SparkJob Class
Definition
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Spark job definition.
public class SparkJob : Azure.ResourceManager.MachineLearning.Models.MachineLearningJobProperties, System.ClientModel.Primitives.IJsonModel<Azure.ResourceManager.MachineLearning.Models.SparkJob>, System.ClientModel.Primitives.IPersistableModel<Azure.ResourceManager.MachineLearning.Models.SparkJob>public class SparkJob : Azure.ResourceManager.MachineLearning.Models.MachineLearningJobPropertiestype SparkJob = class
inherit MachineLearningJobProperties
interface IJsonModel<SparkJob>
interface IPersistableModel<SparkJob>type SparkJob = class
inherit MachineLearningJobPropertiesPublic Class SparkJob
Inherits MachineLearningJobProperties
Implements IJsonModel(Of SparkJob), IPersistableModel(Of SparkJob)Public Class SparkJob
Inherits MachineLearningJobProperties- Inheritance
- Implements
Constructors
| SparkJob(ResourceIdentifier, SparkJobEntry) |
Initializes a new instance of SparkJob. |
| SparkJob(String, SparkJobEntry) |
Initializes a new instance of SparkJob. |
Properties
| Archives |
Archive files used in the job. |
| Args |
Arguments for the job. |
| CodeId |
[Required] arm-id of the code asset. |
| ComponentId |
ARM resource ID of the component resource. (Inherited from MachineLearningJobProperties) |
| ComputeId |
ARM resource ID of the compute resource. (Inherited from MachineLearningJobProperties) |
| Conf |
Spark configured properties. |
| Description |
The asset description text. (Inherited from MachineLearningResourceBase) |
| DisplayName |
Display name of job. (Inherited from MachineLearningJobProperties) |
| Entry |
[Required] The entry to execute on startup of the job. Please note SparkJobEntry is the base class. According to the scenario, a derived class of the base class might need to be assigned here, or this property needs to be casted to one of the possible derived classes. The available derived classes include SparkJobPythonEntry and SparkJobScalaEntry. |
| EnvironmentId |
The ARM resource ID of the Environment specification for the job. |
| EnvironmentVariables |
Environment variables included in the job. |
| ExperimentName |
The name of the experiment the job belongs to. If not set, the job is placed in the "Default" experiment. (Inherited from MachineLearningJobProperties) |
| Files |
Files used in the job. |
| Identity |
Identity configuration. If set, this should be one of AmlToken, ManagedIdentity, UserIdentity or null. Defaults to AmlToken if null. Please note MachineLearningIdentityConfiguration is the base class. According to the scenario, a derived class of the base class might need to be assigned here, or this property needs to be casted to one of the possible derived classes. The available derived classes include AmlToken, MachineLearningManagedIdentity and MachineLearningUserIdentity. (Inherited from MachineLearningJobProperties) |
| Inputs |
Mapping of input data bindings used in the job. Please note MachineLearningJobInput is the base class. According to the scenario, a derived class of the base class might need to be assigned here, or this property needs to be casted to one of the possible derived classes. The available derived classes include MachineLearningCustomModelJobInput, MachineLearningLiteralJobInput, MachineLearningFlowModelJobInput, MachineLearningTableJobInput, MachineLearningTritonModelJobInput, MachineLearningUriFileJobInput and MachineLearningUriFolderJobInput. |
| IsArchived |
Is the asset archived?. (Inherited from MachineLearningJobProperties) |
| Jars |
Jar files used in the job. |
| NotificationSetting |
Notification setting for the job. (Inherited from MachineLearningJobProperties) |
| Outputs |
Mapping of output data bindings used in the job. Please note MachineLearningJobOutput is the base class. According to the scenario, a derived class of the base class might need to be assigned here, or this property needs to be casted to one of the possible derived classes. The available derived classes include MachineLearningCustomModelJobOutput, MachineLearningFlowModelJobOutput, MachineLearningTableJobOutput, MachineLearningTritonModelJobOutput, MachineLearningUriFileJobOutput and MachineLearningUriFolderJobOutput. |
| Properties |
The asset property dictionary. (Inherited from MachineLearningResourceBase) |
| PyFiles |
Python files used in the job. |
| QueueJobTier |
Controls the compute job tier. |
| QueueSettings |
Queue settings for the job. |
| Resources |
Compute Resource configuration for the job. |
| SecretsConfiguration |
Configuration for secrets to be made available during runtime. (Inherited from MachineLearningJobProperties) |
| Services |
List of JobEndpoints. For local jobs, a job endpoint will have an endpoint value of FileStreamObject. (Inherited from MachineLearningJobProperties) |
| Status |
Status of the job. (Inherited from MachineLearningJobProperties) |
| Tags |
Tag dictionary. Tags can be added, removed, and updated. (Inherited from MachineLearningResourceBase) |
