CreateJobRequest (AWS SDK for Java

java.lang.Object
- com.amazonaws.AmazonWebServiceRequest
- - com.amazonaws.services.glue.model.CreateJobRequest

All Implemented Interfaces:: HandlerContextAware, ReadLimitInfo, Serializable, Cloneable

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

See Also:: AWS API Documentation, Serialized Form

Field Summary
- Fields inherited from class com.amazonaws.AmazonWebServiceRequest
  NOOP

Constructor Summary

Constructors
Constructor and Description

CreateJobRequest()

Constructors
Constructor and Description
`CreateJobRequest()`

Method Summary

All Methods Instance Methods Concrete Methods Deprecated Methods
Modifier and Type	Method and Description
`CreateJobRequest`	`addCodeGenConfigurationNodesEntry(String key, CodeGenConfigurationNode value)` Add a single CodeGenConfigurationNodes entry
`CreateJobRequest`	`addDefaultArgumentsEntry(String key, String value)` Add a single DefaultArguments entry
`CreateJobRequest`	`addNonOverridableArgumentsEntry(String key, String value)` Add a single NonOverridableArguments entry
`CreateJobRequest`	`addTagsEntry(String key, String value)` Add a single Tags entry
`CreateJobRequest`	`clearCodeGenConfigurationNodesEntries()` Removes all the entries added into CodeGenConfigurationNodes.
`CreateJobRequest`	`clearDefaultArgumentsEntries()` Removes all the entries added into DefaultArguments.
`CreateJobRequest`	`clearNonOverridableArgumentsEntries()` Removes all the entries added into NonOverridableArguments.
`CreateJobRequest`	`clearTagsEntries()` Removes all the entries added into Tags.
`CreateJobRequest`	`clone()` Creates a shallow clone of this object for all fields except the handler context.
`boolean`	`equals(Object obj)`
`Integer`	`getAllocatedCapacity()` Deprecated.
`Map<String,CodeGenConfigurationNode>`	`getCodeGenConfigurationNodes()` The representation of a directed acyclic graph on which both the Glue Studio visual component and Glue Studio code generation is based.
`JobCommand`	`getCommand()` The `JobCommand` that runs this job.
`ConnectionsList`	`getConnections()` The connections used for this job.
`Map<String,String>`	`getDefaultArguments()` The default arguments for every run of this job, specified as name-value pairs.
`String`	`getDescription()` Description of the job being defined.
`String`	`getExecutionClass()` Indicates whether the job is run with a standard or flexible execution class.
`ExecutionProperty`	`getExecutionProperty()` An `ExecutionProperty` specifying the maximum number of concurrent runs allowed for this job.
`String`	`getGlueVersion()` In Spark jobs, `GlueVersion` determines the versions of Apache Spark and Python that Glue available in a job.
`String`	`getLogUri()` This field is reserved for future use.
`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.
`Integer`	`getMaxRetries()` The maximum number of times to retry this job if it fails.
`String`	`getName()` The name you assign to this job definition.
`Map<String,String>`	`getNonOverridableArguments()` Arguments for this job that are not overridden when providing job arguments in a job run, specified as name-value pairs.
`NotificationProperty`	`getNotificationProperty()` Specifies configuration properties of a job notification.
`Integer`	`getNumberOfWorkers()` The number of workers of a defined `workerType` that are allocated when a job runs.
`String`	`getRole()` The name or Amazon Resource Name (ARN) of the IAM role associated with this job.
`String`	`getSecurityConfiguration()` The name of the `SecurityConfiguration` structure to be used with this job.
`SourceControlDetails`	`getSourceControlDetails()` The details for a source control configuration for a job, allowing synchronization of job artifacts to or from a remote repository.
`Map<String,String>`	`getTags()` The tags to use with this job.
`Integer`	`getTimeout()` The job timeout in minutes.
`String`	`getWorkerType()` The type of predefined worker that is allocated when a job runs.
`int`	`hashCode()`
`void`	`setAllocatedCapacity(Integer allocatedCapacity)` Deprecated.
`void`	`setCodeGenConfigurationNodes(Map<String,CodeGenConfigurationNode> codeGenConfigurationNodes)` The representation of a directed acyclic graph on which both the Glue Studio visual component and Glue Studio code generation is based.
`void`	`setCommand(JobCommand command)` The `JobCommand` that runs this job.
`void`	`setConnections(ConnectionsList connections)` The connections used for this job.
`void`	`setDefaultArguments(Map<String,String> defaultArguments)` The default arguments for every run of this job, specified as name-value pairs.
`void`	`setDescription(String description)` Description of the job being defined.
`void`	`setExecutionClass(String executionClass)` Indicates whether the job is run with a standard or flexible execution class.
`void`	`setExecutionProperty(ExecutionProperty executionProperty)` An `ExecutionProperty` specifying the maximum number of concurrent runs allowed for this job.
