@Generated(value="com.amazonaws:aws-java-sdk-code-generator") public class JobRun extends Object implements Serializable, Cloneable, StructuredPojo
Contains information about a job run.
Constructor and Description |
---|
JobRun() |
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 populates only for Auto Scaling job runs, 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 |
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.
|
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 |
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) |
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 populates only for Auto Scaling job runs, 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 |
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 |
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 |
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 populates only for Auto Scaling job runs, 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 |
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 |
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 |
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.
|
public void setId(String id)
The ID of this job run.
id
- The ID of this job run.public String getId()
The ID of this job run.
public JobRun withId(String id)
The ID of this job run.
id
- The ID of this job run.public void setAttempt(Integer attempt)
The number of the attempt to run this job.
attempt
- The number of the attempt to run this job.public Integer getAttempt()
The number of the attempt to run this job.
public JobRun withAttempt(Integer attempt)
The number of the attempt to run this job.
attempt
- The number of the attempt to run this job.public void setPreviousRunId(String previousRunId)
The ID of the previous run of this job. For example, the JobRunId
specified in the
StartJobRun
action.
previousRunId
- The ID of the previous run of this job. For example, the JobRunId
specified in the
StartJobRun
action.public String getPreviousRunId()
The ID of the previous run of this job. For example, the JobRunId
specified in the
StartJobRun
action.
JobRunId
specified in the
StartJobRun
action.public JobRun withPreviousRunId(String previousRunId)
The ID of the previous run of this job. For example, the JobRunId
specified in the
StartJobRun
action.
previousRunId
- The ID of the previous run of this job. For example, the JobRunId
specified in the
StartJobRun
action.public void setTriggerName(String triggerName)
The name of the trigger that started this job run.
triggerName
- The name of the trigger that started this job run.public String getTriggerName()
The name of the trigger that started this job run.
public JobRun withTriggerName(String triggerName)
The name of the trigger that started this job run.
triggerName
- The name of the trigger that started this job run.public void setJobName(String jobName)
The name of the job definition being used in this run.
jobName
- The name of the job definition being used in this run.public String getJobName()
The name of the job definition being used in this run.
public JobRun withJobName(String jobName)
The name of the job definition being used in this run.
jobName
- The name of the job definition being used in this run.public void setStartedOn(Date startedOn)
The date and time at which this job run was started.
startedOn
- The date and time at which this job run was started.public Date getStartedOn()
The date and time at which this job run was started.
public JobRun withStartedOn(Date startedOn)
The date and time at which this job run was started.
startedOn
- The date and time at which this job run was started.public void setLastModifiedOn(Date lastModifiedOn)
The last time that this job run was modified.
lastModifiedOn
- The last time that this job run was modified.public Date getLastModifiedOn()
The last time that this job run was modified.
public JobRun withLastModifiedOn(Date lastModifiedOn)
The last time that this job run was modified.
lastModifiedOn
- The last time that this job run was modified.public void setCompletedOn(Date completedOn)
The date and time that this job run completed.
completedOn
- The date and time that this job run completed.public Date getCompletedOn()
The date and time that this job run completed.
public JobRun withCompletedOn(Date completedOn)
The date and time that this job run completed.
completedOn
- The date and time that this job run completed.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.
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.JobRunState
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.
JobRunState
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.
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.JobRunState
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.
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.JobRunState
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.
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.
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.
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.
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.
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.
public JobRun addArgumentsEntry(String key, String value)
public JobRun clearArgumentsEntries()
public void setErrorMessage(String errorMessage)
An error message associated with this job run.
errorMessage
- An error message associated with this job run.public String getErrorMessage()
An error message associated with this job run.
public JobRun withErrorMessage(String errorMessage)
An error message associated with this job run.
errorMessage
- An error message associated with this job run.public List<Predecessor> getPredecessorRuns()
A list of predecessors to this job run.
public void setPredecessorRuns(Collection<Predecessor> predecessorRuns)
A list of predecessors to this job run.
predecessorRuns
- A list of predecessors to this job run.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.
predecessorRuns
- A list of predecessors to this job run.public JobRun withPredecessorRuns(Collection<Predecessor> predecessorRuns)
A list of predecessors to this job run.
predecessorRuns
- A list of predecessors to this job run.@Deprecated public void setAllocatedCapacity(Integer 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.
