# 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 datetime
from typing import Dict, List, Optional, Union
import msrest.serialization
from ._spark_client_enums import *
[docs]class SparkBatchJob(msrest.serialization.Model):
"""SparkBatchJob.
All required parameters must be populated in order to send to Azure.
:param livy_info:
:type livy_info: ~azure.synapse.spark.models.SparkBatchJobState
:param name: The batch name.
:type name: str
:param workspace_name: The workspace name.
:type workspace_name: str
:param spark_pool_name: The Spark pool name.
:type spark_pool_name: str
:param submitter_name: The submitter name.
:type submitter_name: str
:param submitter_id: The submitter identifier.
:type submitter_id: str
:param artifact_id: The artifact identifier.
:type artifact_id: str
:param job_type: The job type. Possible values include: "SparkBatch", "SparkSession".
:type job_type: str or ~azure.synapse.spark.models.SparkJobType
:param result: The Spark batch job result. Possible values include: "Uncertain", "Succeeded",
"Failed", "Cancelled".
:type result: str or ~azure.synapse.spark.models.SparkBatchJobResultType
:param scheduler: The scheduler information.
:type scheduler: ~azure.synapse.spark.models.SparkScheduler
:param plugin: The plugin information.
:type plugin: ~azure.synapse.spark.models.SparkServicePlugin
:param errors: The error information.
:type errors: list[~azure.synapse.spark.models.SparkServiceError]
:param tags: A set of tags. The tags.
:type tags: dict[str, str]
:param id: Required. The session Id.
:type id: int
:param app_id: The application id of this session.
:type app_id: str
:param app_info: The detailed application info.
:type app_info: dict[str, str]
:param state: The batch state.
:type state: str
:param log_lines: The log lines.
:type log_lines: list[str]
"""
_validation = {
'id': {'required': True},
}
_attribute_map = {
'livy_info': {'key': 'livyInfo', 'type': 'SparkBatchJobState'},
'name': {'key': 'name', 'type': 'str'},
'workspace_name': {'key': 'workspaceName', 'type': 'str'},
'spark_pool_name': {'key': 'sparkPoolName', 'type': 'str'},
'submitter_name': {'key': 'submitterName', 'type': 'str'},
'submitter_id': {'key': 'submitterId', 'type': 'str'},
'artifact_id': {'key': 'artifactId', 'type': 'str'},
'job_type': {'key': 'jobType', 'type': 'str'},
'result': {'key': 'result', 'type': 'str'},
'scheduler': {'key': 'schedulerInfo', 'type': 'SparkScheduler'},
'plugin': {'key': 'pluginInfo', 'type': 'SparkServicePlugin'},
'errors': {'key': 'errorInfo', 'type': '[SparkServiceError]'},
'tags': {'key': 'tags', 'type': '{str}'},
'id': {'key': 'id', 'type': 'int'},
'app_id': {'key': 'appId', 'type': 'str'},
'app_info': {'key': 'appInfo', 'type': '{str}'},
'state': {'key': 'state', 'type': 'str'},
'log_lines': {'key': 'log', 'type': '[str]'},
}
def __init__(
self,
*,
id: int,
livy_info: Optional["SparkBatchJobState"] = None,
name: Optional[str] = None,
workspace_name: Optional[str] = None,
spark_pool_name: Optional[str] = None,
submitter_name: Optional[str] = None,
submitter_id: Optional[str] = None,
artifact_id: Optional[str] = None,
job_type: Optional[Union[str, "SparkJobType"]] = None,
result: Optional[Union[str, "SparkBatchJobResultType"]] = None,
scheduler: Optional["SparkScheduler"] = None,
plugin: Optional["SparkServicePlugin"] = None,
errors: Optional[List["SparkServiceError"]] = None,
tags: Optional[Dict[str, str]] = None,
app_id: Optional[str] = None,
app_info: Optional[Dict[str, str]] = None,
state: Optional[str] = None,
log_lines: Optional[List[str]] = None,
**kwargs
):
super(SparkBatchJob, self).__init__(**kwargs)
self.livy_info = livy_info
self.name = name
self.workspace_name = workspace_name
self.spark_pool_name = spark_pool_name
self.submitter_name = submitter_name
self.submitter_id = submitter_id
self.artifact_id = artifact_id
self.job_type = job_type
self.result = result
self.scheduler = scheduler
self.plugin = plugin
self.errors = errors
self.tags = tags
self.id = id
self.app_id = app_id
self.app_info = app_info
self.state = state
self.log_lines = log_lines
[docs]class SparkBatchJobCollection(msrest.serialization.Model):
"""Response for batch list operation.