`void`	`setGlueVersion(String glueVersion)` In Spark jobs, `GlueVersion` determines the versions of Apache Spark and Python that Glue available in a job.
`void`	`setLogUri(String logUri)` This field is reserved for future use.
`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`	`setMaxRetries(Integer maxRetries)` The maximum number of times to retry this job if it fails.
`void`	`setName(String name)` The name you assign to this job definition.
`void`	`setNonOverridableArguments(Map<String,String> nonOverridableArguments)` Arguments for this job that are not overridden when providing job arguments in a job run, specified as name-value pairs.
`void`	`setNotificationProperty(NotificationProperty notificationProperty)` Specifies configuration properties of a job notification.
`void`	`setNumberOfWorkers(Integer numberOfWorkers)` The number of workers of a defined `workerType` that are allocated when a job runs.
`void`	`setRole(String role)` The name or Amazon Resource Name (ARN) of the IAM role associated with this job.
`void`	`setSecurityConfiguration(String securityConfiguration)` The name of the `SecurityConfiguration` structure to be used with this job.
`void`	`setSourceControlDetails(SourceControlDetails sourceControlDetails)` The details for a source control configuration for a job, allowing synchronization of job artifacts to or from a remote repository.
`void`	`setTags(Map<String,String> tags)` The tags to use with this job.
`void`	`setTimeout(Integer timeout)` The job timeout in minutes.
`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.
`CreateJobRequest`	`withAllocatedCapacity(Integer allocatedCapacity)` Deprecated.
`CreateJobRequest`	`withCodeGenConfigurationNodes(Map<String,CodeGenConfigurationNode> codeGenConfigurationNodes)` The representation of a directed acyclic graph on which both the Glue Studio visual component and Glue Studio code generation is based.
`CreateJobRequest`	`withCommand(JobCommand command)` The `JobCommand` that runs this job.
`CreateJobRequest`	`withConnections(ConnectionsList connections)` The connections used for this job.
`CreateJobRequest`	`withDefaultArguments(Map<String,String> defaultArguments)` The default arguments for every run of this job, specified as name-value pairs.
`CreateJobRequest`	`withDescription(String description)` Description of the job being defined.
`CreateJobRequest`	`withExecutionClass(ExecutionClass executionClass)` Indicates whether the job is run with a standard or flexible execution class.
`CreateJobRequest`	`withExecutionClass(String executionClass)` Indicates whether the job is run with a standard or flexible execution class.
`CreateJobRequest`	`withExecutionProperty(ExecutionProperty executionProperty)` An `ExecutionProperty` specifying the maximum number of concurrent runs allowed for this job.
`CreateJobRequest`	`withGlueVersion(String glueVersion)` In Spark jobs, `GlueVersion` determines the versions of Apache Spark and Python that Glue available in a job.
`CreateJobRequest`	`withLogUri(String logUri)` This field is reserved for future use.
`CreateJobRequest`	`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.
`CreateJobRequest`	`withMaxRetries(Integer maxRetries)` The maximum number of times to retry this job if it fails.
`CreateJobRequest`	`withName(String name)` The name you assign to this job definition.
`CreateJobRequest`	`withNonOverridableArguments(Map<String,String> nonOverridableArguments)` Arguments for this job that are not overridden when providing job arguments in a job run, specified as name-value pairs.
`CreateJobRequest`	`withNotificationProperty(NotificationProperty notificationProperty)` Specifies configuration properties of a job notification.
`CreateJobRequest`	`withNumberOfWorkers(Integer numberOfWorkers)` The number of workers of a defined `workerType` that are allocated when a job runs.
`CreateJobRequest`	`withRole(String role)` The name or Amazon Resource Name (ARN) of the IAM role associated with this job.
`CreateJobRequest`	`withSecurityConfiguration(String securityConfiguration)` The name of the `SecurityConfiguration` structure to be used with this job.
`CreateJobRequest`	`withSourceControlDetails(SourceControlDetails sourceControlDetails)` The details for a source control configuration for a job, allowing synchronization of job artifacts to or from a remote repository.
`CreateJobRequest`	`withTags(Map<String,String> tags)` The tags to use with this job.
`CreateJobRequest`	`withTimeout(Integer timeout)` The job timeout in minutes.
`CreateJobRequest`	`withWorkerType(String workerType)` The type of predefined worker that is allocated when a job runs.
`CreateJobRequest`	`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
  - CreateJobRequest
```
public CreateJobRequest()
```
- Method Detail
  - setName
```
public void setName(String name)
```
    The name you assign to this job definition. It must be unique in your account.
    
