JobRun (AWS SDK for Java

java.lang.Object
- com.amazonaws.services.glue.model.JobRun

All Implemented Interfaces:: StructuredPojo, Serializable, Cloneable

@Generated(value="com.amazonaws:aws-java-sdk-code-generator")
public class JobRun
extends Object
implements Serializable, Cloneable, StructuredPojo

Contains information about a job run.

See Also:: AWS API Documentation, Serialized Form

Constructor Summary

Constructors
Constructor and Description

JobRun()

Constructors
Constructor and Description
`JobRun()`

Method Summary

All Methods Instance Methods Concrete Methods Deprecated Methods
Modifier and Type	Method and Description
`JobRun`	`addArgumentsEntry(String key, String value)` Add a single Arguments entry
`JobRun`	`clearArgumentsEntries()` Removes all the entries added into Arguments.
`JobRun`	`clone()`
`boolean`	`equals(Object obj)`
`Integer`	`getAllocatedCapacity()` Deprecated.
`Map<String,String>`	`getArguments()` The job arguments associated with this run.
`Integer`	`getAttempt()` The number of the attempt to run this job.
`Date`	`getCompletedOn()` The date and time that this job run completed.
`Double`	`getDPUSeconds()` This field can be set for either job runs with execution class `FLEX` or when Auto Scaling is enabled, and represents the total time each executor ran during the lifecycle of a job run in seconds, multiplied by a DPU factor (1 for `G.1X`, 2 for `G.2X`, or 0.25 for `G.025X` workers).
`String`	`getErrorMessage()` An error message associated with this job run.
`String`	`getExecutionClass()` Indicates whether the job is run with a standard or flexible execution class.
`Integer`	`getExecutionTime()` The amount of time (in seconds) that the job run consumed resources.
`String`	`getGlueVersion()` In Spark jobs, `GlueVersion` determines the versions of Apache Spark and Python that Glue available in a job.
`String`	`getId()` The ID of this job run.
`String`	`getJobMode()` A mode that describes how a job was created.
`String`	`getJobName()` The name of the job definition being used in this run.
`String`	`getJobRunState()` The current state of the job run.
`Date`	`getLastModifiedOn()` The last time that this job run was modified.
`String`	`getLogGroupName()` The name of the log group for secure logging that can be server-side encrypted in Amazon CloudWatch using KMS.
`String`	`getMaintenanceWindow()` This field specifies a day of the week and hour for a maintenance window for streaming jobs.
`Double`	`getMaxCapacity()` For Glue version 1.0 or earlier jobs, using the standard worker type, the number of Glue data processing units (DPUs) that can be allocated when this job runs.
`NotificationProperty`	`getNotificationProperty()` Specifies configuration properties of a job run notification.
`Integer`	`getNumberOfWorkers()` The number of workers of a defined `workerType` that are allocated when a job runs.
`List<Predecessor>`	`getPredecessorRuns()` A list of predecessors to this job run.
`String`	`getPreviousRunId()` The ID of the previous run of this job.
`String`	`getProfileName()` The name of an Glue usage profile associated with the job run.
`String`	`getSecurityConfiguration()` The name of the `SecurityConfiguration` structure to be used with this job run.
`Date`	`getStartedOn()` The date and time at which this job run was started.
`Integer`	`getTimeout()` The `JobRun` timeout in minutes.
`String`	`getTriggerName()` The name of the trigger that started this job run.
`String`	`getWorkerType()` The type of predefined worker that is allocated when a job runs.
`int`	`hashCode()`
`void`	`marshall(ProtocolMarshaller protocolMarshaller)` Marshalls this structured data using the given `ProtocolMarshaller`.
`void`	`setAllocatedCapacity(Integer allocatedCapacity)` Deprecated.
`void`	`setArguments(Map<String,String> arguments)` The job arguments associated with this run.
`void`	`setAttempt(Integer attempt)` The number of the attempt to run this job.
`void`	`setCompletedOn(Date completedOn)` The date and time that this job run completed.
`void`	`setDPUSeconds(Double dPUSeconds)` This field can be set for either job runs with execution class `FLEX` or when Auto Scaling is enabled, and represents the total time each executor ran during the lifecycle of a job run in seconds, multiplied by a DPU factor (1 for `G.1X`, 2 for `G.2X`, or 0.25 for `G.025X` workers).
`void`	`setErrorMessage(String errorMessage)` An error message associated with this job run.
`void`	`setExecutionClass(String executionClass)` Indicates whether the job is run with a standard or flexible execution class.
`void`	`setExecutionTime(Integer executionTime)` The amount of time (in seconds) that the job run consumed resources.
`void`	`setGlueVersion(String glueVersion)` In Spark jobs, `GlueVersion` determines the versions of Apache Spark and Python that Glue available in a job.
`void`	`setId(String id)` The ID of this job run.
`void`	`setJobMode(String jobMode)` A mode that describes how a job was created.
`void`	`setJobName(String jobName)` The name of the job definition being used in this run.
`void`	`setJobRunState(String jobRunState)` The current state of the job run.
`void`	`setLastModifiedOn(Date lastModifiedOn)` The last time that this job run was modified.
`void`	`setLogGroupName(String logGroupName)` The name of the log group for secure logging that can be server-side encrypted in Amazon CloudWatch using KMS.
`void`	`setMaintenanceWindow(String maintenanceWindow)` This field specifies a day of the week and hour for a maintenance window for streaming jobs.
`void`	`setMaxCapacity(Double maxCapacity)` For Glue version 1.0 or earlier jobs, using the standard worker type, the number of Glue data processing units (DPUs) that can be allocated when this job runs.
`void`	`setNotificationProperty(NotificationProperty notificationProperty)` Specifies configuration properties of a job run notification.
`void`	`setNumberOfWorkers(Integer numberOfWorkers)` The number of workers of a defined `workerType` that are allocated when a job runs.
`void`	`setPredecessorRuns(Collection<Predecessor> predecessorRuns)` A list of predecessors to this job run.
`void`	`setPreviousRunId(String previousRunId)` The ID of the previous run of this job.
`void`	`setProfileName(String profileName)` The name of an Glue usage profile associated with the job run.
`void`	`setSecurityConfiguration(String securityConfiguration)` The name of the `SecurityConfiguration` structure to be used with this job run.
`void`	`setStartedOn(Date startedOn)` The date and time at which this job run was started.
`void`	`setTimeout(Integer timeout)` The `JobRun` timeout in minutes.
`void`	`setTriggerName(String triggerName)` The name of the trigger that started this job run.
`void`	`setWorkerType(String workerType)` The type of predefined worker that is allocated when a job runs.
`String`	`toString()` Returns a string representation of this object.
`JobRun`	`withAllocatedCapacity(Integer allocatedCapacity)` Deprecated.
`JobRun`	`withArguments(Map<String,String> arguments)` The job arguments associated with this run.
`JobRun`	`withAttempt(Integer attempt)` The number of the attempt to run this job.
`JobRun`	`withCompletedOn(Date completedOn)` The date and time that this job run completed.
`JobRun`	`withDPUSeconds(Double dPUSeconds)` This field can be set for either job runs with execution class `FLEX` or when Auto Scaling is enabled, and represents the total time each executor ran during the lifecycle of a job run in seconds, multiplied by a DPU factor (1 for `G.1X`, 2 for `G.2X`, or 0.25 for `G.025X` workers).
`JobRun`	`withErrorMessage(String errorMessage)` An error message associated with this job run.
`JobRun`	`withExecutionClass(ExecutionClass executionClass)` Indicates whether the job is run with a standard or flexible execution class.
`JobRun`	`withExecutionClass(String executionClass)` Indicates whether the job is run with a standard or flexible execution class.
`JobRun`	`withExecutionTime(Integer executionTime)` The amount of time (in seconds) that the job run consumed resources.
`JobRun`	`withGlueVersion(String glueVersion)` In Spark jobs, `GlueVersion` determines the versions of Apache Spark and Python that Glue available in a job.
`JobRun`	`withId(String id)` The ID of this job run.
`JobRun`	`withJobMode(JobMode jobMode)` A mode that describes how a job was created.
`JobRun`	`withJobMode(String jobMode)` A mode that describes how a job was created.
`JobRun`	`withJobName(String jobName)` The name of the job definition being used in this run.
`JobRun`	`withJobRunState(JobRunState jobRunState)` The current state of the job run.
`JobRun`	`withJobRunState(String jobRunState)` The current state of the job run.
`JobRun`	`withLastModifiedOn(Date lastModifiedOn)` The last time that this job run was modified.
`JobRun`	`withLogGroupName(String logGroupName)` The name of the log group for secure logging that can be server-side encrypted in Amazon CloudWatch using KMS.
`JobRun`	`withMaintenanceWindow(String maintenanceWindow)` This field specifies a day of the week and hour for a maintenance window for streaming jobs.
`JobRun`	`withMaxCapacity(Double maxCapacity)` For Glue version 1.0 or earlier jobs, using the standard worker type, the number of Glue data processing units (DPUs) that can be allocated when this job runs.
`JobRun`	`withNotificationProperty(NotificationProperty notificationProperty)` Specifies configuration properties of a job run notification.
`JobRun`	`withNumberOfWorkers(Integer numberOfWorkers)` The number of workers of a defined `workerType` that are allocated when a job runs.
`JobRun`	`withPredecessorRuns(Collection<Predecessor> predecessorRuns)` A list of predecessors to this job run.
`JobRun`	`withPredecessorRuns(Predecessor... predecessorRuns)` A list of predecessors to this job run.
`JobRun`	`withPreviousRunId(String previousRunId)` The ID of the previous run of this job.
`JobRun`	`withProfileName(String profileName)` The name of an Glue usage profile associated with the job run.
`JobRun`	`withSecurityConfiguration(String securityConfiguration)` The name of the `SecurityConfiguration` structure to be used with this job run.
`JobRun`	`withStartedOn(Date startedOn)` The date and time at which this job run was started.
`JobRun`	`withTimeout(Integer timeout)` The `JobRun` timeout in minutes.
`JobRun`	`withTriggerName(String triggerName)` The name of the trigger that started this job run.
`JobRun`	`withWorkerType(String workerType)` The type of predefined worker that is allocated when a job runs.
`JobRun`	`withWorkerType(WorkerType workerType)` The type of predefined worker that is allocated when a job runs.