All required parameters must be populated in order to send to Azure.
:param from_property: Required. The start index of fetched sessions.
:type from_property: int
:param total: Required. Number of sessions fetched.
:type total: int
:param sessions: Batch list.
:type sessions: list[~azure.synapse.spark.models.SparkBatchJob]
"""
_validation = {
'from_property': {'required': True},
'total': {'required': True},
}
_attribute_map = {
'from_property': {'key': 'from', 'type': 'int'},
'total': {'key': 'total', 'type': 'int'},
'sessions': {'key': 'sessions', 'type': '[SparkBatchJob]'},
}
def __init__(
self,
*,
from_property: int,
total: int,
sessions: Optional[List["SparkBatchJob"]] = None,
**kwargs
):
super(SparkBatchJobCollection, self).__init__(**kwargs)
self.from_property = from_property
self.total = total
self.sessions = sessions
[docs]class SparkBatchJobOptions(msrest.serialization.Model):
"""SparkBatchJobOptions.
All required parameters must be populated in order to send to Azure.
:param tags: A set of tags. Dictionary of :code:`<string>`.
:type tags: dict[str, str]
:param artifact_id:
:type artifact_id: str
:param name: Required.
:type name: str
:param file: Required.
:type file: str
:param class_name:
:type class_name: str
:param arguments:
:type arguments: list[str]
:param jars:
:type jars: list[str]
:param python_files:
:type python_files: list[str]
:param files:
:type files: list[str]
:param archives:
:type archives: list[str]
:param configuration: Dictionary of :code:`<string>`.
:type configuration: dict[str, str]
:param driver_memory:
:type driver_memory: str
:param driver_cores:
:type driver_cores: int
:param executor_memory:
:type executor_memory: str
:param executor_cores:
:type executor_cores: int
:param executor_count:
:type executor_count: int
"""
_validation = {
'name': {'required': True},
'file': {'required': True},
}
_attribute_map = {
'tags': {'key': 'tags', 'type': '{str}'},
'artifact_id': {'key': 'artifactId', 'type': 'str'},
'name': {'key': 'name', 'type': 'str'},
'file': {'key': 'file', 'type': 'str'},
'class_name': {'key': 'className', 'type': 'str'},
'arguments': {'key': 'args', 'type': '[str]'},
'jars': {'key': 'jars', 'type': '[str]'},
'python_files': {'key': 'pyFiles', 'type': '[str]'},
'files': {'key': 'files', 'type': '[str]'},
'archives': {'key': 'archives', 'type': '[str]'},
'configuration': {'key': 'conf', 'type': '{str}'},
'driver_memory': {'key': 'driverMemory', 'type': 'str'},
'driver_cores': {'key': 'driverCores', 'type': 'int'},
'executor_memory': {'key': 'executorMemory', 'type': 'str'},
'executor_cores': {'key': 'executorCores', 'type': 'int'},
'executor_count': {'key': 'numExecutors', 'type': 'int'},
}
def __init__(
self,
*,
name: str,
file: str,
tags: Optional[Dict[str, str]] = None,
artifact_id: Optional[str] = None,
class_name: Optional[str] = None,
arguments: Optional[List[str]] = None,
jars: Optional[List[str]] = None,
python_files: Optional[List[str]] = None,
files: Optional[List[str]] = None,
archives: Optional[List[str]] = None,
configuration: Optional[Dict[str, str]] = None,
driver_memory: Optional[str] = None,
driver_cores: Optional[int] = None,
executor_memory: Optional[str] = None,
executor_cores: Optional[int] = None,
executor_count: Optional[int] = None,
**kwargs
):
super(SparkBatchJobOptions, self).__init__(**kwargs)
self.tags = tags
self.artifact_id = artifact_id
self.name = name
self.file = file
self.class_name = class_name
self.arguments = arguments
self.jars = jars
self.python_files = python_files
self.files = files
self.archives = archives
self.configuration = configuration
self.driver_memory = driver_memory
self.driver_cores = driver_cores
self.executor_memory = executor_memory
self.executor_cores = executor_cores
self.executor_count = executor_count
[docs]class SparkBatchJobState(msrest.serialization.Model):
"""SparkBatchJobState.