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.
@Deprecated public Integer getAllocatedCapacity()
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.
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.
@Deprecated public JobRun withAllocatedCapacity(Integer 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.
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.
public void setExecutionTime(Integer executionTime)
The amount of time (in seconds) that the job run consumed resources.
executionTime
- The amount of time (in seconds) that the job run consumed resources.public Integer getExecutionTime()
The amount of time (in seconds) that the job run consumed resources.
public JobRun withExecutionTime(Integer executionTime)
The amount of time (in seconds) that the job run consumed resources.
executionTime
- The amount of time (in seconds) that the job run consumed resources.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 do not have a timeout. The default for non-streaming jobs is 2,880 minutes (48 hours).
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 do not have a timeout. The default for non-streaming jobs is 2,880 minutes (48 hours).
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 do not have a timeout. The default for non-streaming jobs is 2,880 minutes (48 hours).
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 do not have a timeout. The default for non-streaming jobs is 2,880 minutes (48 hours).
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 do not have a timeout. The default for non-streaming jobs is 2,880 minutes (48 hours).
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 do not have a timeout. The default for non-streaming jobs is 2,880 minutes (48 hours).
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.
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.
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.
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.
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.
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.
public void setWorkerType(String workerType)
The type of predefined worker that is allocated when a job runs. Accepts a value of Standard, G.1X, G.2X, or G.025X for Spark jobs. Accepts the value Z.2X for Ray jobs.
For the Standard
worker type, each worker provides 4 vCPU, 16 GB of memory and a 50GB disk, and 2
executors per worker.
For the G.1X
worker type, each worker maps to 1 DPU (4 vCPU, 16 GB of memory, 64 GB disk), and
provides 1 executor per worker. We recommend this worker type for memory-intensive jobs.
For the G.2X
worker type, each worker maps to 2 DPU (8 vCPU, 32 GB of memory, 128 GB disk), and
provides 1 executor per worker. We recommend this worker type for memory-intensive jobs.
For the G.025X
worker type, each worker maps to 0.25 DPU (2 vCPU, 4 GB of memory, 64 GB disk), 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 (8vCPU, 64 GB of m emory, 128 GB disk), and
provides up to 8 Ray workers (one per vCPU) based on the autoscaler.
workerType
- The type of predefined worker that is allocated when a job runs. Accepts a value of Standard, G.1X, G.2X,
or G.025X for Spark jobs. Accepts the value Z.2X for Ray jobs.
For the Standard
worker type, each worker provides 4 vCPU, 16 GB of memory and a 50GB disk,
and 2 executors per worker.
For the G.1X
worker type, each worker maps to 1 DPU (4 vCPU, 16 GB of memory, 64 GB disk),
and provides 1 executor per worker. We recommend this worker type for memory-intensive jobs.
For the G.2X
worker type, each worker maps to 2 DPU (8 vCPU, 32 GB of memory, 128 GB disk),
and provides 1 executor per worker. We recommend this worker type for memory-intensive jobs.
For the G.025X
worker type, each worker maps to 0.25 DPU (2 vCPU, 4 GB of memory, 64 GB
disk), 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 (8vCPU, 64 GB of m emory, 128 GB disk),
and provides up to 8 Ray workers (one per vCPU) based on the autoscaler.
WorkerType
public String getWorkerType()
The type of predefined worker that is allocated when a job runs. Accepts a value of Standard, G.1X, G.2X, or G.025X for Spark jobs. Accepts the value Z.2X for Ray jobs.
For the Standard
worker type, each worker provides 4 vCPU, 16 GB of memory and a 50GB disk, and 2
executors per worker.