Methods inherited from class java.lang.Object
getClass, notify, notifyAll, wait, wait, wait

- Constructor Detail
  - JobRun
```
public JobRun()
```
- Method Detail
  - setId
```
public void setId(String id)
```
    The ID of this job run.
    
    Parameters:
    
    id - The ID of this job run.
  - getId
```
public String getId()
```
    The ID of this job run.
    
    Returns:
    
    The ID of this job run.
  - withId
```
public JobRun withId(String id)
```
    The ID of this job run.
    
    Parameters:
    
    id - The ID of this job run.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setAttempt
```
public void setAttempt(Integer attempt)
```
    The number of the attempt to run this job.
    
    Parameters:
    
    attempt - The number of the attempt to run this job.
  - getAttempt
```
public Integer getAttempt()
```
    The number of the attempt to run this job.
    
    Returns:
    
    The number of the attempt to run this job.
  - withAttempt
```
public JobRun withAttempt(Integer attempt)
```
    The number of the attempt to run this job.
    
    Parameters:
    
    attempt - The number of the attempt to run this job.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setPreviousRunId
```
public void setPreviousRunId(String previousRunId)
```
    The ID of the previous run of this job. For example, the JobRunId specified in the StartJobRun action.
    
    Parameters:
    
    previousRunId - The ID of the previous run of this job. For example, the JobRunId specified in the StartJobRun action.
  - getPreviousRunId
```
public String getPreviousRunId()
```
    The ID of the previous run of this job. For example, the JobRunId specified in the StartJobRun action.
    
    Returns:
    
    The ID of the previous run of this job. For example, the JobRunId specified in the StartJobRun action.
  - withPreviousRunId
```
public JobRun withPreviousRunId(String previousRunId)
```
    The ID of the previous run of this job. For example, the JobRunId specified in the StartJobRun action.
    
    Parameters:
    
    previousRunId - The ID of the previous run of this job. For example, the JobRunId specified in the StartJobRun action.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setTriggerName
```
public void setTriggerName(String triggerName)
```
    The name of the trigger that started this job run.
    
    Parameters:
    
    triggerName - The name of the trigger that started this job run.
  - getTriggerName
```
public String getTriggerName()
```
    The name of the trigger that started this job run.
    
    Returns:
    
    The name of the trigger that started this job run.
  - withTriggerName
```
public JobRun withTriggerName(String triggerName)
```
    The name of the trigger that started this job run.
    
    Parameters:
    
    triggerName - The name of the trigger that started this job run.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setJobName
```
public void setJobName(String jobName)
```
    The name of the job definition being used in this run.
    
    Parameters:
    
    jobName - The name of the job definition being used in this run.
  - getJobName
```
public String getJobName()
```
    The name of the job definition being used in this run.
    
    Returns:
    
    The name of the job definition being used in this run.
  - withJobName
```
public JobRun withJobName(String jobName)
```
    The name of the job definition being used in this run.
    
    Parameters:
    
    jobName - The name of the job definition being used in this run.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setJobMode
```
public void setJobMode(String jobMode)
```
    A mode that describes how a job was created. Valid values are:
    - SCRIPT - The job was created using the Glue Studio script editor.
    - VISUAL - The job was created using the Glue Studio visual editor.
    - NOTEBOOK - The job was created using an interactive sessions notebook.
    When the JobMode field is missing or null, SCRIPT is assigned as the default value.
    Parameters:
    jobMode - A mode that describes how a job was created. Valid values are:
    
    SCRIPT - The job was created using the Glue Studio script editor.
    
    VISUAL - The job was created using the Glue Studio visual editor.
    
    NOTEBOOK - The job was created using an interactive sessions notebook.
    
    When the JobMode field is missing or null, SCRIPT is assigned as the default value.
    See Also:
    
    JobMode
  - getJobMode
```
public String getJobMode()
```
    A mode that describes how a job was created. Valid values are:
    - SCRIPT - The job was created using the Glue Studio script editor.
    - VISUAL - The job was created using the Glue Studio visual editor.
    - NOTEBOOK - The job was created using an interactive sessions notebook.
    When the JobMode field is missing or null, SCRIPT is assigned as the default value.
    Returns:
    A mode that describes how a job was created. Valid values are:
    
    SCRIPT - The job was created using the Glue Studio script editor.
    
    VISUAL - The job was created using the Glue Studio visual editor.
    
    NOTEBOOK - The job was created using an interactive sessions notebook.
    
    When the JobMode field is missing or null, SCRIPT is assigned as the default value.
    See Also:
    
    JobMode
  - withJobMode
```
public JobRun withJobMode(String jobMode)
```
    A mode that describes how a job was created. Valid values are:
    - SCRIPT - The job was created using the Glue Studio script editor.
    - VISUAL - The job was created using the Glue Studio visual editor.
    - NOTEBOOK - The job was created using an interactive sessions notebook.
    When the JobMode field is missing or null, SCRIPT is assigned as the default value.
    Parameters:
    jobMode - A mode that describes how a job was created. Valid values are:
    
    SCRIPT - The job was created using the Glue Studio script editor.
    
    VISUAL - The job was created using the Glue Studio visual editor.
    
    NOTEBOOK - The job was created using an interactive sessions notebook.
    
    When the JobMode field is missing or null, SCRIPT is assigned as the default value.
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
    
    See Also:
    
    JobMode
  - withJobMode
```
public JobRun withJobMode(JobMode jobMode)
```
    A mode that describes how a job was created. Valid values are:
    - SCRIPT - The job was created using the Glue Studio script editor.
    - VISUAL - The job was created using the Glue Studio visual editor.
    - NOTEBOOK - The job was created using an interactive sessions notebook.
    When the JobMode field is missing or null, SCRIPT is assigned as the default value.
    Parameters:
    jobMode - A mode that describes how a job was created. Valid values are:
    
    SCRIPT - The job was created using the Glue Studio script editor.
    
    VISUAL - The job was created using the Glue Studio visual editor.
    
    NOTEBOOK - The job was created using an interactive sessions notebook.
    
    When the JobMode field is missing or null, SCRIPT is assigned as the default value.
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
    
    See Also:
    
    JobMode
  - setStartedOn
```
public void setStartedOn(Date startedOn)
```
    The date and time at which this job run was started.
    
    Parameters:
    
    startedOn - The date and time at which this job run was started.
  - getStartedOn
```
public Date getStartedOn()
```
    The date and time at which this job run was started.
    
    Returns:
    
    The date and time at which this job run was started.
  - withStartedOn
```
public JobRun withStartedOn(Date startedOn)
```
    The date and time at which this job run was started.
    
    Parameters:
    
    startedOn - The date and time at which this job run was started.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setLastModifiedOn
```
public void setLastModifiedOn(Date lastModifiedOn)
```
    The last time that this job run was modified.
    
    Parameters:
    
    lastModifiedOn - The last time that this job run was modified.
  - getLastModifiedOn
```
public Date getLastModifiedOn()
```
    The last time that this job run was modified.
    
    Returns:
    
    The last time that this job run was modified.
  - withLastModifiedOn
```
public JobRun withLastModifiedOn(Date lastModifiedOn)
```
    The last time that this job run was modified.
    
    Parameters:
    
    lastModifiedOn - The last time that this job run was modified.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setCompletedOn
```
public void setCompletedOn(Date completedOn)
```
    The date and time that this job run completed.
    
    Parameters:
    
    completedOn - The date and time that this job run completed.
  - getCompletedOn
```
public Date getCompletedOn()
```
    The date and time that this job run completed.
    
    Returns:
    
    The date and time that this job run completed.
  - withCompletedOn
```
public JobRun withCompletedOn(Date completedOn)
```
    The date and time that this job run completed.
    
    Parameters:
    
    completedOn - The date and time that this job run completed.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setJobRunState
```
public void setJobRunState(String jobRunState)
```
    The current state of the job run. For more information about the statuses of jobs that have terminated abnormally, see Glue Job Run Statuses.
    
    Parameters:
    
    jobRunState - The current state of the job run. For more information about the statuses of jobs that have terminated abnormally, see Glue Job Run Statuses.
    
    See Also:
    
    JobRunState
  - getJobRunState
```
public String getJobRunState()
```
    The current state of the job run. For more information about the statuses of jobs that have terminated abnormally, see Glue Job Run Statuses.
    
    Returns:
    
    The current state of the job run. For more information about the statuses of jobs that have terminated abnormally, see Glue Job Run Statuses.
    
    See Also:
    
    JobRunState
  - withJobRunState
```
public JobRun withJobRunState(String jobRunState)
```
    The current state of the job run. For more information about the statuses of jobs that have terminated abnormally, see Glue Job Run Statuses.
    
    Parameters:
    
    jobRunState - The current state of the job run. For more information about the statuses of jobs that have terminated abnormally, see Glue Job Run Statuses.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
    
    See Also:
    
    JobRunState
  - withJobRunState
```
public JobRun withJobRunState(JobRunState jobRunState)
```
    The current state of the job run. For more information about the statuses of jobs that have terminated abnormally, see Glue Job Run Statuses.
    
    Parameters:
    
    jobRunState - The current state of the job run. For more information about the statuses of jobs that have terminated abnormally, see Glue Job Run Statuses.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
    
    See Also:
    
    JobRunState
  - getArguments
```
public Map<String,String> getArguments()
```
    The job arguments associated with this run. For this job run, they replace the default arguments set in the job definition itself.
    