:param not_started_at: the time that at which "not_started" livy state was first seen.
:type not_started_at: ~datetime.datetime
:param starting_at: the time that at which "starting" livy state was first seen.
:type starting_at: ~datetime.datetime
:param running_at: the time that at which "running" livy state was first seen.
:type running_at: ~datetime.datetime
:param dead_at: time that at which "dead" livy state was first seen.
:type dead_at: ~datetime.datetime
:param success_at: the time that at which "success" livy state was first seen.
:type success_at: ~datetime.datetime
:param terminated_at: the time that at which "killed" livy state was first seen.
:type terminated_at: ~datetime.datetime
:param recovering_at: the time that at which "recovering" livy state was first seen.
:type recovering_at: ~datetime.datetime
:param current_state: the Spark job state.
:type current_state: str
:param job_creation_request:
:type job_creation_request: ~azure.synapse.spark.models.SparkRequest
"""
_attribute_map = {
'not_started_at': {'key': 'notStartedAt', 'type': 'iso-8601'},
'starting_at': {'key': 'startingAt', 'type': 'iso-8601'},
'running_at': {'key': 'runningAt', 'type': 'iso-8601'},
'dead_at': {'key': 'deadAt', 'type': 'iso-8601'},
'success_at': {'key': 'successAt', 'type': 'iso-8601'},
'terminated_at': {'key': 'killedAt', 'type': 'iso-8601'},
'recovering_at': {'key': 'recoveringAt', 'type': 'iso-8601'},
'current_state': {'key': 'currentState', 'type': 'str'},
'job_creation_request': {'key': 'jobCreationRequest', 'type': 'SparkRequest'},
}
def __init__(
self,
*,
not_started_at: Optional[datetime.datetime] = None,
starting_at: Optional[datetime.datetime] = None,
running_at: Optional[datetime.datetime] = None,
dead_at: Optional[datetime.datetime] = None,
success_at: Optional[datetime.datetime] = None,
terminated_at: Optional[datetime.datetime] = None,
recovering_at: Optional[datetime.datetime] = None,
current_state: Optional[str] = None,
job_creation_request: Optional["SparkRequest"] = None,
**kwargs
):
super(SparkBatchJobState, self).__init__(**kwargs)
self.not_started_at = not_started_at
self.starting_at = starting_at
self.running_at = running_at
self.dead_at = dead_at
self.success_at = success_at
self.terminated_at = terminated_at
self.recovering_at = recovering_at
self.current_state = current_state
self.job_creation_request = job_creation_request
[docs]class SparkRequest(msrest.serialization.Model):
"""SparkRequest.
:param name:
:type name: str
:param file:
:type file: str
:param class_name:
:type class_name: str
:param arguments:
:type arguments: list[str]
:param jars:
:type jars: list[str]
:param python_files:
:type python_files: list[str]
:param files:
:type files: list[str]
:param archives:
:type archives: list[str]
:param configuration: Dictionary of :code:`<string>`.