For the G.1X
worker type, each worker maps to 1 DPU (4 vCPU, 16 GB of memory, 64 GB disk), and
provides 1 executor per worker. We recommend this worker type for memory-intensive jobs.
For the G.2X
worker type, each worker maps to 2 DPU (8 vCPU, 32 GB of memory, 128 GB disk), and
provides 1 executor per worker. We recommend this worker type for memory-intensive jobs.
For the G.025X
worker type, each worker maps to 0.25 DPU (2 vCPU, 4 GB of memory, 64 GB disk), 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 (8vCPU, 64 GB of m emory, 128 GB disk), and
provides up to 8 Ray workers (one per vCPU) based on the autoscaler.
For the Standard
worker type, each worker provides 4 vCPU, 16 GB of memory and a 50GB disk,
and 2 executors per worker.
For the G.1X
worker type, each worker maps to 1 DPU (4 vCPU, 16 GB of memory, 64 GB disk),
and provides 1 executor per worker. We recommend this worker type for memory-intensive jobs.
For the G.2X
worker type, each worker maps to 2 DPU (8 vCPU, 32 GB of memory, 128 GB disk),
and provides 1 executor per worker. We recommend this worker type for memory-intensive jobs.
For the G.025X
worker type, each worker maps to 0.25 DPU (2 vCPU, 4 GB of memory, 64 GB
disk), 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 (8vCPU, 64 GB of m emory, 128 GB
disk), and provides up to 8 Ray workers (one per vCPU) based on the autoscaler.
WorkerType
public JobRun withWorkerType(String workerType)
The type of predefined worker that is allocated when a job runs. Accepts a value of Standard, G.1X, G.2X, or G.025X for Spark jobs. Accepts the value Z.2X for Ray jobs.
For the Standard
worker type, each worker provides 4 vCPU, 16 GB of memory and a 50GB disk, and 2
executors per worker.
For the G.1X
worker type, each worker maps to 1 DPU (4 vCPU, 16 GB of memory, 64 GB disk), and
provides 1 executor per worker. We recommend this worker type for memory-intensive jobs.
For the G.2X
worker type, each worker maps to 2 DPU (8 vCPU, 32 GB of memory, 128 GB disk), and
provides 1 executor per worker. We recommend this worker type for memory-intensive jobs.
For the G.025X
worker type, each worker maps to 0.25 DPU (2 vCPU, 4 GB of memory, 64 GB disk), 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 (8vCPU, 64 GB of m emory, 128 GB disk), and
provides up to 8 Ray workers (one per vCPU) based on the autoscaler.
workerType
- The type of predefined worker that is allocated when a job runs. Accepts a value of Standard, G.1X, G.2X,
or G.025X for Spark jobs. Accepts the value Z.2X for Ray jobs.
For the Standard
worker type, each worker provides 4 vCPU, 16 GB of memory and a 50GB disk,
and 2 executors per worker.
For the G.1X
worker type, each worker maps to 1 DPU (4 vCPU, 16 GB of memory, 64 GB disk),
and provides 1 executor per worker. We recommend this worker type for memory-intensive jobs.
For the G.2X
worker type, each worker maps to 2 DPU (8 vCPU, 32 GB of memory, 128 GB disk),
and provides 1 executor per worker. We recommend this worker type for memory-intensive jobs.
For the G.025X
worker type, each worker maps to 0.25 DPU (2 vCPU, 4 GB of memory, 64 GB
disk), 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 (8vCPU, 64 GB of m emory, 128 GB disk),
and provides up to 8 Ray workers (one per vCPU) based on the autoscaler.
WorkerType
public JobRun withWorkerType(WorkerType workerType)
The type of predefined worker that is allocated when a job runs. Accepts a value of Standard, G.1X, G.2X, or G.025X for Spark jobs. Accepts the value Z.2X for Ray jobs.
For the Standard
worker type, each worker provides 4 vCPU, 16 GB of memory and a 50GB disk, and 2
executors per worker.
For the G.1X
worker type, each worker maps to 1 DPU (4 vCPU, 16 GB of memory, 64 GB disk), and
provides 1 executor per worker. We recommend this worker type for memory-intensive jobs.
