Glue / Client / get_job_run

get_job_run#

Glue.Client.get_job_run(**kwargs)#

Retrieves the metadata for a given job run.

Request Syntax

response = client.get_job_run(
    JobName='string',
    RunId='string',
    PredecessorsIncluded=True|False
)

Parameters:

JobName (string) –
[REQUIRED]

Name of the job definition being run.
RunId (string) –
[REQUIRED]

The ID of the job run.
PredecessorsIncluded (boolean) – True if a list of predecessor runs should be returned.

Return type:

dict

Returns:

Response Syntax

{
    'JobRun': {
        'Id': 'string',
        'Attempt': 123,
        'PreviousRunId': 'string',
        'TriggerName': 'string',
        'JobName': 'string',
        'StartedOn': datetime(2015, 1, 1),
        'LastModifiedOn': datetime(2015, 1, 1),
        'CompletedOn': datetime(2015, 1, 1),
        'JobRunState': 'STARTING'|'RUNNING'|'STOPPING'|'STOPPED'|'SUCCEEDED'|'FAILED'|'TIMEOUT'|'ERROR'|'WAITING',
        'Arguments': {
            'string': 'string'
        },
        'ErrorMessage': 'string',
        'PredecessorRuns': [
            {
                'JobName': 'string',
                'RunId': 'string'
            },
        ],
        'AllocatedCapacity': 123,
        'ExecutionTime': 123,
        'Timeout': 123,
        'MaxCapacity': 123.0,
        'WorkerType': 'Standard'|'G.1X'|'G.2X'|'G.025X'|'G.4X'|'G.8X'|'Z.2X',
        'NumberOfWorkers': 123,
        'SecurityConfiguration': 'string',
        'LogGroupName': 'string',
        'NotificationProperty': {
            'NotifyDelayAfter': 123
        },
        'GlueVersion': 'string',
        'DPUSeconds': 123.0,
        'ExecutionClass': 'FLEX'|'STANDARD'
    }
}

Response Structure

(dict) –
- JobRun (dict) –
  
  The requested job-run metadata.
  - Id (string) –
    
    The ID of this job run.
  - Attempt (integer) –
    
    The number of the attempt to run this job.
  - PreviousRunId (string) –
    
    The ID of the previous run of this job. For example, the JobRunId specified in the StartJobRun action.
  - TriggerName (string) –
    
    The name of the trigger that started this job run.
  - JobName (string) –
    
    The name of the job definition being used in this run.
  - StartedOn (datetime) –
    
    The date and time at which this job run was started.
  - LastModifiedOn (datetime) –
    
    The last time that this job run was modified.
  - CompletedOn (datetime) –
    
    The date and time that this job run completed.
  - JobRunState (string) –
    
    The current state of the job run. For more information about the statuses of jobs that have terminated abnormally, see Glue Job Run Statuses.
  - Arguments (dict) –
    
    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.
    - (string) –
      - (string) –
  - ErrorMessage (string) –
    
    An error message associated with this job run.
  - PredecessorRuns (list) –
    
    A list of predecessors to this job run.
    - (dict) –
      
      A job run that was used in the predicate of a conditional trigger that triggered this job run.
      - JobName (string) –
        
        The name of the job definition used by the predecessor job run.
      - RunId (string) –
        
        The job-run ID of the predecessor job run.
  - AllocatedCapacity (integer) –
    
    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.
  - ExecutionTime (integer) –
    
    The amount of time (in seconds) that the job run consumed resources.
  - Timeout (integer) –
    
    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).
  - MaxCapacity (float) –
    
    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.
  - WorkerType (string) –
    
    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.
  - NumberOfWorkers (integer) –
    
    The number of workers of a defined workerType that are allocated when a job runs.
  - SecurityConfiguration (string) –
    
    The name of the SecurityConfiguration structure to be used with this job run.
  - LogGroupName (string) –
    
    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.
  - NotificationProperty (dict) –
    
    Specifies configuration properties of a job run notification.
    - NotifyDelayAfter (integer) –
      
      After a job run starts, the number of minutes to wait before sending a job run delay notification.
  - GlueVersion (string) –
    
    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.
  - DPUSeconds (float) –
    
    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.
  - ExecutionClass (string) –
    
    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.

Exceptions

Glue.Client.exceptions.InvalidInputException
Glue.Client.exceptions.EntityNotFoundException
Glue.Client.exceptions.InternalServiceException
Glue.Client.exceptions.OperationTimeoutException