:type configuration: dict[str, str]
:param driver_memory:
:type driver_memory: str
:param driver_cores:
:type driver_cores: int
:param executor_memory:
:type executor_memory: str
:param executor_cores:
:type executor_cores: int
:param executor_count:
:type executor_count: int
"""
_attribute_map = {
'name': {'key': 'name', 'type': 'str'},
'file': {'key': 'file', 'type': 'str'},
'class_name': {'key': 'className', 'type': 'str'},
'arguments': {'key': 'args', 'type': '[str]'},
'jars': {'key': 'jars', 'type': '[str]'},
'python_files': {'key': 'pyFiles', 'type': '[str]'},
'files': {'key': 'files', 'type': '[str]'},
'archives': {'key': 'archives', 'type': '[str]'},
'configuration': {'key': 'conf', 'type': '{str}'},
'driver_memory': {'key': 'driverMemory', 'type': 'str'},
'driver_cores': {'key': 'driverCores', 'type': 'int'},
'executor_memory': {'key': 'executorMemory', 'type': 'str'},
'executor_cores': {'key': 'executorCores', 'type': 'int'},
'executor_count': {'key': 'numExecutors', 'type': 'int'},
}
def __init__(
self,
*,
name: Optional[str] = None,
file: Optional[str] = None,
class_name: Optional[str] = None,
arguments: Optional[List[str]] = None,
jars: Optional[List[str]] = None,
python_files: Optional[List[str]] = None,
files: Optional[List[str]] = None,
archives: Optional[List[str]] = None,
configuration: Optional[Dict[str, str]] = None,
driver_memory: Optional[str] = None,
driver_cores: Optional[int] = None,
executor_memory: Optional[str] = None,
executor_cores: Optional[int] = None,
executor_count: Optional[int] = None,
**kwargs
):
super(SparkRequest, self).__init__(**kwargs)
self.name = name
self.file = file
self.class_name = class_name
self.arguments = arguments
self.jars = jars
self.python_files = python_files
self.files = files
self.archives = archives
self.configuration = configuration
self.driver_memory = driver_memory
self.driver_cores = driver_cores
self.executor_memory = executor_memory
self.executor_cores = executor_cores
self.executor_count = executor_count
[docs]class SparkScheduler(msrest.serialization.Model):
"""SparkScheduler.
:param submitted_at:
:type submitted_at: ~datetime.datetime
:param scheduled_at:
:type scheduled_at: ~datetime.datetime
:param ended_at:
:type ended_at: ~datetime.datetime
:param cancellation_requested_at:
:type cancellation_requested_at: ~datetime.datetime
:param current_state: Possible values include: "Queued", "Scheduled", "Ended".
:type current_state: str or ~azure.synapse.spark.models.SchedulerCurrentState
"""
_attribute_map = {
'submitted_at': {'key': 'submittedAt', 'type': 'iso-8601'},
'scheduled_at': {'key': 'scheduledAt', 'type': 'iso-8601'},
'ended_at': {'key': 'endedAt', 'type': 'iso-8601'},
'cancellation_requested_at': {'key': 'cancellationRequestedAt', 'type': 'iso-8601'},
'current_state': {'key': 'currentState', 'type': 'str'},
}
def __init__(
self,
*,
submitted_at: Optional[datetime.datetime] = None,
scheduled_at: Optional[datetime.datetime] = None,
ended_at: Optional[datetime.datetime] = None,
cancellation_requested_at: Optional[datetime.datetime] = None,
current_state: Optional[Union[str, "SchedulerCurrentState"]] = None,
**kwargs
):
super(SparkScheduler, self).__init__(**kwargs)
self.submitted_at = submitted_at
self.scheduled_at = scheduled_at
self.ended_at = ended_at
self.cancellation_requested_at = cancellation_requested_at
self.current_state = current_state
[docs]class SparkServiceError(msrest.serialization.Model):
"""SparkServiceError.
:param message:
:type message: str
:param error_code:
:type error_code: str
:param source: Possible values include: "System", "User", "Unknown", "Dependency".
:type source: str or ~azure.synapse.spark.models.SparkErrorSource
"""
_attribute_map = {
'message': {'key': 'message', 'type': 'str'},
'error_code': {'key': 'errorCode', 'type': 'str'},
'source': {'key': 'source', 'type': 'str'},
}
def __init__(
self,
*,
message: Optional[str] = None,
error_code: Optional[str] = None,
source: Optional[Union[str, "SparkErrorSource"]] = None,
**kwargs
):
super(SparkServiceError, self).__init__(**kwargs)
self.message = message
self.error_code = error_code
self.source = source
[docs]class SparkServicePlugin(msrest.serialization.Model):
"""SparkServicePlugin.
:param preparation_started_at:
:type preparation_started_at: ~datetime.datetime
:param resource_acquisition_started_at:
:type resource_acquisition_started_at: ~datetime.datetime
:param submission_started_at:
:type submission_started_at: ~datetime.datetime
:param monitoring_started_at:
:type monitoring_started_at: ~datetime.datetime
:param cleanup_started_at:
:type cleanup_started_at: ~datetime.datetime
:param current_state: Possible values include: "Preparation", "ResourceAcquisition", "Queued",
"Submission", "Monitoring", "Cleanup", "Ended".