    You can specify arguments here that your own job-execution script consumes, as well as arguments that Glue itself consumes.
    
    Job arguments may be logged. Do not pass plaintext secrets as arguments. Retrieve secrets from a Glue Connection, Secrets Manager or other secret management mechanism if you intend to keep them within the Job.
    
    For information about how to specify and consume your own Job arguments, see the Calling Glue APIs in Python topic in the developer guide.
    
    For information about the arguments you can provide to this field when configuring Spark jobs, see the Special Parameters Used by Glue topic in the developer guide.
    
    For information about the arguments you can provide to this field when configuring Ray jobs, see Using job parameters in Ray jobs in the developer guide.
    
    Returns:
    
    The job arguments associated with this run. For this job run, they replace the default arguments set in the job definition itself.
    
    You can specify arguments here that your own job-execution script consumes, as well as arguments that Glue itself consumes.
    
    Job arguments may be logged. Do not pass plaintext secrets as arguments. Retrieve secrets from a Glue Connection, Secrets Manager or other secret management mechanism if you intend to keep them within the Job.
    
    For information about how to specify and consume your own Job arguments, see the Calling Glue APIs in Python topic in the developer guide.
    
    For information about the arguments you can provide to this field when configuring Spark jobs, see the Special Parameters Used by Glue topic in the developer guide.
    
    For information about the arguments you can provide to this field when configuring Ray jobs, see Using job parameters in Ray jobs in the developer guide.
  - setArguments
```
public void setArguments(Map<String,String> arguments)
```
    The job arguments associated with this run. For this job run, they replace the default arguments set in the job definition itself.
    
    You can specify arguments here that your own job-execution script consumes, as well as arguments that Glue itself consumes.
    
    Job arguments may be logged. Do not pass plaintext secrets as arguments. Retrieve secrets from a Glue Connection, Secrets Manager or other secret management mechanism if you intend to keep them within the Job.
    
    For information about how to specify and consume your own Job arguments, see the Calling Glue APIs in Python topic in the developer guide.
    
    For information about the arguments you can provide to this field when configuring Spark jobs, see the Special Parameters Used by Glue topic in the developer guide.
    
    For information about the arguments you can provide to this field when configuring Ray jobs, see Using job parameters in Ray jobs in the developer guide.
    
    Parameters:
    
    arguments - The job arguments associated with this run. For this job run, they replace the default arguments set in the job definition itself.
    
    You can specify arguments here that your own job-execution script consumes, as well as arguments that Glue itself consumes.
    
    Job arguments may be logged. Do not pass plaintext secrets as arguments. Retrieve secrets from a Glue Connection, Secrets Manager or other secret management mechanism if you intend to keep them within the Job.
    
    For information about how to specify and consume your own Job arguments, see the Calling Glue APIs in Python topic in the developer guide.
    
    For information about the arguments you can provide to this field when configuring Spark jobs, see the Special Parameters Used by Glue topic in the developer guide.
    
    For information about the arguments you can provide to this field when configuring Ray jobs, see Using job parameters in Ray jobs in the developer guide.
  - withArguments
```
public JobRun withArguments(Map<String,String> arguments)
```
    The job arguments associated with this run. For this job run, they replace the default arguments set in the job definition itself.
    
    You can specify arguments here that your own job-execution script consumes, as well as arguments that Glue itself consumes.
    
    Job arguments may be logged. Do not pass plaintext secrets as arguments. Retrieve secrets from a Glue Connection, Secrets Manager or other secret management mechanism if you intend to keep them within the Job.
    
    For information about how to specify and consume your own Job arguments, see the Calling Glue APIs in Python topic in the developer guide.
    
    For information about the arguments you can provide to this field when configuring Spark jobs, see the Special Parameters Used by Glue topic in the developer guide.
    
    For information about the arguments you can provide to this field when configuring Ray jobs, see Using job parameters in Ray jobs in the developer guide.
    
    Parameters:
    
    arguments - The job arguments associated with this run. For this job run, they replace the default arguments set in the job definition itself.
    
    You can specify arguments here that your own job-execution script consumes, as well as arguments that Glue itself consumes.
    
    Job arguments may be logged. Do not pass plaintext secrets as arguments. Retrieve secrets from a Glue Connection, Secrets Manager or other secret management mechanism if you intend to keep them within the Job.
    
    For information about how to specify and consume your own Job arguments, see the Calling Glue APIs in Python topic in the developer guide.
    
    For information about the arguments you can provide to this field when configuring Spark jobs, see the Special Parameters Used by Glue topic in the developer guide.
    
    For information about the arguments you can provide to this field when configuring Ray jobs, see Using job parameters in Ray jobs in the developer guide.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - addArgumentsEntry
```
public JobRun addArgumentsEntry(String key,
                                String value)
```
    Add a single Arguments entry
    
    See Also:
    
    withArguments(java.util.Map<java.lang.String, java.lang.String>)
  - clearArgumentsEntries
```
public JobRun clearArgumentsEntries()
```
    Removes all the entries added into Arguments.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setErrorMessage
```
public void setErrorMessage(String errorMessage)
```
    An error message associated with this job run.
    
    Parameters:
    
    errorMessage - An error message associated with this job run.
  - getErrorMessage
```
public String getErrorMessage()
```
    An error message associated with this job run.
    
    Returns:
    
    An error message associated with this job run.
  - withErrorMessage
```
public JobRun withErrorMessage(String errorMessage)
```
    An error message associated with this job run.
    
    Parameters:
    
    errorMessage - An error message associated with this job run.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - getPredecessorRuns
```
public List<Predecessor> getPredecessorRuns()
```
    A list of predecessors to this job run.
    
    Returns:
    
    A list of predecessors to this job run.
  - setPredecessorRuns
```
public void setPredecessorRuns(Collection<Predecessor> predecessorRuns)
```
    A list of predecessors to this job run.
    
    Parameters:
    
    predecessorRuns - A list of predecessors to this job run.
  - withPredecessorRuns
```
public JobRun withPredecessorRuns(Predecessor... predecessorRuns)
```
    A list of predecessors to this job run.
    
    NOTE: This method appends the values to the existing list (if any). Use setPredecessorRuns(java.util.Collection) or withPredecessorRuns(java.util.Collection) if you want to override the existing values.
    
    Parameters:
    
    predecessorRuns - A list of predecessors to this job run.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - withPredecessorRuns
```
public JobRun withPredecessorRuns(Collection<Predecessor> predecessorRuns)
```
    A list of predecessors to this job run.
    
    Parameters:
    
    predecessorRuns - A list of predecessors to this job run.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setAllocatedCapacity
```
@Deprecated
public void setAllocatedCapacity(Integer allocatedCapacity)
```
    Deprecated.
    
    This field is deprecated. Use MaxCapacity instead.
    
    The number of Glue data processing units (DPUs) allocated to this JobRun. From 2 to 100 DPUs can be allocated; the default is 10. A DPU is a relative measure of processing power that consists of 4 vCPUs of compute capacity and 16 GB of memory. For more information, see the Glue pricing page.
    
    Parameters:
    
    allocatedCapacity - This field is deprecated. Use MaxCapacity instead.
    
    The number of Glue data processing units (DPUs) allocated to this JobRun. From 2 to 100 DPUs can be allocated; the default is 10. A DPU is a relative measure of processing power that consists of 4 vCPUs of compute capacity and 16 GB of memory. For more information, see the Glue pricing page.
  - getAllocatedCapacity
```
@Deprecated
public Integer getAllocatedCapacity()
```
    Deprecated.
    
    This field is deprecated. Use MaxCapacity instead.
    
    The number of Glue data processing units (DPUs) allocated to this JobRun. From 2 to 100 DPUs can be allocated; the default is 10. A DPU is a relative measure of processing power that consists of 4 vCPUs of compute capacity and 16 GB of memory. For more information, see the Glue pricing page.
    
    Returns:
    
    This field is deprecated. Use MaxCapacity instead.
    
    The number of Glue data processing units (DPUs) allocated to this JobRun. From 2 to 100 DPUs can be allocated; the default is 10. A DPU is a relative measure of processing power that consists of 4 vCPUs of compute capacity and 16 GB of memory. For more information, see the Glue pricing page.
  - withAllocatedCapacity
```
@Deprecated
public JobRun withAllocatedCapacity(Integer allocatedCapacity)
```
    Deprecated.
    
    This field is deprecated. Use MaxCapacity instead.
    
    The number of Glue data processing units (DPUs) allocated to this JobRun. From 2 to 100 DPUs can be allocated; the default is 10. A DPU is a relative measure of processing power that consists of 4 vCPUs of compute capacity and 16 GB of memory. For more information, see the Glue pricing page.
    
    Parameters:
    
    allocatedCapacity - This field is deprecated. Use MaxCapacity instead.
    
    The number of Glue data processing units (DPUs) allocated to this JobRun. From 2 to 100 DPUs can be allocated; the default is 10. A DPU is a relative measure of processing power that consists of 4 vCPUs of compute capacity and 16 GB of memory. For more information, see the Glue pricing page.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setExecutionTime
```
public void setExecutionTime(Integer executionTime)
```
    The amount of time (in seconds) that the job run consumed resources.
    
    Parameters:
    
    executionTime - The amount of time (in seconds) that the job run consumed resources.
  - getExecutionTime
```
public Integer getExecutionTime()
```
    The amount of time (in seconds) that the job run consumed resources.
    
    Returns:
    
    The amount of time (in seconds) that the job run consumed resources.
  - withExecutionTime
```
public JobRun withExecutionTime(Integer executionTime)
```
    The amount of time (in seconds) that the job run consumed resources.
    
    Parameters:
    
    executionTime - The amount of time (in seconds) that the job run consumed resources.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setTimeout
```
public void setTimeout(Integer timeout)
```
    The JobRun timeout in minutes. This is the maximum time that a job run can consume resources before it is terminated and enters TIMEOUT status. This value overrides the timeout value set in the parent job.
    