    Parameters:
    
    name - The name you assign to this job definition. It must be unique in your account.
  - getName
```
public String getName()
```
    The name you assign to this job definition. It must be unique in your account.
    
    Returns:
    
    The name you assign to this job definition. It must be unique in your account.
  - withName
```
public CreateJobRequest withName(String name)
```
    The name you assign to this job definition. It must be unique in your account.
    
    Parameters:
    
    name - The name you assign to this job definition. It must be unique in your account.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setDescription
```
public void setDescription(String description)
```
    Description of the job being defined.
    
    Parameters:
    
    description - Description of the job being defined.
  - getDescription
```
public String getDescription()
```
    Description of the job being defined.
    
    Returns:
    
    Description of the job being defined.
  - withDescription
```
public CreateJobRequest withDescription(String description)
```
    Description of the job being defined.
    
    Parameters:
    
    description - Description of the job being defined.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setLogUri
```
public void setLogUri(String logUri)
```
    This field is reserved for future use.
    
    Parameters:
    
    logUri - This field is reserved for future use.
  - getLogUri
```
public String getLogUri()
```
    This field is reserved for future use.
    
    Returns:
    
    This field is reserved for future use.
  - withLogUri
```
public CreateJobRequest withLogUri(String logUri)
```
    This field is reserved for future use.
    
    Parameters:
    
    logUri - This field is reserved for future use.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setRole
```
public void setRole(String role)
```
    The name or Amazon Resource Name (ARN) of the IAM role associated with this job.
    
    Parameters:
    
    role - The name or Amazon Resource Name (ARN) of the IAM role associated with this job.
  - getRole
```
public String getRole()
```
    The name or Amazon Resource Name (ARN) of the IAM role associated with this job.
    
    Returns:
    
    The name or Amazon Resource Name (ARN) of the IAM role associated with this job.
  - withRole
```
public CreateJobRequest withRole(String role)
```
    The name or Amazon Resource Name (ARN) of the IAM role associated with this job.
    
    Parameters:
    
    role - The name or Amazon Resource Name (ARN) of the IAM role associated with this job.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setExecutionProperty
```
public void setExecutionProperty(ExecutionProperty executionProperty)
```
    An ExecutionProperty specifying the maximum number of concurrent runs allowed for this job.
    
    Parameters:
    
    executionProperty - An ExecutionProperty specifying the maximum number of concurrent runs allowed for this job.
  - getExecutionProperty
```
public ExecutionProperty getExecutionProperty()
```
    An ExecutionProperty specifying the maximum number of concurrent runs allowed for this job.
    