:type current_state: str or ~azure.synapse.spark.models.PluginCurrentState
"""
_attribute_map = {
'preparation_started_at': {'key': 'preparationStartedAt', 'type': 'iso-8601'},
'resource_acquisition_started_at': {'key': 'resourceAcquisitionStartedAt', 'type': 'iso-8601'},
'submission_started_at': {'key': 'submissionStartedAt', 'type': 'iso-8601'},
'monitoring_started_at': {'key': 'monitoringStartedAt', 'type': 'iso-8601'},
'cleanup_started_at': {'key': 'cleanupStartedAt', 'type': 'iso-8601'},
'current_state': {'key': 'currentState', 'type': 'str'},
}
def __init__(
self,
*,
preparation_started_at: Optional[datetime.datetime] = None,
resource_acquisition_started_at: Optional[datetime.datetime] = None,
submission_started_at: Optional[datetime.datetime] = None,
monitoring_started_at: Optional[datetime.datetime] = None,
cleanup_started_at: Optional[datetime.datetime] = None,
current_state: Optional[Union[str, "PluginCurrentState"]] = None,
**kwargs
):
super(SparkServicePlugin, self).__init__(**kwargs)
self.preparation_started_at = preparation_started_at
self.resource_acquisition_started_at = resource_acquisition_started_at
self.submission_started_at = submission_started_at
self.monitoring_started_at = monitoring_started_at
self.cleanup_started_at = cleanup_started_at
self.current_state = current_state
[docs]class SparkSession(msrest.serialization.Model):
"""SparkSession.
All required parameters must be populated in order to send to Azure.
:param livy_info:
:type livy_info: ~azure.synapse.spark.models.SparkSessionState
:param name:
:type name: str
:param workspace_name:
:type workspace_name: str
:param spark_pool_name:
:type spark_pool_name: str
:param submitter_name:
:type submitter_name: str
:param submitter_id:
:type submitter_id: str
:param artifact_id:
:type artifact_id: str
:param job_type: The job type. Possible values include: "SparkBatch", "SparkSession".
:type job_type: str or ~azure.synapse.spark.models.SparkJobType
:param result: Possible values include: "Uncertain", "Succeeded", "Failed", "Cancelled".
:type result: str or ~azure.synapse.spark.models.SparkSessionResultType
:param scheduler:
:type scheduler: ~azure.synapse.spark.models.SparkScheduler
:param plugin:
:type plugin: ~azure.synapse.spark.models.SparkServicePlugin
:param errors: The error information.
:type errors: list[~azure.synapse.spark.models.SparkServiceError]
:param tags: A set of tags. Dictionary of :code:`<string>`.
:type tags: dict[str, str]
:param id: Required.
:type id: int
:param app_id:
:type app_id: str
:param app_info: Dictionary of :code:`<string>`.