    Streaming jobs must have timeout values less than 7 days or 10080 minutes. When the value is left blank, the job will be restarted after 7 days based if you have not setup a maintenance window. If you have setup maintenance window, it will be restarted during the maintenance window after 7 days.
    
    Parameters:
    
    timeout - The JobRun timeout in minutes. This is the maximum time that a job run can consume resources before it is terminated and enters TIMEOUT status. This value overrides the timeout value set in the parent job.
    
    Streaming jobs must have timeout values less than 7 days or 10080 minutes. When the value is left blank, the job will be restarted after 7 days based if you have not setup a maintenance window. If you have setup maintenance window, it will be restarted during the maintenance window after 7 days.
  - getTimeout
```
public Integer getTimeout()
```
    The JobRun timeout in minutes. This is the maximum time that a job run can consume resources before it is terminated and enters TIMEOUT status. This value overrides the timeout value set in the parent job.
    
    Streaming jobs must have timeout values less than 7 days or 10080 minutes. When the value is left blank, the job will be restarted after 7 days based if you have not setup a maintenance window. If you have setup maintenance window, it will be restarted during the maintenance window after 7 days.
    
    Returns:
    
    The JobRun timeout in minutes. This is the maximum time that a job run can consume resources before it is terminated and enters TIMEOUT status. This value overrides the timeout value set in the parent job.
    
    Streaming jobs must have timeout values less than 7 days or 10080 minutes. When the value is left blank, the job will be restarted after 7 days based if you have not setup a maintenance window. If you have setup maintenance window, it will be restarted during the maintenance window after 7 days.
  - withTimeout
```
public JobRun withTimeout(Integer timeout)
```
    The JobRun timeout in minutes. This is the maximum time that a job run can consume resources before it is terminated and enters TIMEOUT status. This value overrides the timeout value set in the parent job.
    
    Streaming jobs must have timeout values less than 7 days or 10080 minutes. When the value is left blank, the job will be restarted after 7 days based if you have not setup a maintenance window. If you have setup maintenance window, it will be restarted during the maintenance window after 7 days.
    
    Parameters:
    
    timeout - The JobRun timeout in minutes. This is the maximum time that a job run can consume resources before it is terminated and enters TIMEOUT status. This value overrides the timeout value set in the parent job.
    
    Streaming jobs must have timeout values less than 7 days or 10080 minutes. When the value is left blank, the job will be restarted after 7 days based if you have not setup a maintenance window. If you have setup maintenance window, it will be restarted during the maintenance window after 7 days.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setMaxCapacity
```
public void setMaxCapacity(Double maxCapacity)
```
    For Glue version 1.0 or earlier jobs, using the standard worker type, the number of Glue data processing units (DPUs) that can be allocated when this job runs. A DPU is a relative measure of processing power that consists of 4 vCPUs of compute capacity and 16 GB of memory. For more information, see the Glue pricing page.
    
    For Glue version 2.0+ jobs, you cannot specify a Maximum capacity. Instead, you should specify a Worker type and the Number of workers.
    
    Do not set MaxCapacity if using WorkerType and NumberOfWorkers.
    
    The value that can be allocated for MaxCapacity depends on whether you are running a Python shell job, an Apache Spark ETL job, or an Apache Spark streaming ETL job:
    - When you specify a Python shell job (JobCommand.Name="pythonshell"), you can allocate either 0.0625 or 1 DPU. The default is 0.0625 DPU.
    - When you specify an Apache Spark ETL job (JobCommand.Name="glueetl") or Apache Spark streaming ETL job (JobCommand.Name="gluestreaming"), you can allocate from 2 to 100 DPUs. The default is 10 DPUs. This job type cannot have a fractional DPU allocation.
    Parameters:
    maxCapacity - For Glue version 1.0 or earlier jobs, using the standard worker type, the number of Glue data processing units (DPUs) that can be allocated when this job runs. A DPU is a relative measure of processing power that consists of 4 vCPUs of compute capacity and 16 GB of memory. For more information, see the Glue pricing page.
    
    For Glue version 2.0+ jobs, you cannot specify a Maximum capacity. Instead, you should specify a Worker type and the Number of workers.
    
    Do not set MaxCapacity if using WorkerType and NumberOfWorkers.
    
    The value that can be allocated for MaxCapacity depends on whether you are running a Python shell job, an Apache Spark ETL job, or an Apache Spark streaming ETL job:
    
    When you specify a Python shell job (JobCommand.Name="pythonshell"), you can allocate either 0.0625 or 1 DPU. The default is 0.0625 DPU.
    
    When you specify an Apache Spark ETL job (JobCommand.Name="glueetl") or Apache Spark streaming ETL job (JobCommand.Name="gluestreaming"), you can allocate from 2 to 100 DPUs. The default is 10 DPUs. This job type cannot have a fractional DPU allocation.
  - getMaxCapacity
```
public Double getMaxCapacity()
```
    For Glue version 1.0 or earlier jobs, using the standard worker type, the number of Glue data processing units (DPUs) that can be allocated when this job runs. A DPU is a relative measure of processing power that consists of 4 vCPUs of compute capacity and 16 GB of memory. For more information, see the Glue pricing page.
    
    For Glue version 2.0+ jobs, you cannot specify a Maximum capacity. Instead, you should specify a Worker type and the Number of workers.
    
    Do not set MaxCapacity if using WorkerType and NumberOfWorkers.
    
    The value that can be allocated for MaxCapacity depends on whether you are running a Python shell job, an Apache Spark ETL job, or an Apache Spark streaming ETL job:
    - When you specify a Python shell job (JobCommand.Name="pythonshell"), you can allocate either 0.0625 or 1 DPU. The default is 0.0625 DPU.
    - When you specify an Apache Spark ETL job (JobCommand.Name="glueetl") or Apache Spark streaming ETL job (JobCommand.Name="gluestreaming"), you can allocate from 2 to 100 DPUs. The default is 10 DPUs. This job type cannot have a fractional DPU allocation.
    Returns:
    For Glue version 1.0 or earlier jobs, using the standard worker type, the number of Glue data processing units (DPUs) that can be allocated when this job runs. A DPU is a relative measure of processing power that consists of 4 vCPUs of compute capacity and 16 GB of memory. For more information, see the Glue pricing page.
    
    For Glue version 2.0+ jobs, you cannot specify a Maximum capacity. Instead, you should specify a Worker type and the Number of workers.
    
    Do not set MaxCapacity if using WorkerType and NumberOfWorkers.
    
    The value that can be allocated for MaxCapacity depends on whether you are running a Python shell job, an Apache Spark ETL job, or an Apache Spark streaming ETL job:
    
    When you specify a Python shell job (JobCommand.Name="pythonshell"), you can allocate either 0.0625 or 1 DPU. The default is 0.0625 DPU.
    
    When you specify an Apache Spark ETL job (JobCommand.Name="glueetl") or Apache Spark streaming ETL job (JobCommand.Name="gluestreaming"), you can allocate from 2 to 100 DPUs. The default is 10 DPUs. This job type cannot have a fractional DPU allocation.
  - withMaxCapacity
```
public JobRun withMaxCapacity(Double maxCapacity)
```
    For Glue version 1.0 or earlier jobs, using the standard worker type, the number of Glue data processing units (DPUs) that can be allocated when this job runs. A DPU is a relative measure of processing power that consists of 4 vCPUs of compute capacity and 16 GB of memory. For more information, see the Glue pricing page.
    
    For Glue version 2.0+ jobs, you cannot specify a Maximum capacity. Instead, you should specify a Worker type and the Number of workers.
    
    Do not set MaxCapacity if using WorkerType and NumberOfWorkers.
    
    The value that can be allocated for MaxCapacity depends on whether you are running a Python shell job, an Apache Spark ETL job, or an Apache Spark streaming ETL job:
    - When you specify a Python shell job (JobCommand.Name="pythonshell"), you can allocate either 0.0625 or 1 DPU. The default is 0.0625 DPU.
    - When you specify an Apache Spark ETL job (JobCommand.Name="glueetl") or Apache Spark streaming ETL job (JobCommand.Name="gluestreaming"), you can allocate from 2 to 100 DPUs. The default is 10 DPUs. This job type cannot have a fractional DPU allocation.
    Parameters:
    maxCapacity - For Glue version 1.0 or earlier jobs, using the standard worker type, the number of Glue data processing units (DPUs) that can be allocated when this job runs. A DPU is a relative measure of processing power that consists of 4 vCPUs of compute capacity and 16 GB of memory. For more information, see the Glue pricing page.
    
    For Glue version 2.0+ jobs, you cannot specify a Maximum capacity. Instead, you should specify a Worker type and the Number of workers.
    
    Do not set MaxCapacity if using WorkerType and NumberOfWorkers.
    
    The value that can be allocated for MaxCapacity depends on whether you are running a Python shell job, an Apache Spark ETL job, or an Apache Spark streaming ETL job:
    
    When you specify a Python shell job (JobCommand.Name="pythonshell"), you can allocate either 0.0625 or 1 DPU. The default is 0.0625 DPU.
    
