JobStatus

API reference for JobStatus

JobStatus

Status values for asynchronous job operations in Fiddler.

This enum defines the possible states that a Job can be in during its lifecycle. Jobs represent asynchronous operations such as data publishing, model uploads, and computation tasks that may take significant time to complete.

Job Lifecycle:

1. PENDING: Job created and queued for execution

2. STARTED: Job execution has begun

3. SUCCESS/FAILURE: Job completed with final status

4. RETRY: Job failed but will be retried automatically

5. REVOKED: Job was cancelled before completion

Examples

Monitoring job progress:

# Start a data publishing job
job = model.publish(source=data_df, environment=fdl.EnvType.PRODUCTION)

# Wait for completion
job.wait()  # Blocks until job completes

# Check final status
if job.status == fdl.JobStatus.SUCCESS:

    print(“Data published successfully”)

else:
    print(f”Job failed with status: {job.status}”)

Polling job status manually:

import time

# Check status periodically
while job.status in [fdl.JobStatus.PENDING, fdl.JobStatus.STARTED]:

    print(f”Job progress: {job.progress}%”)
    time.sleep(10)
    job.refresh()  # Update job status from server

    # Handle different completion states
if job.status == fdl.JobStatus.SUCCESS:

    print(“Operation completed successfully”)

elif job.status == fdl.JobStatus.FAILURE:
    print(f”Operation failed: {job.error_message}”)

elif job.status == fdl.JobStatus.REVOKED:
    print(“Operation was cancelled”)

Handling job failures and retries:

# Monitor job with retry handling
    max_wait_time = 3600  # 1 hour timeout
start_time = time.time()

while (time.time() - start_time) < max_wait_time:
    : if job.status == fdl.JobStatus.SUCCESS:
    break
  
    elif job.status == fdl.JobStatus.FAILURE:
    print(f”Job failed permanently: {job.error_message}”)
    break
  
elif job.status == fdl.JobStatus.RETRY:
    print(“Job failed but will be retried automatically”)
  
    time.sleep(30)
    job.refresh()

Job status should be refreshed periodically using job.refresh() to get the latest status from the server. The job.wait() method provides a convenient way to block until completion.

PENDING = 'PENDING'

Job is queued and waiting to start execution.

This is the initial status when a job is first created. The job has been submitted to the system but has not yet begun processing. Jobs may remain in PENDING status if there are resource constraints or if they are waiting for dependencies.

Characteristics:

• Job is in the execution queue

• No processing has started yet

• May transition to STARTED when resources become available

• Can be cancelled while in this state

Typical duration: Seconds to minutes depending on system load

STARTED = 'STARTED'

Job execution is currently in progress.

The job has begun processing and is actively running. Progress information may be available through the job.progress property. Jobs in this state are consuming system resources and performing the requested operation.

Characteristics:

• Active processing is occurring

• Progress updates may be available

• Cannot be cancelled once started

• Will transition to SUCCESS, FAILURE, or RETRY

Typical duration: Minutes to hours depending on operation complexity

SUCCESS = 'SUCCESS'

Job completed successfully.

The operation has finished successfully and all requested work has been completed. Results are available and the operation achieved its intended outcome without errors.

Characteristics:

• Operation completed without errors

• Results are available for use

• Job will not change status again

• Resources have been released

This is a terminal status - the job is complete.

FAILURE = 'FAILURE'

Job failed and will not be retried.

The operation encountered an error and could not be completed successfully. This is a permanent failure - the job will not be automatically retried. Error details are typically available in the job.error_message property.

Characteristics:

• Operation failed due to an error

• No automatic retry will occur

• Error details available in error_message

• Manual intervention may be required

Common causes:

• Invalid input data or parameters

• Insufficient permissions

• System resource exhaustion

• Data validation failures

This is a terminal status - the job will not continue.

RETRY = 'RETRY'

Job failed but will be automatically retried.

The operation encountered a temporary error but the system will automatically attempt to retry the job. This typically occurs for transient issues like network timeouts or temporary resource unavailability.

Characteristics:

• Temporary failure occurred

• System will automatically retry

• May transition back to PENDING or STARTED

• Retry attempts are limited

Common causes:

• Network connectivity issues

• Temporary resource constraints

• Transient system errors

• Database connection timeouts

The job may eventually succeed or transition to FAILURE if retries are exhausted.

REVOKED = 'REVOKED'

Job was cancelled or revoked before completion.

The job was explicitly cancelled by the user or system before it could complete. This may occur due to user cancellation, system shutdown, or administrative intervention.

Characteristics:

• Job was cancelled before completion

• No results are available

• Resources have been cleaned up

• Operation did not complete

Common causes:

• User-initiated cancellation

• System maintenance or shutdown

• Administrative intervention

• Timeout or resource limits exceeded

This is a terminal status - the job will not continue.