:type app_info: dict[str, str]
:param state:
:type state: str
:param log_lines:
:type log_lines: list[str]
"""
_validation = {
'id': {'required': True},
}
_attribute_map = {
'livy_info': {'key': 'livyInfo', 'type': 'SparkSessionState'},
'name': {'key': 'name', 'type': 'str'},
'workspace_name': {'key': 'workspaceName', 'type': 'str'},
'spark_pool_name': {'key': 'sparkPoolName', 'type': 'str'},
'submitter_name': {'key': 'submitterName', 'type': 'str'},
'submitter_id': {'key': 'submitterId', 'type': 'str'},
'artifact_id': {'key': 'artifactId', 'type': 'str'},
'job_type': {'key': 'jobType', 'type': 'str'},
'result': {'key': 'result', 'type': 'str'},
'scheduler': {'key': 'schedulerInfo', 'type': 'SparkScheduler'},
'plugin': {'key': 'pluginInfo', 'type': 'SparkServicePlugin'},
'errors': {'key': 'errorInfo', 'type': '[SparkServiceError]'},
'tags': {'key': 'tags', 'type': '{str}'},
'id': {'key': 'id', 'type': 'int'},
'app_id': {'key': 'appId', 'type': 'str'},
'app_info': {'key': 'appInfo', 'type': '{str}'},
'state': {'key': 'state', 'type': 'str'},
'log_lines': {'key': 'log', 'type': '[str]'},
}
def __init__(
self,
*,
id: int,
livy_info: Optional["SparkSessionState"] = None,
name: Optional[str] = None,
workspace_name: Optional[str] = None,
spark_pool_name: Optional[str] = None,
submitter_name: Optional[str] = None,
submitter_id: Optional[str] = None,
artifact_id: Optional[str] = None,
job_type: Optional[Union[str, "SparkJobType"]] = None,
result: Optional[Union[str, "SparkSessionResultType"]] = None,
scheduler: Optional["SparkScheduler"] = None,
plugin: Optional["SparkServicePlugin"] = None,
errors: Optional[List["SparkServiceError"]] = None,
tags: Optional[Dict[str, str]] = None,
app_id: Optional[str] = None,
app_info: Optional[Dict[str, str]] = None,
state: Optional[str] = None,
log_lines: Optional[List[str]] = None,
**kwargs
):
super(SparkSession, self).__init__(**kwargs)
self.livy_info = livy_info
self.name = name
self.workspace_name = workspace_name
self.spark_pool_name = spark_pool_name
self.submitter_name = submitter_name
self.submitter_id = submitter_id
self.artifact_id = artifact_id
self.job_type = job_type
self.result = result
self.scheduler = scheduler
self.plugin = plugin
self.errors = errors
self.tags = tags
self.id = id
self.app_id = app_id
self.app_info = app_info
self.state = state
self.log_lines = log_lines
[docs]class SparkSessionCollection(msrest.serialization.Model):
"""SparkSessionCollection.
All required parameters must be populated in order to send to Azure.
:param from_property: Required.
:type from_property: int
:param total: Required.
:type total: int
:param sessions:
:type sessions: list[~azure.synapse.spark.models.SparkSession]
"""
_validation = {
'from_property': {'required': True},
'total': {'required': True},
}
_attribute_map = {
'from_property': {'key': 'from', 'type': 'int'},
'total': {'key': 'total', 'type': 'int'},
'sessions': {'key': 'sessions', 'type': '[SparkSession]'},
}
def __init__(
self,
*,
from_property: int,
total: int,
sessions: Optional[List["SparkSession"]] = None,
**kwargs
):
super(SparkSessionCollection, self).__init__(**kwargs)
self.from_property = from_property
self.total = total
self.sessions = sessions
[docs]class SparkSessionOptions(msrest.serialization.Model):
"""SparkSessionOptions.
All required parameters must be populated in order to send to Azure.
:param tags: A set of tags. Dictionary of :code:`<string>`.
:type tags: dict[str, str]
:param artifact_id:
:type artifact_id: str
:param name: Required.
:type name: str
:param file:
:type file: str
:param class_name:
:type class_name: str
:param arguments:
:type arguments: list[str]
:param jars:
:type jars: list[str]
:param python_files:
:type python_files: list[str]
:param files:
:type files: list[str]
:param archives:
:type archives: list[str]
:param configuration: Dictionary of :code:`<string>`.