    When you specify an Apache Spark ETL job (JobCommand.Name="glueetl") or Apache Spark streaming ETL job (JobCommand.Name="gluestreaming"), you can allocate from 2 to 100 DPUs. The default is 10 DPUs. This job type cannot have a fractional DPU allocation.
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setWorkerType
```
public void setWorkerType(String workerType)
```
    The type of predefined worker that is allocated when a job runs. Accepts a value of G.1X, G.2X, G.4X, G.8X or G.025X for Spark jobs. Accepts the value Z.2X for Ray jobs.
    - For the G.1X worker type, each worker maps to 1 DPU (4 vCPUs, 16 GB of memory) with 84GB disk (approximately 34GB free), and provides 1 executor per worker. We recommend this worker type for workloads such as data transforms, joins, and queries, to offers a scalable and cost effective way to run most jobs.
    - For the G.2X worker type, each worker maps to 2 DPU (8 vCPUs, 32 GB of memory) with 128GB disk (approximately 77GB free), and provides 1 executor per worker. We recommend this worker type for workloads such as data transforms, joins, and queries, to offers a scalable and cost effective way to run most jobs.
    - For the G.4X worker type, each worker maps to 4 DPU (16 vCPUs, 64 GB of memory) with 256GB disk (approximately 235GB free), and provides 1 executor per worker. We recommend this worker type for jobs whose workloads contain your most demanding transforms, aggregations, joins, and queries. This worker type is available only for Glue version 3.0 or later Spark ETL jobs in the following Amazon Web Services Regions: US East (Ohio), US East (N. Virginia), US West (Oregon), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Tokyo), Canada (Central), Europe (Frankfurt), Europe (Ireland), and Europe (Stockholm).
    - For the G.8X worker type, each worker maps to 8 DPU (32 vCPUs, 128 GB of memory) with 512GB disk (approximately 487GB free), and provides 1 executor per worker. We recommend this worker type for jobs whose workloads contain your most demanding transforms, aggregations, joins, and queries. This worker type is available only for Glue version 3.0 or later Spark ETL jobs, in the same Amazon Web Services Regions as supported for the G.4X worker type.
    - For the G.025X worker type, each worker maps to 0.25 DPU (2 vCPUs, 4 GB of memory) with 84GB disk (approximately 34GB free), and provides 1 executor per worker. We recommend this worker type for low volume streaming jobs. This worker type is only available for Glue version 3.0 streaming jobs.
    - For the Z.2X worker type, each worker maps to 2 M-DPU (8vCPUs, 64 GB of memory) with 128 GB disk (approximately 120GB free), and provides up to 8 Ray workers based on the autoscaler.
    Parameters:
    workerType - The type of predefined worker that is allocated when a job runs. Accepts a value of G.1X, G.2X, G.4X, G.8X or G.025X for Spark jobs. Accepts the value Z.2X for Ray jobs.
    
    For the G.1X worker type, each worker maps to 1 DPU (4 vCPUs, 16 GB of memory) with 84GB disk (approximately 34GB free), and provides 1 executor per worker. We recommend this worker type for workloads such as data transforms, joins, and queries, to offers a scalable and cost effective way to run most jobs.
    
    For the G.2X worker type, each worker maps to 2 DPU (8 vCPUs, 32 GB of memory) with 128GB disk (approximately 77GB free), and provides 1 executor per worker. We recommend this worker type for workloads such as data transforms, joins, and queries, to offers a scalable and cost effective way to run most jobs.
    
    For the G.4X worker type, each worker maps to 4 DPU (16 vCPUs, 64 GB of memory) with 256GB disk (approximately 235GB free), and provides 1 executor per worker. We recommend this worker type for jobs whose workloads contain your most demanding transforms, aggregations, joins, and queries. This worker type is available only for Glue version 3.0 or later Spark ETL jobs in the following Amazon Web Services Regions: US East (Ohio), US East (N. Virginia), US West (Oregon), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Tokyo), Canada (Central), Europe (Frankfurt), Europe (Ireland), and Europe (Stockholm).
    
    For the G.8X worker type, each worker maps to 8 DPU (32 vCPUs, 128 GB of memory) with 512GB disk (approximately 487GB free), and provides 1 executor per worker. We recommend this worker type for jobs whose workloads contain your most demanding transforms, aggregations, joins, and queries. This worker type is available only for Glue version 3.0 or later Spark ETL jobs, in the same Amazon Web Services Regions as supported for the G.4X worker type.
    
    For the G.025X worker type, each worker maps to 0.25 DPU (2 vCPUs, 4 GB of memory) with 84GB disk (approximately 34GB free), and provides 1 executor per worker. We recommend this worker type for low volume streaming jobs. This worker type is only available for Glue version 3.0 streaming jobs.
    
    For the Z.2X worker type, each worker maps to 2 M-DPU (8vCPUs, 64 GB of memory) with 128 GB disk (approximately 120GB free), and provides up to 8 Ray workers based on the autoscaler.
    See Also:
    
    WorkerType
  - getWorkerType
```
public String getWorkerType()
```
    The type of predefined worker that is allocated when a job runs. Accepts a value of G.1X, G.2X, G.4X, G.8X or G.025X for Spark jobs. Accepts the value Z.2X for Ray jobs.
    - For the G.1X worker type, each worker maps to 1 DPU (4 vCPUs, 16 GB of memory) with 84GB disk (approximately 34GB free), and provides 1 executor per worker. We recommend this worker type for workloads such as data transforms, joins, and queries, to offers a scalable and cost effective way to run most jobs.
    - For the G.2X worker type, each worker maps to 2 DPU (8 vCPUs, 32 GB of memory) with 128GB disk (approximately 77GB free), and provides 1 executor per worker. We recommend this worker type for workloads such as data transforms, joins, and queries, to offers a scalable and cost effective way to run most jobs.
    - For the G.4X worker type, each worker maps to 4 DPU (16 vCPUs, 64 GB of memory) with 256GB disk (approximately 235GB free), and provides 1 executor per worker. We recommend this worker type for jobs whose workloads contain your most demanding transforms, aggregations, joins, and queries. This worker type is available only for Glue version 3.0 or later Spark ETL jobs in the following Amazon Web Services Regions: US East (Ohio), US East (N. Virginia), US West (Oregon), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Tokyo), Canada (Central), Europe (Frankfurt), Europe (Ireland), and Europe (Stockholm).
    - For the G.8X worker type, each worker maps to 8 DPU (32 vCPUs, 128 GB of memory) with 512GB disk (approximately 487GB free), and provides 1 executor per worker. We recommend this worker type for jobs whose workloads contain your most demanding transforms, aggregations, joins, and queries. This worker type is available only for Glue version 3.0 or later Spark ETL jobs, in the same Amazon Web Services Regions as supported for the G.4X worker type.
    - For the G.025X worker type, each worker maps to 0.25 DPU (2 vCPUs, 4 GB of memory) with 84GB disk (approximately 34GB free), and provides 1 executor per worker. We recommend this worker type for low volume streaming jobs. This worker type is only available for Glue version 3.0 streaming jobs.
    - For the Z.2X worker type, each worker maps to 2 M-DPU (8vCPUs, 64 GB of memory) with 128 GB disk (approximately 120GB free), and provides up to 8 Ray workers based on the autoscaler.
    Returns:
    The type of predefined worker that is allocated when a job runs. Accepts a value of G.1X, G.2X, G.4X, G.8X or G.025X for Spark jobs. Accepts the value Z.2X for Ray jobs.
    
    For the G.1X worker type, each worker maps to 1 DPU (4 vCPUs, 16 GB of memory) with 84GB disk (approximately 34GB free), and provides 1 executor per worker. We recommend this worker type for workloads such as data transforms, joins, and queries, to offers a scalable and cost effective way to run most jobs.
    
    For the G.2X worker type, each worker maps to 2 DPU (8 vCPUs, 32 GB of memory) with 128GB disk (approximately 77GB free), and provides 1 executor per worker. We recommend this worker type for workloads such as data transforms, joins, and queries, to offers a scalable and cost effective way to run most jobs.
    
    For the G.4X worker type, each worker maps to 4 DPU (16 vCPUs, 64 GB of memory) with 256GB disk (approximately 235GB free), and provides 1 executor per worker. We recommend this worker type for jobs whose workloads contain your most demanding transforms, aggregations, joins, and queries. This worker type is available only for Glue version 3.0 or later Spark ETL jobs in the following Amazon Web Services Regions: US East (Ohio), US East (N. Virginia), US West (Oregon), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Tokyo), Canada (Central), Europe (Frankfurt), Europe (Ireland), and Europe (Stockholm).
    
    For the G.8X worker type, each worker maps to 8 DPU (32 vCPUs, 128 GB of memory) with 512GB disk (approximately 487GB free), and provides 1 executor per worker. We recommend this worker type for jobs whose workloads contain your most demanding transforms, aggregations, joins, and queries. This worker type is available only for Glue version 3.0 or later Spark ETL jobs, in the same Amazon Web Services Regions as supported for the G.4X worker type.
    
    For the G.025X worker type, each worker maps to 0.25 DPU (2 vCPUs, 4 GB of memory) with 84GB disk (approximately 34GB free), and provides 1 executor per worker. We recommend this worker type for low volume streaming jobs. This worker type is only available for Glue version 3.0 streaming jobs.
    