    Returns:
    
    An ExecutionProperty specifying the maximum number of concurrent runs allowed for this job.
  - withExecutionProperty
```
public CreateJobRequest withExecutionProperty(ExecutionProperty executionProperty)
```
    An ExecutionProperty specifying the maximum number of concurrent runs allowed for this job.
    
    Parameters:
    
    executionProperty - An ExecutionProperty specifying the maximum number of concurrent runs allowed for this job.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setCommand
```
public void setCommand(JobCommand command)
```
    The JobCommand that runs this job.
    
    Parameters:
    
    command - The JobCommand that runs this job.
  - getCommand
```
public JobCommand getCommand()
```
    The JobCommand that runs this job.
    
    Returns:
    
    The JobCommand that runs this job.
  - withCommand
```
public CreateJobRequest withCommand(JobCommand command)
```
    The JobCommand that runs this job.
    
    Parameters:
    
    command - The JobCommand that runs this job.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - getDefaultArguments
```
public Map<String,String> getDefaultArguments()
```
    The default arguments for every run of this job, specified as name-value pairs.
    
    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 default arguments for every run of this job, specified as name-value pairs.
    
    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.
  - setDefaultArguments
```
public void setDefaultArguments(Map<String,String> defaultArguments)
```
    The default arguments for every run of this job, specified as name-value pairs.
    
    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:
    
    defaultArguments - The default arguments for every run of this job, specified as name-value pairs.
    
    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.
  - withDefaultArguments
```
public CreateJobRequest withDefaultArguments(Map<String,String> defaultArguments)
```
    The default arguments for every run of this job, specified as name-value pairs.
    
    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:
    
    defaultArguments - The default arguments for every run of this job, specified as name-value pairs.
    
    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.
  - addDefaultArgumentsEntry
```
public CreateJobRequest addDefaultArgumentsEntry(String key,
                                                 String value)
```
    Add a single DefaultArguments entry
    
    See Also:
    
    withDefaultArguments(java.util.Map<java.lang.String, java.lang.String>)
  - clearDefaultArgumentsEntries
```
public CreateJobRequest clearDefaultArgumentsEntries()
```
    Removes all the entries added into DefaultArguments.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - getNonOverridableArguments
```
public Map<String,String> getNonOverridableArguments()
```
    Arguments for this job that are not overridden when providing job arguments in a job run, specified as name-value pairs.
    
    Returns:
    
    Arguments for this job that are not overridden when providing job arguments in a job run, specified as name-value pairs.
  - setNonOverridableArguments
```
public void setNonOverridableArguments(Map<String,String> nonOverridableArguments)
```
    Arguments for this job that are not overridden when providing job arguments in a job run, specified as name-value pairs.
    
    Parameters:
    
    nonOverridableArguments - Arguments for this job that are not overridden when providing job arguments in a job run, specified as name-value pairs.
  - withNonOverridableArguments
```
public CreateJobRequest withNonOverridableArguments(Map<String,String> nonOverridableArguments)
```
    Arguments for this job that are not overridden when providing job arguments in a job run, specified as name-value pairs.
    
    Parameters:
    
    nonOverridableArguments - Arguments for this job that are not overridden when providing job arguments in a job run, specified as name-value pairs.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - addNonOverridableArgumentsEntry
```
public CreateJobRequest addNonOverridableArgumentsEntry(String key,
                                                        String value)
```
    Add a single NonOverridableArguments entry
    
    See Also:
    
    withNonOverridableArguments(java.util.Map<java.lang.String, java.lang.String>)
  - clearNonOverridableArgumentsEntries
```
public CreateJobRequest clearNonOverridableArgumentsEntries()
```
    Removes all the entries added into NonOverridableArguments.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setConnections
```
public void setConnections(ConnectionsList connections)
```
    The connections used for this job.
    