:type configuration: dict[str, str]
:param driver_memory:
:type driver_memory: str
:param driver_cores:
:type driver_cores: int
:param executor_memory:
:type executor_memory: str
:param executor_cores:
:type executor_cores: int
:param executor_count:
:type executor_count: int
"""
_validation = {
'name': {'required': True},
}
_attribute_map = {
'tags': {'key': 'tags', 'type': '{str}'},
'artifact_id': {'key': 'artifactId', 'type': 'str'},
'name': {'key': 'name', 'type': 'str'},
'file': {'key': 'file', 'type': 'str'},
'class_name': {'key': 'className', 'type': 'str'},
'arguments': {'key': 'args', 'type': '[str]'},
'jars': {'key': 'jars', 'type': '[str]'},
'python_files': {'key': 'pyFiles', 'type': '[str]'},
'files': {'key': 'files', 'type': '[str]'},
'archives': {'key': 'archives', 'type': '[str]'},
'configuration': {'key': 'conf', 'type': '{str}'},
'driver_memory': {'key': 'driverMemory', 'type': 'str'},
'driver_cores': {'key': 'driverCores', 'type': 'int'},
'executor_memory': {'key': 'executorMemory', 'type': 'str'},
'executor_cores': {'key': 'executorCores', 'type': 'int'},
'executor_count': {'key': 'numExecutors', 'type': 'int'},
}
def __init__(
self,
*,
name: str,
tags: Optional[Dict[str, str]] = None,
artifact_id: Optional[str] = None,
file: Optional[str] = None,
class_name: Optional[str] = None,
arguments: Optional[List[str]] = None,
jars: Optional[List[str]] = None,
python_files: Optional[List[str]] = None,
files: Optional[List[str]] = None,
archives: Optional[List[str]] = None,
configuration: Optional[Dict[str, str]] = None,
driver_memory: Optional[str] = None,
driver_cores: Optional[int] = None,
executor_memory: Optional[str] = None,
executor_cores: Optional[int] = None,
executor_count: Optional[int] = None,
**kwargs
):
super(SparkSessionOptions, self).__init__(**kwargs)
self.tags = tags
self.artifact_id = artifact_id
self.name = name
self.file = file
self.class_name = class_name
self.arguments = arguments
self.jars = jars
self.python_files = python_files
self.files = files
self.archives = archives
self.configuration = configuration
self.driver_memory = driver_memory
self.driver_cores = driver_cores
self.executor_memory = executor_memory
self.executor_cores = executor_cores
self.executor_count = executor_count
[docs]class SparkSessionState(msrest.serialization.Model):
"""SparkSessionState.
:param not_started_at:
:type not_started_at: ~datetime.datetime
:param starting_at:
:type starting_at: ~datetime.datetime
:param idle_at:
:type idle_at: ~datetime.datetime
:param dead_at:
:type dead_at: ~datetime.datetime
:param shutting_down_at:
:type shutting_down_at: ~datetime.datetime
:param terminated_at: the time that at which "killed" livy state was first seen.
:type terminated_at: ~datetime.datetime
:param recovering_at:
:type recovering_at: ~datetime.datetime
:param busy_at:
:type busy_at: ~datetime.datetime
:param error_at:
:type error_at: ~datetime.datetime
:param current_state:
:type current_state: str
:param job_creation_request:
:type job_creation_request: ~azure.synapse.spark.models.SparkRequest
"""
_attribute_map = {
'not_started_at': {'key': 'notStartedAt', 'type': 'iso-8601'},
'starting_at': {'key': 'startingAt', 'type': 'iso-8601'},
'idle_at': {'key': 'idleAt', 'type': 'iso-8601'},
'dead_at': {'key': 'deadAt', 'type': 'iso-8601'},
'shutting_down_at': {'key': 'shuttingDownAt', 'type': 'iso-8601'},
'terminated_at': {'key': 'killedAt', 'type': 'iso-8601'},
'recovering_at': {'key': 'recoveringAt', 'type': 'iso-8601'},
'busy_at': {'key': 'busyAt', 'type': 'iso-8601'},
'error_at': {'key': 'errorAt', 'type': 'iso-8601'},
'current_state': {'key': 'currentState', 'type': 'str'},
'job_creation_request': {'key': 'jobCreationRequest', 'type': 'SparkRequest'},
}
def __init__(
self,
*,
not_started_at: Optional[datetime.datetime] = None,
starting_at: Optional[datetime.datetime] = None,
idle_at: Optional[datetime.datetime] = None,
dead_at: Optional[datetime.datetime] = None,
shutting_down_at: Optional[datetime.datetime] = None,
terminated_at: Optional[datetime.datetime] = None,
recovering_at: Optional[datetime.datetime] = None,
busy_at: Optional[datetime.datetime] = None,
error_at: Optional[datetime.datetime] = None,
current_state: Optional[str] = None,
job_creation_request: Optional["SparkRequest"] = None,
**kwargs
):
super(SparkSessionState, self).__init__(**kwargs)
self.not_started_at = not_started_at
self.starting_at = starting_at
self.idle_at = idle_at
self.dead_at = dead_at
self.shutting_down_at = shutting_down_at
self.terminated_at = terminated_at
self.recovering_at = recovering_at
self.busy_at = busy_at
self.error_at = error_at
self.current_state = current_state
self.job_creation_request = job_creation_request
[docs]class SparkStatement(msrest.serialization.Model):
"""SparkStatement.