    For the Z.2X worker type, each worker maps to 2 M-DPU (8vCPUs, 64 GB of memory) with 128 GB disk (approximately 120GB free), and provides up to 8 Ray workers based on the autoscaler.
    See Also:
    
    WorkerType
  - withWorkerType
```
public JobRun withWorkerType(String workerType)
```
    The type of predefined worker that is allocated when a job runs. Accepts a value of G.1X, G.2X, G.4X, G.8X or G.025X for Spark jobs. Accepts the value Z.2X for Ray jobs.
    - For the G.1X worker type, each worker maps to 1 DPU (4 vCPUs, 16 GB of memory) with 84GB disk (approximately 34GB free), and provides 1 executor per worker. We recommend this worker type for workloads such as data transforms, joins, and queries, to offers a scalable and cost effective way to run most jobs.
    - For the G.2X worker type, each worker maps to 2 DPU (8 vCPUs, 32 GB of memory) with 128GB disk (approximately 77GB free), and provides 1 executor per worker. We recommend this worker type for workloads such as data transforms, joins, and queries, to offers a scalable and cost effective way to run most jobs.
    - For the G.4X worker type, each worker maps to 4 DPU (16 vCPUs, 64 GB of memory) with 256GB disk (approximately 235GB free), and provides 1 executor per worker. We recommend this worker type for jobs whose workloads contain your most demanding transforms, aggregations, joins, and queries. This worker type is available only for Glue version 3.0 or later Spark ETL jobs in the following Amazon Web Services Regions: US East (Ohio), US East (N. Virginia), US West (Oregon), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Tokyo), Canada (Central), Europe (Frankfurt), Europe (Ireland), and Europe (Stockholm).
    - For the G.8X worker type, each worker maps to 8 DPU (32 vCPUs, 128 GB of memory) with 512GB disk (approximately 487GB free), and provides 1 executor per worker. We recommend this worker type for jobs whose workloads contain your most demanding transforms, aggregations, joins, and queries. This worker type is available only for Glue version 3.0 or later Spark ETL jobs, in the same Amazon Web Services Regions as supported for the G.4X worker type.
    - For the G.025X worker type, each worker maps to 0.25 DPU (2 vCPUs, 4 GB of memory) with 84GB disk (approximately 34GB free), and provides 1 executor per worker. We recommend this worker type for low volume streaming jobs. This worker type is only available for Glue version 3.0 streaming jobs.
    - For the Z.2X worker type, each worker maps to 2 M-DPU (8vCPUs, 64 GB of memory) with 128 GB disk (approximately 120GB free), and provides up to 8 Ray workers based on the autoscaler.
    Parameters:
    workerType - The type of predefined worker that is allocated when a job runs. Accepts a value of G.1X, G.2X, G.4X, G.8X or G.025X for Spark jobs. Accepts the value Z.2X for Ray jobs.
    
    For the G.1X worker type, each worker maps to 1 DPU (4 vCPUs, 16 GB of memory) with 84GB disk (approximately 34GB free), and provides 1 executor per worker. We recommend this worker type for workloads such as data transforms, joins, and queries, to offers a scalable and cost effective way to run most jobs.
    
    For the G.2X worker type, each worker maps to 2 DPU (8 vCPUs, 32 GB of memory) with 128GB disk (approximately 77GB free), and provides 1 executor per worker. We recommend this worker type for workloads such as data transforms, joins, and queries, to offers a scalable and cost effective way to run most jobs.
    
    For the G.4X worker type, each worker maps to 4 DPU (16 vCPUs, 64 GB of memory) with 256GB disk (approximately 235GB free), and provides 1 executor per worker. We recommend this worker type for jobs whose workloads contain your most demanding transforms, aggregations, joins, and queries. This worker type is available only for Glue version 3.0 or later Spark ETL jobs in the following Amazon Web Services Regions: US East (Ohio), US East (N. Virginia), US West (Oregon), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Tokyo), Canada (Central), Europe (Frankfurt), Europe (Ireland), and Europe (Stockholm).
    
    For the G.8X worker type, each worker maps to 8 DPU (32 vCPUs, 128 GB of memory) with 512GB disk (approximately 487GB free), and provides 1 executor per worker. We recommend this worker type for jobs whose workloads contain your most demanding transforms, aggregations, joins, and queries. This worker type is available only for Glue version 3.0 or later Spark ETL jobs, in the same Amazon Web Services Regions as supported for the G.4X worker type.
    
    For the G.025X worker type, each worker maps to 0.25 DPU (2 vCPUs, 4 GB of memory) with 84GB disk (approximately 34GB free), and provides 1 executor per worker. We recommend this worker type for low volume streaming jobs. This worker type is only available for Glue version 3.0 streaming jobs.
    
    For the Z.2X worker type, each worker maps to 2 M-DPU (8vCPUs, 64 GB of memory) with 128 GB disk (approximately 120GB free), and provides up to 8 Ray workers based on the autoscaler.
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
    
    See Also:
    
    WorkerType
  - withWorkerType
```
public JobRun withWorkerType(WorkerType workerType)
```
    The type of predefined worker that is allocated when a job runs. Accepts a value of G.1X, G.2X, G.4X, G.8X or G.025X for Spark jobs. Accepts the value Z.2X for Ray jobs.
    - For the G.1X worker type, each worker maps to 1 DPU (4 vCPUs, 16 GB of memory) with 84GB disk (approximately 34GB free), and provides 1 executor per worker. We recommend this worker type for workloads such as data transforms, joins, and queries, to offers a scalable and cost effective way to run most jobs.
    - For the G.2X worker type, each worker maps to 2 DPU (8 vCPUs, 32 GB of memory) with 128GB disk (approximately 77GB free), and provides 1 executor per worker. We recommend this worker type for workloads such as data transforms, joins, and queries, to offers a scalable and cost effective way to run most jobs.
    - For the G.4X worker type, each worker maps to 4 DPU (16 vCPUs, 64 GB of memory) with 256GB disk (approximately 235GB free), and provides 1 executor per worker. We recommend this worker type for jobs whose workloads contain your most demanding transforms, aggregations, joins, and queries. This worker type is available only for Glue version 3.0 or later Spark ETL jobs in the following Amazon Web Services Regions: US East (Ohio), US East (N. Virginia), US West (Oregon), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Tokyo), Canada (Central), Europe (Frankfurt), Europe (Ireland), and Europe (Stockholm).
    - For the G.8X worker type, each worker maps to 8 DPU (32 vCPUs, 128 GB of memory) with 512GB disk (approximately 487GB free), and provides 1 executor per worker. We recommend this worker type for jobs whose workloads contain your most demanding transforms, aggregations, joins, and queries. This worker type is available only for Glue version 3.0 or later Spark ETL jobs, in the same Amazon Web Services Regions as supported for the G.4X worker type.
    - For the G.025X worker type, each worker maps to 0.25 DPU (2 vCPUs, 4 GB of memory) with 84GB disk (approximately 34GB free), and provides 1 executor per worker. We recommend this worker type for low volume streaming jobs. This worker type is only available for Glue version 3.0 streaming jobs.
    - For the Z.2X worker type, each worker maps to 2 M-DPU (8vCPUs, 64 GB of memory) with 128 GB disk (approximately 120GB free), and provides up to 8 Ray workers based on the autoscaler.
    Parameters:
    workerType - The type of predefined worker that is allocated when a job runs. Accepts a value of G.1X, G.2X, G.4X, G.8X or G.025X for Spark jobs. Accepts the value Z.2X for Ray jobs.
    
    For the G.1X worker type, each worker maps to 1 DPU (4 vCPUs, 16 GB of memory) with 84GB disk (approximately 34GB free), and provides 1 executor per worker. We recommend this worker type for workloads such as data transforms, joins, and queries, to offers a scalable and cost effective way to run most jobs.
    
    For the G.2X worker type, each worker maps to 2 DPU (8 vCPUs, 32 GB of memory) with 128GB disk (approximately 77GB free), and provides 1 executor per worker. We recommend this worker type for workloads such as data transforms, joins, and queries, to offers a scalable and cost effective way to run most jobs.
    
    For the G.4X worker type, each worker maps to 4 DPU (16 vCPUs, 64 GB of memory) with 256GB disk (approximately 235GB free), and provides 1 executor per worker. We recommend this worker type for jobs whose workloads contain your most demanding transforms, aggregations, joins, and queries. This worker type is available only for Glue version 3.0 or later Spark ETL jobs in the following Amazon Web Services Regions: US East (Ohio), US East (N. Virginia), US West (Oregon), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Tokyo), Canada (Central), Europe (Frankfurt), Europe (Ireland), and Europe (Stockholm).
    
    For the G.8X worker type, each worker maps to 8 DPU (32 vCPUs, 128 GB of memory) with 512GB disk (approximately 487GB free), and provides 1 executor per worker. We recommend this worker type for jobs whose workloads contain your most demanding transforms, aggregations, joins, and queries. This worker type is available only for Glue version 3.0 or later Spark ETL jobs, in the same Amazon Web Services Regions as supported for the G.4X worker type.
    
    For the G.025X worker type, each worker maps to 0.25 DPU (2 vCPUs, 4 GB of memory) with 84GB disk (approximately 34GB free), and provides 1 executor per worker. We recommend this worker type for low volume streaming jobs. This worker type is only available for Glue version 3.0 streaming jobs.
    
    For the Z.2X worker type, each worker maps to 2 M-DPU (8vCPUs, 64 GB of memory) with 128 GB disk (approximately 120GB free), and provides up to 8 Ray workers based on the autoscaler.
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
    
    See Also:
    
    WorkerType
  - setNumberOfWorkers
```
public void setNumberOfWorkers(Integer numberOfWorkers)
```
    The number of workers of a defined workerType that are allocated when a job runs.
    
    Parameters:
    
    numberOfWorkers - The number of workers of a defined workerType that are allocated when a job runs.
  - getNumberOfWorkers
```
public Integer getNumberOfWorkers()
```
    The number of workers of a defined workerType that are allocated when a job runs.
    
    Returns:
    
    The number of workers of a defined workerType that are allocated when a job runs.
  - withNumberOfWorkers
```
public JobRun withNumberOfWorkers(Integer numberOfWorkers)
```
    The number of workers of a defined workerType that are allocated when a job runs.
    
    Parameters:
    
    numberOfWorkers - The number of workers of a defined workerType that are allocated when a job runs.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setSecurityConfiguration
```
public void setSecurityConfiguration(String securityConfiguration)
```
    The name of the SecurityConfiguration structure to be used with this job run.
    
    Parameters:
    
    securityConfiguration - The name of the SecurityConfiguration structure to be used with this job run.
  - getSecurityConfiguration
```
public String getSecurityConfiguration()
```
    The name of the SecurityConfiguration structure to be used with this job run.
    
    Returns:
    
    The name of the SecurityConfiguration structure to be used with this job run.
  - withSecurityConfiguration
```
public JobRun withSecurityConfiguration(String securityConfiguration)
```
    The name of the SecurityConfiguration structure to be used with this job run.
    