For the G.2X
worker type, each worker maps to 2 DPU (8 vCPU, 32 GB of memory, 128 GB disk), and
provides 1 executor per worker. We recommend this worker type for memory-intensive jobs.
For the G.025X
worker type, each worker maps to 0.25 DPU (2 vCPU, 4 GB of memory, 64 GB disk), 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 (8vCPU, 64 GB of m emory, 128 GB disk), and
provides up to 8 Ray workers (one per vCPU) based on the autoscaler.
workerType
- The type of predefined worker that is allocated when a job runs. Accepts a value of Standard, G.1X, G.2X,
or G.025X for Spark jobs. Accepts the value Z.2X for Ray jobs.
For the Standard
worker type, each worker provides 4 vCPU, 16 GB of memory and a 50GB disk,
and 2 executors per worker.
For the G.1X
worker type, each worker maps to 1 DPU (4 vCPU, 16 GB of memory, 64 GB disk),
and provides 1 executor per worker. We recommend this worker type for memory-intensive jobs.
For the G.2X
worker type, each worker maps to 2 DPU (8 vCPU, 32 GB of memory, 128 GB disk),
and provides 1 executor per worker. We recommend this worker type for memory-intensive jobs.
For the G.025X
worker type, each worker maps to 0.25 DPU (2 vCPU, 4 GB of memory, 64 GB
disk), 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 (8vCPU, 64 GB of m emory, 128 GB disk),
and provides up to 8 Ray workers (one per vCPU) based on the autoscaler.
WorkerType
public void setNumberOfWorkers(Integer numberOfWorkers)
The number of workers of a defined workerType
that are allocated when a job runs.
numberOfWorkers
- The number of workers of a defined workerType
that are allocated when a job runs.public Integer getNumberOfWorkers()
The number of workers of a defined workerType
that are allocated when a job runs.
workerType
that are allocated when a job runs.public JobRun withNumberOfWorkers(Integer numberOfWorkers)
The number of workers of a defined workerType
that are allocated when a job runs.
numberOfWorkers
- The number of workers of a defined workerType
that are allocated when a job runs.public void setSecurityConfiguration(String securityConfiguration)
The name of the SecurityConfiguration
structure to be used with this job run.
securityConfiguration
- The name of the SecurityConfiguration
structure to be used with this job run.public String getSecurityConfiguration()
The name of the SecurityConfiguration
structure to be used with this job run.
SecurityConfiguration
structure to be used with this job run.public JobRun withSecurityConfiguration(String securityConfiguration)
The name of the SecurityConfiguration
structure to be used with this job run.
securityConfiguration
- The name of the SecurityConfiguration
structure to be used with this job run.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.
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.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.
/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.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.
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.public void setNotificationProperty(NotificationProperty notificationProperty)
Specifies configuration properties of a job run notification.
notificationProperty
- Specifies configuration properties of a job run notification.public NotificationProperty getNotificationProperty()
Specifies configuration properties of a job run notification.
public JobRun withNotificationProperty(NotificationProperty notificationProperty)
Specifies configuration properties of a job run notification.
notificationProperty
- Specifies configuration properties of a job run notification.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.
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.
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.
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.
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.
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.
public void setDPUSeconds(Double dPUSeconds)
This field populates only for Auto Scaling job runs, 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
.
dPUSeconds
- This field populates only for Auto Scaling job runs, 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
.public Double getDPUSeconds()
This field populates only for Auto Scaling job runs, 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
.
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
.public JobRun withDPUSeconds(Double dPUSeconds)
This field populates only for Auto Scaling job runs, 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
.
dPUSeconds
- This field populates only for Auto Scaling job runs, 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
.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.
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.
ExecutionClass
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.
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.
ExecutionClass
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.
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.
ExecutionClass
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.
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.
ExecutionClass
public String toString()
toString
in class Object
Object.toString()
public void marshall(ProtocolMarshaller protocolMarshaller)
marshall
in interface StructuredPojo
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