    Parameters:
    
    connections - The connections used for this job.
  - getConnections
```
public ConnectionsList getConnections()
```
    The connections used for this job.
    
    Returns:
    
    The connections used for this job.
  - withConnections
```
public CreateJobRequest withConnections(ConnectionsList connections)
```
    The connections used for this job.
    
    Parameters:
    
    connections - The connections used for this job.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setMaxRetries
```
public void setMaxRetries(Integer maxRetries)
```
    The maximum number of times to retry this job if it fails.
    
    Parameters:
    
    maxRetries - The maximum number of times to retry this job if it fails.
  - getMaxRetries
```
public Integer getMaxRetries()
```
    The maximum number of times to retry this job if it fails.
    
    Returns:
    
    The maximum number of times to retry this job if it fails.
  - withMaxRetries
```
public CreateJobRequest withMaxRetries(Integer maxRetries)
```
    The maximum number of times to retry this job if it fails.
    
    Parameters:
    
    maxRetries - The maximum number of times to retry this job if it fails.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - setAllocatedCapacity
```
@Deprecated
public void setAllocatedCapacity(Integer allocatedCapacity)
```
    Deprecated.
    
    This parameter is deprecated. Use MaxCapacity instead.
    
    The number of Glue data processing units (DPUs) to allocate to this Job. You can allocate a minimum of 2 DPUs; 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 parameter is deprecated. Use MaxCapacity instead.
    
    The number of Glue data processing units (DPUs) to allocate to this Job. You can allocate a minimum of 2 DPUs; 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 parameter is deprecated. Use MaxCapacity instead.
    
    The number of Glue data processing units (DPUs) to allocate to this Job. You can allocate a minimum of 2 DPUs; 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 parameter is deprecated. Use MaxCapacity instead.
    