    Parameters:
    
    securityConfiguration - The name of the SecurityConfiguration structure to be used with this job run.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setLogGroupName
```
public void setLogGroupName(String logGroupName)
```
    The name of the log group for secure logging that can be server-side encrypted in Amazon CloudWatch using KMS. This name can be /aws-glue/jobs/, in which case the default encryption is NONE. If you add a role name and SecurityConfiguration name (in other words, /aws-glue/jobs-yourRoleName-yourSecurityConfigurationName/), then that security configuration is used to encrypt the log group.
    
    Parameters:
    
    logGroupName - The name of the log group for secure logging that can be server-side encrypted in Amazon CloudWatch using KMS. This name can be /aws-glue/jobs/, in which case the default encryption is NONE. If you add a role name and SecurityConfiguration name (in other words, /aws-glue/jobs-yourRoleName-yourSecurityConfigurationName/), then that security configuration is used to encrypt the log group.
  - getLogGroupName
```
public String getLogGroupName()
```
    The name of the log group for secure logging that can be server-side encrypted in Amazon CloudWatch using KMS. This name can be /aws-glue/jobs/, in which case the default encryption is NONE. If you add a role name and SecurityConfiguration name (in other words, /aws-glue/jobs-yourRoleName-yourSecurityConfigurationName/), then that security configuration is used to encrypt the log group.
    
    Returns:
    
    The name of the log group for secure logging that can be server-side encrypted in Amazon CloudWatch using KMS. This name can be /aws-glue/jobs/, in which case the default encryption is NONE. If you add a role name and SecurityConfiguration name (in other words, /aws-glue/jobs-yourRoleName-yourSecurityConfigurationName/), then that security configuration is used to encrypt the log group.
  - withLogGroupName
```
public JobRun withLogGroupName(String logGroupName)
```
    The name of the log group for secure logging that can be server-side encrypted in Amazon CloudWatch using KMS. This name can be /aws-glue/jobs/, in which case the default encryption is NONE. If you add a role name and SecurityConfiguration name (in other words, /aws-glue/jobs-yourRoleName-yourSecurityConfigurationName/), then that security configuration is used to encrypt the log group.
    
    Parameters:
    
    logGroupName - The name of the log group for secure logging that can be server-side encrypted in Amazon CloudWatch using KMS. This name can be /aws-glue/jobs/, in which case the default encryption is NONE. If you add a role name and SecurityConfiguration name (in other words, /aws-glue/jobs-yourRoleName-yourSecurityConfigurationName/), then that security configuration is used to encrypt the log group.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setNotificationProperty
```
public void setNotificationProperty(NotificationProperty notificationProperty)
```
    Specifies configuration properties of a job run notification.
    
    Parameters:
    
    notificationProperty - Specifies configuration properties of a job run notification.
  - getNotificationProperty
```
public NotificationProperty getNotificationProperty()
```
    Specifies configuration properties of a job run notification.
    
    Returns:
    
    Specifies configuration properties of a job run notification.
  - withNotificationProperty
```
public JobRun withNotificationProperty(NotificationProperty notificationProperty)
```
    Specifies configuration properties of a job run notification.
    
    Parameters:
    
    notificationProperty - Specifies configuration properties of a job run notification.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setGlueVersion
```
public void setGlueVersion(String glueVersion)
```
    In Spark jobs, GlueVersion determines the versions of Apache Spark and Python that Glue available in a job. The Python version indicates the version supported for jobs of type Spark.
    
    Ray jobs should set GlueVersion to 4.0 or greater. However, the versions of Ray, Python and additional libraries available in your Ray job are determined by the Runtime parameter of the Job command.
    
    For more information about the available Glue versions and corresponding Spark and Python versions, see Glue version in the developer guide.
    
    Jobs that are created without specifying a Glue version default to Glue 0.9.
    
    Parameters:
    
    glueVersion - In Spark jobs, GlueVersion determines the versions of Apache Spark and Python that Glue available in a job. The Python version indicates the version supported for jobs of type Spark.
    
    Ray jobs should set GlueVersion to 4.0 or greater. However, the versions of Ray, Python and additional libraries available in your Ray job are determined by the Runtime parameter of the Job command.
    
    For more information about the available Glue versions and corresponding Spark and Python versions, see Glue version in the developer guide.
    
    Jobs that are created without specifying a Glue version default to Glue 0.9.
  - getGlueVersion
```
public String getGlueVersion()
```
    In Spark jobs, GlueVersion determines the versions of Apache Spark and Python that Glue available in a job. The Python version indicates the version supported for jobs of type Spark.
    
    Ray jobs should set GlueVersion to 4.0 or greater. However, the versions of Ray, Python and additional libraries available in your Ray job are determined by the Runtime parameter of the Job command.
    
    For more information about the available Glue versions and corresponding Spark and Python versions, see Glue version in the developer guide.
    
    Jobs that are created without specifying a Glue version default to Glue 0.9.
    
    Returns:
    
    In Spark jobs, GlueVersion determines the versions of Apache Spark and Python that Glue available in a job. The Python version indicates the version supported for jobs of type Spark.
    
    Ray jobs should set GlueVersion to 4.0 or greater. However, the versions of Ray, Python and additional libraries available in your Ray job are determined by the Runtime parameter of the Job command.
    
    For more information about the available Glue versions and corresponding Spark and Python versions, see Glue version in the developer guide.
    
    Jobs that are created without specifying a Glue version default to Glue 0.9.
  - withGlueVersion
```
public JobRun withGlueVersion(String glueVersion)
```
    In Spark jobs, GlueVersion determines the versions of Apache Spark and Python that Glue available in a job. The Python version indicates the version supported for jobs of type Spark.
    
    Ray jobs should set GlueVersion to 4.0 or greater. However, the versions of Ray, Python and additional libraries available in your Ray job are determined by the Runtime parameter of the Job command.
    
    For more information about the available Glue versions and corresponding Spark and Python versions, see Glue version in the developer guide.
    
    Jobs that are created without specifying a Glue version default to Glue 0.9.
    
    Parameters:
    
    glueVersion - In Spark jobs, GlueVersion determines the versions of Apache Spark and Python that Glue available in a job. The Python version indicates the version supported for jobs of type Spark.
    
    Ray jobs should set GlueVersion to 4.0 or greater. However, the versions of Ray, Python and additional libraries available in your Ray job are determined by the Runtime parameter of the Job command.
    
    For more information about the available Glue versions and corresponding Spark and Python versions, see Glue version in the developer guide.
    
    Jobs that are created without specifying a Glue version default to Glue 0.9.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setDPUSeconds
```
public void setDPUSeconds(Double dPUSeconds)
```
    This field can be set for either job runs with execution class FLEX or when Auto Scaling is enabled, and represents the total time each executor ran during the lifecycle of a job run in seconds, multiplied by a DPU factor (1 for G.1X, 2 for G.2X, or 0.25 for G.025X workers). This value may be different than the executionEngineRuntime * MaxCapacity as in the case of Auto Scaling jobs, as the number of executors running at a given time may be less than the MaxCapacity. Therefore, it is possible that the value of DPUSeconds is less than executionEngineRuntime * MaxCapacity.
    
    Parameters:
    
    dPUSeconds - This field can be set for either job runs with execution class FLEX or when Auto Scaling is enabled, and represents the total time each executor ran during the lifecycle of a job run in seconds, multiplied by a DPU factor (1 for G.1X, 2 for G.2X, or 0.25 for G.025X workers). This value may be different than the executionEngineRuntime * MaxCapacity as in the case of Auto Scaling jobs, as the number of executors running at a given time may be less than the MaxCapacity. Therefore, it is possible that the value of DPUSeconds is less than executionEngineRuntime MaxCapacity.
  - getDPUSeconds
```
public Double getDPUSeconds()
```
    This field can be set for either job runs with execution class FLEX or when Auto Scaling is enabled, and represents the total time each executor ran during the lifecycle of a job run in seconds, multiplied by a DPU factor (1 for G.1X, 2 for G.2X, or 0.25 for G.025X workers). This value may be different than the executionEngineRuntime * MaxCapacity as in the case of Auto Scaling jobs, as the number of executors running at a given time may be less than the MaxCapacity. Therefore, it is possible that the value of DPUSeconds is less than executionEngineRuntime * MaxCapacity.
    
    Returns:
    
    This field can be set for either job runs with execution class FLEX or when Auto Scaling is enabled, and represents the total time each executor ran during the lifecycle of a job run in seconds, multiplied by a DPU factor (1 for G.1X, 2 for G.2X, or 0.25 for G.025X workers). This value may be different than the executionEngineRuntime * MaxCapacity as in the case of Auto Scaling jobs, as the number of executors running at a given time may be less than the MaxCapacity. Therefore, it is possible that the value of DPUSeconds is less than executionEngineRuntime MaxCapacity.
  - withDPUSeconds
```
public JobRun withDPUSeconds(Double dPUSeconds)
```
    This field can be set for either job runs with execution class FLEX or when Auto Scaling is enabled, and represents the total time each executor ran during the lifecycle of a job run in seconds, multiplied by a DPU factor (1 for G.1X, 2 for G.2X, or 0.25 for G.025X workers). This value may be different than the executionEngineRuntime * MaxCapacity as in the case of Auto Scaling jobs, as the number of executors running at a given time may be less than the MaxCapacity. Therefore, it is possible that the value of DPUSeconds is less than executionEngineRuntime * MaxCapacity.
    
    Parameters:
    
    dPUSeconds - This field can be set for either job runs with execution class FLEX or when Auto Scaling is enabled, and represents the total time each executor ran during the lifecycle of a job run in seconds, multiplied by a DPU factor (1 for G.1X, 2 for G.2X, or 0.25 for G.025X workers). This value may be different than the executionEngineRuntime * MaxCapacity as in the case of Auto Scaling jobs, as the number of executors running at a given time may be less than the MaxCapacity. Therefore, it is possible that the value of DPUSeconds is less than executionEngineRuntime MaxCapacity.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setExecutionClass
```
public void setExecutionClass(String executionClass)
```
    Indicates whether the job is run with a standard or flexible execution class. The standard execution-class is ideal for time-sensitive workloads that require fast job startup and dedicated resources.
    
