[−][src]Struct rusoto_glue::JobRun
Contains information about a job run.
Fields
arguments: Option<HashMap<String, String>>
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 AWS Glue itself consumes.
For information about how to specify and consume your own job arguments, see the Calling AWS Glue APIs in Python topic in the developer guide.
For information about the key-value pairs that AWS Glue consumes to set up your job, see the Special Parameters Used by AWS Glue topic in the developer guide.
attempt: Option<i64>
The number of the attempt to run this job.
completed_on: Option<f64>
The date and time that this job run completed.
error_message: Option<String>
An error message associated with this job run.
execution_time: Option<i64>
The amount of time (in seconds) that the job run consumed resources.
id: Option<String>
The ID of this job run.
job_name: Option<String>
The name of the job definition being used in this run.
job_run_state: Option<String>
The current state of the job run.
last_modified_on: Option<f64>
The last time that this job run was modified.
log_group_name: Option<String>
The name of the log group for secure logging that can be server-side encrypted in Amazon CloudWatch using AWS 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.
max_capacity: Option<f64>
The number of AWS 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 AWS Glue pricing page.
Do not set Max Capacity
if using WorkerType
and NumberOfWorkers
.
The value that can be allocated for MaxCapacity
depends on whether you are running a Python shell job or an Apache Spark 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"), you can allocate from 2 to 100 DPUs. The default is 10 DPUs. This job type cannot have a fractional DPU allocation.
notification_property: Option<NotificationProperty>
Specifies configuration properties of a job run notification.
number_of_workers: Option<i64>
The number of workers of a defined workerType
that are allocated when a job runs.
The maximum number of workers you can define are 299 for G.1X
, and 149 for G.2X
.
predecessor_runs: Option<Vec<Predecessor>>
A list of predecessors to this job run.
previous_run_id: Option<String>
The ID of the previous run of this job. For example, the JobRunId
specified in the StartJobRun
action.
security_configuration: Option<String>
The name of the SecurityConfiguration
structure to be used with this job run.
started_on: Option<f64>
The date and time at which this job run was started.
timeout: Option<i64>
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. The default is 2,880 minutes (48 hours). This overrides the timeout value set in the parent job.
trigger_name: Option<String>
The name of the trigger that started this job run.
worker_type: Option<String>
The type of predefined worker that is allocated when a job runs. Accepts a value of Standard, G.1X, or G.2X.
-
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 provides 4 vCPU, 16 GB of memory and a 64GB disk, and 1 executor per worker. -
For the
G.2X
worker type, each worker provides 8 vCPU, 32 GB of memory and a 128GB disk, and 1 executor per worker.
Trait Implementations
impl PartialEq<JobRun> for JobRun
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impl Default for JobRun
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impl Clone for JobRun
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fn clone(&self) -> JobRun
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fn clone_from(&mut self, source: &Self)
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Performs copy-assignment from source
. Read more
impl Debug for JobRun
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impl<'de> Deserialize<'de> for JobRun
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fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error> where
__D: Deserializer<'de>,
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__D: Deserializer<'de>,
Auto Trait Implementations
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impl<T> From for T
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U: From<T>,
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T: Clone,
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T: Clone,
impl<T, U> TryFrom for T where
T: From<U>,
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T: From<U>,
type Error = !
try_from
)The type returned in the event of a conversion error.
fn try_from(value: U) -> Result<T, <T as TryFrom<U>>::Error>
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impl<T> Borrow for T where
T: ?Sized,
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T: ?Sized,
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T: ?Sized,
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U: TryFrom<T>,
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try_from
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T: 'static + ?Sized,
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Should always be Self