Source code for azure.synapse.spark.models._models_py3

# 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: :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: :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 msg: :type msg: str """ _attribute_map = { 'msg': {'key': 'msg', 'type': 'str'}, } def __init__( self, *, msg: Optional[str] = None, **kwargs ): super(SparkStatementCancellationResult, self).__init__(**kwargs) self.msg = msg
[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