    The number of Glue data processing units (DPUs) to allocate to this Job. You can allocate a minimum of 2 DPUs; 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 CreateJobRequest withAllocatedCapacity(Integer allocatedCapacity)
```
    Deprecated.
    
    This parameter is deprecated. Use MaxCapacity instead.
    
    The number of Glue data processing units (DPUs) to allocate to this Job. You can allocate a minimum of 2 DPUs; 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 parameter is deprecated. Use MaxCapacity instead.
    
    The number of Glue data processing units (DPUs) to allocate to this Job. You can allocate a minimum of 2 DPUs; 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.
  - setTimeout
```
public void setTimeout(Integer timeout)
```
    The job timeout in minutes. This is the maximum time that a job run can consume resources before it is terminated and enters TIMEOUT status. The default is 2,880 minutes (48 hours).
    
    Parameters:
    
    timeout - The job timeout in minutes. This is the maximum time that a job run can consume resources before it is terminated and enters TIMEOUT status. The default is 2,880 minutes (48 hours).
  - getTimeout
```
public Integer getTimeout()
```
    The job timeout in minutes. This is the maximum time that a job run can consume resources before it is terminated and enters TIMEOUT status. The default is 2,880 minutes (48 hours).
    
    Returns:
    
    The job timeout in minutes. This is the maximum time that a job run can consume resources before it is terminated and enters TIMEOUT status. The default is 2,880 minutes (48 hours).
  - withTimeout
```
public CreateJobRequest withTimeout(Integer timeout)
```
    The job timeout in minutes. This is the maximum time that a job run can consume resources before it is terminated and enters TIMEOUT status. The default is 2,880 minutes (48 hours).
    
    Parameters:
    
    timeout - The job timeout in minutes. This is the maximum time that a job run can consume resources before it is terminated and enters TIMEOUT status. The default is 2,880 minutes (48 hours).
    
    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 CreateJobRequest 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.
  - setSecurityConfiguration
```
public void setSecurityConfiguration(String securityConfiguration)
```
    The name of the SecurityConfiguration structure to be used with this job.
    
    Parameters:
    
    securityConfiguration - The name of the SecurityConfiguration structure to be used with this job.
  - getSecurityConfiguration
```
public String getSecurityConfiguration()
```
    The name of the SecurityConfiguration structure to be used with this job.
    
    Returns:
    
    The name of the SecurityConfiguration structure to be used with this job.
  - withSecurityConfiguration
```
public CreateJobRequest withSecurityConfiguration(String securityConfiguration)
```
    The name of the SecurityConfiguration structure to be used with this job.
    
    Parameters:
    
    securityConfiguration - The name of the SecurityConfiguration structure to be used with this job.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - getTags
```
public Map<String,String> getTags()
```
    The tags to use with this job. You may use tags to limit access to the job. For more information about tags in Glue, see Amazon Web Services Tags in Glue in the developer guide.
    
    Returns:
    
    The tags to use with this job. You may use tags to limit access to the job. For more information about tags in Glue, see Amazon Web Services Tags in Glue in the developer guide.
  - setTags
```
public void setTags(Map<String,String> tags)
```
    The tags to use with this job. You may use tags to limit access to the job. For more information about tags in Glue, see Amazon Web Services Tags in Glue in the developer guide.
    
    Parameters:
    
    tags - The tags to use with this job. You may use tags to limit access to the job. For more information about tags in Glue, see Amazon Web Services Tags in Glue in the developer guide.
  - withTags
```
public CreateJobRequest withTags(Map<String,String> tags)
```
    The tags to use with this job. You may use tags to limit access to the job. For more information about tags in Glue, see Amazon Web Services Tags in Glue in the developer guide.
    
    Parameters:
    
    tags - The tags to use with this job. You may use tags to limit access to the job. For more information about tags in Glue, see Amazon Web Services Tags in Glue in the developer guide.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - addTagsEntry
```
public CreateJobRequest addTagsEntry(String key,
                                     String value)
```
    Add a single Tags entry
    
    See Also:
    
    withTags(java.util.Map<java.lang.String, java.lang.String>)
  - clearTagsEntries
```
public CreateJobRequest clearTagsEntries()
```
    Removes all the entries added into Tags.
    
    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 notification.
    
    Parameters:
    
    notificationProperty - Specifies configuration properties of a job notification.
  - getNotificationProperty
```
public NotificationProperty getNotificationProperty()
```
    Specifies configuration properties of a job notification.
    
    Returns:
    
    Specifies configuration properties of a job notification.
  - withNotificationProperty
```
public CreateJobRequest withNotificationProperty(NotificationProperty notificationProperty)
```
    Specifies configuration properties of a job notification.
    
    Parameters:
    
    notificationProperty - Specifies configuration properties of a job 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 CreateJobRequest 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.
  - 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 CreateJobRequest 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.
  - 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 CreateJobRequest 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 CreateJobRequest 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
  - getCodeGenConfigurationNodes
```
public Map<String,CodeGenConfigurationNode> getCodeGenConfigurationNodes()
```
    The representation of a directed acyclic graph on which both the Glue Studio visual component and Glue Studio code generation is based.
    
    Returns:
    
    The representation of a directed acyclic graph on which both the Glue Studio visual component and Glue Studio code generation is based.
  - setCodeGenConfigurationNodes
```
public void setCodeGenConfigurationNodes(Map<String,CodeGenConfigurationNode> codeGenConfigurationNodes)
```
    The representation of a directed acyclic graph on which both the Glue Studio visual component and Glue Studio code generation is based.
    
    Parameters:
    
    codeGenConfigurationNodes - The representation of a directed acyclic graph on which both the Glue Studio visual component and Glue Studio code generation is based.
  - withCodeGenConfigurationNodes
```
public CreateJobRequest withCodeGenConfigurationNodes(Map<String,CodeGenConfigurationNode> codeGenConfigurationNodes)
```
    The representation of a directed acyclic graph on which both the Glue Studio visual component and Glue Studio code generation is based.
    
    Parameters:
    
    codeGenConfigurationNodes - The representation of a directed acyclic graph on which both the Glue Studio visual component and Glue Studio code generation is based.
    
    Returns:
    
    Returns a reference to this object so that method calls can be chained together.
  - addCodeGenConfigurationNodesEntry
```
public CreateJobRequest addCodeGenConfigurationNodesEntry(String key,
                                                          CodeGenConfigurationNode value)
```
    Add a single CodeGenConfigurationNodes entry
    
    See Also:
    
    withCodeGenConfigurationNodes(java.util.Map<java.lang.String, com.amazonaws.services.glue.model.CodeGenConfigurationNode>)
  - clearCodeGenConfigurationNodesEntries
```
public CreateJobRequest clearCodeGenConfigurationNodesEntries()
```
    Removes all the entries added into CodeGenConfigurationNodes.
    
    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 CreateJobRequest 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 CreateJobRequest 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
  - setSourceControlDetails
```
public void setSourceControlDetails(SourceControlDetails sourceControlDetails)
```
    The details for a source control configuration for a job, allowing synchronization of job artifacts to or from a remote repository.
    
    Parameters:
    
    sourceControlDetails - The details for a source control configuration for a job, allowing synchronization of job artifacts to or from a remote repository.
  - getSourceControlDetails
```
public SourceControlDetails getSourceControlDetails()
```
    The details for a source control configuration for a job, allowing synchronization of job artifacts to or from a remote repository.
    
    Returns:
    
    The details for a source control configuration for a job, allowing synchronization of job artifacts to or from a remote repository.
  - withSourceControlDetails
```
public CreateJobRequest withSourceControlDetails(SourceControlDetails sourceControlDetails)
```
    The details for a source control configuration for a job, allowing synchronization of job artifacts to or from a remote repository.
    
    Parameters:
    
    sourceControlDetails - The details for a source control configuration for a job, allowing synchronization of job artifacts to or from a remote repository.
    
    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 CreateJobRequest clone()
```
    Description copied from class: AmazonWebServiceRequest
    
