/sparkJobDefinitions/{sparkJobDefinitionName}/execute'} # type: ignore
def _rename_spark_job_definition_initial(
self,
spark_job_definition_name, # type: str
new_name=None, # type: Optional[str]
**kwargs # type: Any
):
# type: (...) -> None
cls = kwargs.pop('cls', None) # type: ClsType[None]
error_map = {
401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
}
error_map.update(kwargs.pop('error_map', {}))
api_version = kwargs.pop('api_version', "2020-12-01") # type: str
content_type = kwargs.pop('content_type', "application/json") # type: Optional[str]
_request = _models.ArtifactRenameRequest(new_name=new_name)
_json = self._serialize.body(_request, 'ArtifactRenameRequest')
request = build_rename_spark_job_definition_request_initial(
spark_job_definition_name=spark_job_definition_name,
api_version=api_version,
content_type=content_type,
json=_json,
template_url=self._rename_spark_job_definition_initial.metadata['url'],
)
request = _convert_request(request)
path_format_arguments = {
"endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, 'str', skip_quote=True),
}
request.url = self._client.format_url(request.url, **path_format_arguments)
pipeline_response = 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)
raise HttpResponseError(response=response)
if cls:
return cls(pipeline_response, None, {})
_rename_spark_job_definition_initial.metadata = {'url': '/sparkJobDefinitions/{sparkJobDefinitionName}/rename'} # type: ignore
[docs] @distributed_trace
def begin_rename_spark_job_definition(
self,
spark_job_definition_name, # type: str
new_name=None, # type: Optional[str]
**kwargs # type: Any
):
# type: (...) -> LROPoller[None]
"""Renames a sparkJobDefinition.
:param spark_job_definition_name: The spark job definition name.
:type spark_job_definition_name: str
:param new_name: New name of the artifact.
:type new_name: str
:keyword api_version: Api Version. The default value is "2020-12-01". Note that overriding this
default value may result in unsupported behavior.
:paramtype api_version: 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: By default, your polling method will be LROBasePolling. Pass in False for
this operation to not poll, or pass in your own initialized polling object for a personal
polling strategy.
:paramtype polling: bool or ~azure.core.polling.PollingMethod
:keyword int polling_interval: Default waiting time between two polls for LRO operations if no
Retry-After header is present.
:return: An instance of LROPoller that returns either None or the result of cls(response)
:rtype: ~azure.core.polling.LROPoller[None]
:raises: ~azure.core.exceptions.HttpResponseError
"""
api_version = kwargs.pop('api_version', "2020-12-01") # type: str
content_type = kwargs.pop('content_type', "application/json") # type: Optional[str]
polling = kwargs.pop('polling', True) # type: Union[bool, azure.core.polling.PollingMethod]
cls = kwargs.pop('cls', None) # type: ClsType[None]
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 = self._rename_spark_job_definition_initial(
spark_job_definition_name=spark_job_definition_name,
new_name=new_name,
api_version=api_version,
content_type=content_type,
cls=lambda x,y,z: x,
**kwargs
)
kwargs.pop('error_map', None)
def get_long_running_output(pipeline_response):
if cls:
return cls(pipeline_response, None, {})
path_format_arguments = {
"endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, 'str', skip_quote=True),
}
if polling is True: polling_method = LROBasePolling(lro_delay, path_format_arguments=path_format_arguments, **kwargs)
elif polling is False: polling_method = NoPolling()
else: polling_method = polling
if cont_token:
return LROPoller.from_continuation_token(
polling_method=polling_method,
continuation_token=cont_token,
client=self._client,
deserialization_callback=get_long_running_output
)
else:
return LROPoller(self._client, raw_result, get_long_running_output, polling_method)
begin_rename_spark_job_definition.metadata = {'url': '/sparkJobDefinitions/{sparkJobDefinitionName}/rename'} # type: ignore
def _debug_spark_job_definition_initial(
self,
properties, # type: "_models.SparkJobDefinition"
**kwargs # type: Any
):
# type: (...) -> "_models.SparkBatchJob"
cls = kwargs.pop('cls', None) # type: ClsType["_models.SparkBatchJob"]
error_map = {
401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
}
error_map.update(kwargs.pop('error_map', {}))
api_version = kwargs.pop('api_version', "2020-12-01") # type: str
content_type = kwargs.pop('content_type', "application/json") # type: Optional[str]
_spark_job_definition_azure_resource = _models.SparkJobDefinitionResource(properties=properties)
_json = self._serialize.body(_spark_job_definition_azure_resource, 'SparkJobDefinitionResource')
request = build_debug_spark_job_definition_request_initial(
api_version=api_version,
content_type=content_type,
json=_json,
template_url=self._debug_spark_job_definition_initial.metadata['url'],
)
request = _convert_request(request)
path_format_arguments = {
"endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, 'str', skip_quote=True),
}
request.url = self._client.format_url(request.url, **path_format_arguments)
pipeline_response = 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)
raise HttpResponseError(response=response)
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] @distributed_trace
def begin_debug_spark_job_definition(
self,
properties, # type: "_models.SparkJobDefinition"
**kwargs # type: Any
):
# type: (...) -> LROPoller["_models.SparkBatchJob"]
"""Debug the spark job definition.
:param properties: Properties of spark job definition.
:type properties: ~azure.synapse.artifacts.models.SparkJobDefinition
:keyword api_version: Api Version. The default value is "2020-12-01". Note that overriding this
default value may result in unsupported behavior.
:paramtype api_version: 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: By default, your polling method will be LROBasePolling. Pass in False for
this operation to not poll, or pass in your own initialized polling object for a personal
polling strategy.
:paramtype polling: bool or ~azure.core.polling.PollingMethod
:keyword int polling_interval: Default waiting time between two polls for LRO operations if no
Retry-After header is present.
:return: An instance of LROPoller that returns either SparkBatchJob or the result of
cls(response)
:rtype: ~azure.core.polling.LROPoller[~azure.synapse.artifacts.models.SparkBatchJob]
:raises: ~azure.core.exceptions.HttpResponseError
"""
api_version = kwargs.pop('api_version', "2020-12-01") # type: str
content_type = kwargs.pop('content_type', "application/json") # type: Optional[str]
polling = kwargs.pop('polling', True) # type: Union[bool, azure.core.polling.PollingMethod]
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 = self._debug_spark_job_definition_initial(
properties=properties,
api_version=api_version,
content_type=content_type,
cls=lambda x,y,z: x,
**kwargs
)
kwargs.pop('error_map', None)
def get_long_running_output(pipeline_response):
response = pipeline_response.http_response
deserialized = self._deserialize('SparkBatchJob', pipeline_response)
if cls:
return cls(pipeline_response, deserialized, {})
return deserialized
path_format_arguments = {
"endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, 'str', skip_quote=True),
}
if polling is True: polling_method = LROBasePolling(lro_delay, lro_options={'final-state-via': 'location'}, path_format_arguments=path_format_arguments, **kwargs)
elif polling is False: polling_method = NoPolling()
else: polling_method = polling
if cont_token:
return LROPoller.from_continuation_token(
polling_method=polling_method,
continuation_token=cont_token,
client=self._client,
deserialization_callback=get_long_running_output
)
else:
return LROPoller(self._client, raw_result, get_long_running_output, polling_method)
begin_debug_spark_job_definition.metadata = {'url': '/debugSparkJobDefinition'} # type: ignore