    The flexible execution class is appropriate for time-insensitive jobs whose start and completion times may vary.
    
    Only jobs with Glue version 3.0 and above and command type glueetl will be allowed to set ExecutionClass to FLEX. The flexible execution class is available for Spark jobs.
    
    Parameters:
    
    executionClass - Indicates whether the job is run with a standard or flexible execution class. The standard execution-class is ideal for time-sensitive workloads that require fast job startup and dedicated resources.
    
    The flexible execution class is appropriate for time-insensitive jobs whose start and completion times may vary.
    
    Only jobs with Glue version 3.0 and above and command type glueetl will be allowed to set ExecutionClass to FLEX. The flexible execution class is available for Spark jobs.
    
    See Also:
    
    ExecutionClass
  - getExecutionClass
```
public String getExecutionClass()
```
    Indicates whether the job is run with a standard or flexible execution class. The standard execution-class is ideal for time-sensitive workloads that require fast job startup and dedicated resources.
    
    The flexible execution class is appropriate for time-insensitive jobs whose start and completion times may vary.
    
    Only jobs with Glue version 3.0 and above and command type glueetl will be allowed to set ExecutionClass to FLEX. The flexible execution class is available for Spark jobs.
    
    Returns:
    
    Indicates whether the job is run with a standard or flexible execution class. The standard execution-class is ideal for time-sensitive workloads that require fast job startup and dedicated resources.
    
    The flexible execution class is appropriate for time-insensitive jobs whose start and completion times may vary.
    
    Only jobs with Glue version 3.0 and above and command type glueetl will be allowed to set ExecutionClass to FLEX. The flexible execution class is available for Spark jobs.
    
    See Also:
    
    ExecutionClass
  - withExecutionClass
```
public JobRun withExecutionClass(String executionClass)
```
    Indicates whether the job is run with a standard or flexible execution class. The standard execution-class is ideal for time-sensitive workloads that require fast job startup and dedicated resources.
    
    The flexible execution class is appropriate for time-insensitive jobs whose start and completion times may vary.
    
    Only jobs with Glue version 3.0 and above and command type glueetl will be allowed to set ExecutionClass to FLEX. The flexible execution class is available for Spark jobs.
    
    Parameters:
    
    executionClass - Indicates whether the job is run with a standard or flexible execution class. The standard execution-class is ideal for time-sensitive workloads that require fast job startup and dedicated resources.
    
    The flexible execution class is appropriate for time-insensitive jobs whose start and completion times may vary.
    
    Only jobs with Glue version 3.0 and above and command type glueetl will be allowed to set ExecutionClass to FLEX. The flexible execution class is available for Spark jobs.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
    
    See Also:
    
    ExecutionClass
  - withExecutionClass
```
public JobRun withExecutionClass(ExecutionClass executionClass)
```
    Indicates whether the job is run with a standard or flexible execution class. The standard execution-class is ideal for time-sensitive workloads that require fast job startup and dedicated resources.
    
    The flexible execution class is appropriate for time-insensitive jobs whose start and completion times may vary.
    
    Only jobs with Glue version 3.0 and above and command type glueetl will be allowed to set ExecutionClass to FLEX. The flexible execution class is available for Spark jobs.
    
    Parameters:
    
    executionClass - Indicates whether the job is run with a standard or flexible execution class. The standard execution-class is ideal for time-sensitive workloads that require fast job startup and dedicated resources.
    
    The flexible execution class is appropriate for time-insensitive jobs whose start and completion times may vary.
    
    Only jobs with Glue version 3.0 and above and command type glueetl will be allowed to set ExecutionClass to FLEX. The flexible execution class is available for Spark jobs.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
    
    See Also:
    
    ExecutionClass
  - setMaintenanceWindow
```
public void setMaintenanceWindow(String maintenanceWindow)
```
    This field specifies a day of the week and hour for a maintenance window for streaming jobs. Glue periodically performs maintenance activities. During these maintenance windows, Glue will need to restart your streaming jobs.
    
    Glue will restart the job within 3 hours of the specified maintenance window. For instance, if you set up the maintenance window for Monday at 10:00AM GMT, your jobs will be restarted between 10:00AM GMT to 1:00PM GMT.
    
    Parameters:
    
    maintenanceWindow - This field specifies a day of the week and hour for a maintenance window for streaming jobs. Glue periodically performs maintenance activities. During these maintenance windows, Glue will need to restart your streaming jobs.
    
    Glue will restart the job within 3 hours of the specified maintenance window. For instance, if you set up the maintenance window for Monday at 10:00AM GMT, your jobs will be restarted between 10:00AM GMT to 1:00PM GMT.
  - getMaintenanceWindow
```
public String getMaintenanceWindow()
```
    This field specifies a day of the week and hour for a maintenance window for streaming jobs. Glue periodically performs maintenance activities. During these maintenance windows, Glue will need to restart your streaming jobs.
    
    Glue will restart the job within 3 hours of the specified maintenance window. For instance, if you set up the maintenance window for Monday at 10:00AM GMT, your jobs will be restarted between 10:00AM GMT to 1:00PM GMT.
    
    Returns:
    
    This field specifies a day of the week and hour for a maintenance window for streaming jobs. Glue periodically performs maintenance activities. During these maintenance windows, Glue will need to restart your streaming jobs.
    
    Glue will restart the job within 3 hours of the specified maintenance window. For instance, if you set up the maintenance window for Monday at 10:00AM GMT, your jobs will be restarted between 10:00AM GMT to 1:00PM GMT.
  - withMaintenanceWindow
```
public JobRun withMaintenanceWindow(String maintenanceWindow)
```
    This field specifies a day of the week and hour for a maintenance window for streaming jobs. Glue periodically performs maintenance activities. During these maintenance windows, Glue will need to restart your streaming jobs.
    
    Glue will restart the job within 3 hours of the specified maintenance window. For instance, if you set up the maintenance window for Monday at 10:00AM GMT, your jobs will be restarted between 10:00AM GMT to 1:00PM GMT.
    
    Parameters:
    
    maintenanceWindow - This field specifies a day of the week and hour for a maintenance window for streaming jobs. Glue periodically performs maintenance activities. During these maintenance windows, Glue will need to restart your streaming jobs.
    
    Glue will restart the job within 3 hours of the specified maintenance window. For instance, if you set up the maintenance window for Monday at 10:00AM GMT, your jobs will be restarted between 10:00AM GMT to 1:00PM GMT.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setProfileName
```
public void setProfileName(String profileName)
```
    The name of an Glue usage profile associated with the job run.
    
    Parameters:
    
    profileName - The name of an Glue usage profile associated with the job run.
  - getProfileName
```
public String getProfileName()
```
    The name of an Glue usage profile associated with the job run.
    
    Returns:
    
    The name of an Glue usage profile associated with the job run.
  - withProfileName
```
public JobRun withProfileName(String profileName)
```
    The name of an Glue usage profile associated with the job run.
    
    Parameters:
    
    profileName - The name of an Glue usage profile associated with the job run.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - toString
```
public String toString()
```
    Returns a string representation of this object. This is useful for testing and debugging. Sensitive data will be redacted from this string using a placeholder value.
    
    Overrides:
    
    toString in class Object
    
    Returns:
    
    A string representation of this object.
    
    See Also:
    
    Object.toString()
  - equals
```
public boolean equals(Object obj)
```
    Overrides:
    
    equals in class Object
  - hashCode
```
public int hashCode()
```
    Overrides:
    
    hashCode in class Object
  - clone
```
public JobRun clone()
```
    Overrides:
    
    clone in class Object
  - marshall
```
public void marshall(ProtocolMarshaller protocolMarshaller)
```
    Description copied from interface: StructuredPojo
    
    Marshalls this structured data using the given ProtocolMarshaller.
    
    Specified by:
    
    marshall in interface StructuredPojo
    
    Parameters:
    
    protocolMarshaller - Implementation of ProtocolMarshaller used to marshall this object's data.

AWS SDK for Java 1.x API Reference - 1.12.778

Class JobRun

Constructor Summary

Method Summary

Methods inherited from class java.lang.Object

Constructor Detail

JobRun

Method Detail

setId

getId

withId

setAttempt

getAttempt

withAttempt

setPreviousRunId

getPreviousRunId

withPreviousRunId

setTriggerName

getTriggerName

withTriggerName

setJobName

getJobName

withJobName

setJobMode

getJobMode

withJobMode

withJobMode

setStartedOn

getStartedOn

withStartedOn

setLastModifiedOn

getLastModifiedOn

withLastModifiedOn

setCompletedOn

getCompletedOn

withCompletedOn

setJobRunState

getJobRunState

withJobRunState

withJobRunState

getArguments

setArguments

withArguments

addArgumentsEntry

clearArgumentsEntries

setErrorMessage

getErrorMessage

withErrorMessage

getPredecessorRuns

setPredecessorRuns

withPredecessorRuns

withPredecessorRuns

setAllocatedCapacity

getAllocatedCapacity

withAllocatedCapacity

setExecutionTime

getExecutionTime

withExecutionTime

setTimeout

getTimeout

withTimeout

setMaxCapacity

getMaxCapacity

withMaxCapacity

setWorkerType

getWorkerType

withWorkerType

withWorkerType

setNumberOfWorkers

getNumberOfWorkers

withNumberOfWorkers

setSecurityConfiguration

getSecurityConfiguration

withSecurityConfiguration

setLogGroupName

getLogGroupName

withLogGroupName

setNotificationProperty

getNotificationProperty

withNotificationProperty