    Creates a shallow clone of this object for all fields except the handler context. Explicitly does not clone the deep structure of the other fields in the message.
    
    Overrides:
    
    clone in class AmazonWebServiceRequest
    
    See Also:
    
    Object.clone()

AWS SDK for Java 1.x API Reference - 1.12.560

Class CreateJobRequest

Field Summary

Fields inherited from class com.amazonaws.AmazonWebServiceRequest

Constructor Summary

Method Summary

Methods inherited from class com.amazonaws.AmazonWebServiceRequest

Methods inherited from class java.lang.Object

Constructor Detail

CreateJobRequest

Method Detail

setName

getName

withName

setDescription

getDescription

withDescription

setLogUri

getLogUri

withLogUri

setRole

getRole

withRole

setExecutionProperty

getExecutionProperty

withExecutionProperty

setCommand

getCommand

withCommand

getDefaultArguments

setDefaultArguments

withDefaultArguments

addDefaultArgumentsEntry

clearDefaultArgumentsEntries

getNonOverridableArguments

setNonOverridableArguments

withNonOverridableArguments

addNonOverridableArgumentsEntry

clearNonOverridableArgumentsEntries

setConnections

getConnections

withConnections

setMaxRetries

getMaxRetries

withMaxRetries

setAllocatedCapacity

getAllocatedCapacity

withAllocatedCapacity

setTimeout

getTimeout

withTimeout

setMaxCapacity

getMaxCapacity

withMaxCapacity

setSecurityConfiguration

getSecurityConfiguration

withSecurityConfiguration

getTags

setTags

withTags

addTagsEntry

clearTagsEntries

setNotificationProperty

getNotificationProperty

withNotificationProperty

setGlueVersion

getGlueVersion

withGlueVersion

setNumberOfWorkers

getNumberOfWorkers

withNumberOfWorkers

setWorkerType

getWorkerType

withWorkerType

withWorkerType

getCodeGenConfigurationNodes

setCodeGenConfigurationNodes

withCodeGenConfigurationNodes

addCodeGenConfigurationNodesEntry

clearCodeGenConfigurationNodesEntries