Extend Jupyter-scheduler to create and manage jobs with multiple tasks
akshaychitneni opened this issue · 2 comments
Problem
Jupyter scheduler currently enable users to create and manage background jobs that execute a notebook file. We would like to extend current jobs to support multiple notebook tasks where each task would execute a notebook file and also allow creating dependencies between the tasks. We want to intiate the discussion to extend jupyter scheduler so users can create and manage notebooks workflows and associated runs in jupyter workspace. It would also require UX for users to easily create tasks and it associated dependencies using a DAG editor.
Proposed Solution
Tentative model:
- DescribeJobDefinition API Response
{
"name": "test1",
"tags": null,
"output_filename_template": "{{input_filename}}-{{create_time}}",
"schedule": "0 0 * * MON-FRI",
"timezone": "America/Los_Angeles",
"job_definition_id": "b5c6099c-9bec-4a04-968f-37e9c23c0f9b",
"create_time": 1701124758318,
"update_time": 1701124758317,
"active": true,
"tasks": [
{
"name": "task1",
"input_filename": "Untitled1.ipynb",
"parameters": null,
"runtimeProperties": {},
"runtime_environment_name": "anaconda3",
"runtime_environment_parameters": null,
"output_formats": [
"ipynb",
"html"
],
"compute_type": null,
"trigger_rule": null,
"dependsOn": []
},
{ "name": "task2",
"input_filename": "Untitled2.ipynb",
"parameters": null,
"runtimeProperties": {},
"runtime_environment_name": "anaconda3",
"runtime_environment_parameters": null,
"output_formats": [
"ipynb",
"html"
],
"compute_type": null,
"trigger_rule": "all_success",
"dependsOn": ["task1"]
}
}
DescribeJob API Response:
{
"name": "job1",
"tags": null,
"output_filename_template": "{{input_filename}}-{{create_time}}",
"job_id": "27d8a6ae-47d0-4ed3-9e28-5411d21a0e03",
"url": "/jobs/27d8a6ae-47d0-4ed3-9e28-5411d21a0e03",
"create_time": 1696264966089,
"update_time": 1696264968551,
"start_time": 1696264967241,
"end_time": 1696264968550,
"status": "COMPLETED",
"status_message": null,
"tasks": [
{
"input_filename": "Untitled2.ipynb",
"runtime_environment_name": "anaconda3",
"runtime_environment_parameters": null,
"output_formats": [
"ipynb",
"html"
],
"parameters": null,
"name": "task1",
"job_files": [
{
"display_name": "HTML",
"file_format": "html",
"file_path": null
},
{
"display_name": "Input",
"file_format": "input",
"file_path": null
}
],
"create_time": 1696264966089,
"update_time": 1696264968551,
"start_time": 1696264967241,
"end_time": 1696264968550,
"trigger_rule": null,
"dependsOn": [],
"status": "COMPLETED",
"status_message": null,
"downloaded": false
},
{
"input_filename": "Untitled2.ipynb",
"runtime_environment_name": "anaconda3",
"runtime_environment_parameters": null,
"output_formats": [
"ipynb",
"html"
],
"parameters": null,
"name": "task2",
"job_files": [
{
"display_name": "HTML",
"file_format": "html",
"file_path": null
},
{
"display_name": "Input",
"file_format": "input",
"file_path": null
}
],
"create_time": 1696264966089,
"update_time": 1696264968551,
"start_time": 1696264967241,
"end_time": 1696264968550,
"trigger_rule": "all_success",
"dependsOn": ["task1"],
"status": "COMPLETED",
"status_message": null,
"downloaded": false
}
]
}
Providing such an interface would allow users to extend scheduler to integrate with external orchestrators or schedulers like airflow to schedule and run notebook DAGs.
Additional context
- Elyra provides similar functionality with a DAG editor - https://elyra.readthedocs.io/en/latest/user_guide/pipelines.html#generic-pipelines
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@akshaychitneni Thank you so much for contributing to Jupyter Scheduler! We have an issue #411 to cover multi-task jobs, opened earlier. I'm going to close this one as a duplicate, but let's keep the conversation going on the earlier issue.