All required parameters must be populated in order to send to Azure.
:param id: Required.
:type id: int
:param code:
:type code: str
:param state:
:type state: str
:param output:
:type output: ~azure.synapse.spark.models.SparkStatementOutput
"""
_validation = {
'id': {'required': True},
}
_attribute_map = {
'id': {'key': 'id', 'type': 'int'},
'code': {'key': 'code', 'type': 'str'},
'state': {'key': 'state', 'type': 'str'},
'output': {'key': 'output', 'type': 'SparkStatementOutput'},
}
def __init__(
self,
*,
id: int,
code: Optional[str] = None,
state: Optional[str] = None,
output: Optional["SparkStatementOutput"] = None,
**kwargs
):
super(SparkStatement, self).__init__(**kwargs)
self.id = id
self.code = code
self.state = state
self.output = output
[docs]class SparkStatementCancellationResult(msrest.serialization.Model):
"""SparkStatementCancellationResult.
:param message: The msg property from the Livy API. The value is always "canceled".
:type message: str
"""
_attribute_map = {
'message': {'key': 'msg', 'type': 'str'},
}
def __init__(
self,
*,
message: Optional[str] = None,
**kwargs
):
super(SparkStatementCancellationResult, self).__init__(**kwargs)
self.message = message
[docs]class SparkStatementCollection(msrest.serialization.Model):
"""SparkStatementCollection.
All required parameters must be populated in order to send to Azure.
:param total: Required.
:type total: int
:param statements:
:type statements: list[~azure.synapse.spark.models.SparkStatement]
"""
_validation = {
'total': {'required': True},
}
_attribute_map = {
'total': {'key': 'total_statements', 'type': 'int'},
'statements': {'key': 'statements', 'type': '[SparkStatement]'},
}
def __init__(
self,
*,
total: int,
statements: Optional[List["SparkStatement"]] = None,
**kwargs
):
super(SparkStatementCollection, self).__init__(**kwargs)
self.total = total
self.statements = statements
[docs]class SparkStatementOptions(msrest.serialization.Model):
"""SparkStatementOptions.
:param code:
:type code: str
:param kind: Possible values include: "spark", "pyspark", "dotnetspark", "sql".
:type kind: str or ~azure.synapse.spark.models.SparkStatementLanguageType
"""
_attribute_map = {
'code': {'key': 'code', 'type': 'str'},
'kind': {'key': 'kind', 'type': 'str'},
}
def __init__(
self,
*,
code: Optional[str] = None,
kind: Optional[Union[str, "SparkStatementLanguageType"]] = None,
**kwargs
):
super(SparkStatementOptions, self).__init__(**kwargs)
self.code = code
self.kind = kind
[docs]class SparkStatementOutput(msrest.serialization.Model):
"""SparkStatementOutput.
All required parameters must be populated in order to send to Azure.
:param status:
:type status: str
:param execution_count: Required.
:type execution_count: int
:param data: Any object.
:type data: object
:param error_name:
:type error_name: str
:param error_value:
:type error_value: str
:param traceback:
:type traceback: list[str]
"""
_validation = {
'execution_count': {'required': True},
}
_attribute_map = {
'status': {'key': 'status', 'type': 'str'},
'execution_count': {'key': 'execution_count', 'type': 'int'},
'data': {'key': 'data', 'type': 'object'},
'error_name': {'key': 'ename', 'type': 'str'},
'error_value': {'key': 'evalue', 'type': 'str'},
'traceback': {'key': 'traceback', 'type': '[str]'},
}
def __init__(
self,
*,
execution_count: int,
status: Optional[str] = None,
data: Optional[object] = None,
error_name: Optional[str] = None,
error_value: Optional[str] = None,
traceback: Optional[List[str]] = None,
**kwargs
):
super(SparkStatementOutput, self).__init__(**kwargs)
self.status = status
self.execution_count = execution_count
self.data = data
self.error_name = error_name
self.error_value = error_value
self.traceback = traceback