Show Worker Parameter Values In Job View

by Omar Yusuf 41 views

Introduction

In the realm of complex experimental setups, keeping track of parameter values used by workers during job execution is super important. Currently, the Job View page lacks the crucial functionality to display these worker parameter values, creating a visibility gap and potential confusion for users. This article dives deep into the proposed solution to enhance the Job View by showcasing worker parameter values and highlighting discrepancies between worker values and the latest database values. So, let's get started, guys!

Problem Statement: The Missing Parameter Values

The existing Job View page provides a "Parameter Values" section, but it falls short of its intended purpose. It only displays an "Update Scan Parameters" button without presenting any actual parameter information. This absence of worker parameter values makes it difficult for users to ascertain the parameters that were in effect during job execution. A critical question arises: Do the worker values align with the latest values stored in the database? Without this clarity, users may struggle to troubleshoot issues or replicate experimental results accurately. The image included in the feature request clearly illustrates this deficiency, highlighting the empty parameter information section.

Proposed Solution: A Comprehensive Approach

To address this issue, a multifaceted solution involving both backend and frontend enhancements is proposed. The goal is to provide a seamless and informative experience for users, enabling them to readily access and interpret worker parameter values within the Job View.

Backend Enhancements

The backend enhancements focus on retrieving and transmitting the necessary parameter data to the frontend. This involves several key steps:

  1. Adding get_metadata(experiment_id: string) -> ExperimentMetadata to ExperimentsController: This new function will enable the retrieval of metadata for a specific experiment. Metadata provides essential context and structure for the parameter values.
  2. Extending ExperimentData and ExperimentDataRepository.get_experiment_data_by_job_id: The ExperimentData structure will be extended to include a parameters field, represented as a dictionary: parameters: dict[str, dict[str, DatabaseValueType]]. This dictionary will store parameter information, with the first key representing the parameter ID and the second key representing the timestamp string. The ExperimentDataRepository.get_experiment_data_by_job_id function will also be updated to include this new parameters field in the returned data.
    • The parameter information is already stored in the HDF file within the parameters group. Each parameter has its own dedicated dataset.
  3. Pushing Worker Parameter Updates via Socket Events: A new socket event, experiment_params_{job_id}, will be introduced to push worker parameter updates from ExperimentDataRepository.write_parameter_update_by_job_id. This event will contain updated parameter values and their corresponding timestamps, ensuring that the frontend receives real-time updates.

These backend changes lay the groundwork for efficiently retrieving and disseminating worker parameter data.

Frontend Enhancements

The frontend enhancements are geared towards displaying and highlighting parameter values in a user-friendly manner. These enhancements include:

  1. Updating Parameter Input Components: Existing parameter input components, such as Combobox, Button, and ParameterNumberComponent, will be modified to receive metadata either through props or by utilizing the ParameterMetadataContext. This ensures that these components can effectively render and interact with parameter data.
  2. Introducing a New JobParameterGroups Component: A new component, JobParameterGroups, will be created specifically for the Job View. This component will be job-scoped and will not rely on the ParameterDisplayGroupsContext. It will reuse existing parameter input components, but it will pass metadata via props, ensuring that the component remains focused and efficient.
  3. Fetching Experiment Metadata and Worker Parameter Values: The frontend will fetch experiment metadata using the newly added get_metadata API. It will also retrieve worker parameter values using the updated get_experiment_data_by_job_id function. This data will then be used to populate the JobParameterGroups component.
  4. Highlighting Parameter Discrepancies: A key feature of the solution is the ability to highlight parameters where the worker value differs from the latest value stored in the database. Parameters with discrepancies will be highlighted in orange, providing a visual cue to the user. Additionally, a tooltip will be displayed, showing the latest database value. The backend push updates will be leveraged to remove these highlights once the discrepancies are resolved.
  5. Wrapping Running Jobs in ParameterStoreProvider: To ensure that the frontend has access to live database values, running jobs will be wrapped in a ParameterStoreProvider. This will provide a consistent and up-to-date view of parameter values.

These frontend enhancements will provide a clear and interactive display of worker parameter values, enabling users to quickly identify and address any discrepancies.

Alternatives Considered

An alternative approach considered was rewriting the existing ParameterGroupDisplay component to be job-specific. However, this approach was deemed less desirable because it would introduce job-specific logic into a general-purpose component. Furthermore, it would create unnecessary dependencies on contexts that are not required in the Job View. The creation of a new JobParameterGroups component avoids these issues, resulting in a more modular and maintainable solution.

Additional Context and Considerations

Several additional points are worth noting:

  • Experiments do not yet reference device parameters; therefore, only experiment parameter groups will be displayed.
  • Per-parameter latest value from the HDF file is sufficient; a full time series of values can be returned if needed.
  • Parameters are guaranteed to be present in the HDF file; any missing parameters should raise an error.
  • Parameter input components (Button, Combobox, ParameterNumberComponent) should be passed metadata and values directly to reduce re-renders. Avoid passing an object containing the metadata, as this can trigger unnecessary re-renders.

Conclusion

Implementing these enhancements to the Job View will significantly improve the user experience by providing clear visibility into worker parameter values. The highlighting of discrepancies between worker values and database values will enable users to quickly identify and resolve potential issues, ensuring the integrity and reproducibility of experimental results. This comprehensive solution addresses a critical need and will contribute to a more efficient and reliable experimental workflow. By displaying the worker parameter values and highlighting any differences from the database values, this feature will empower users to have a clearer understanding of their experiments and improve their overall workflow. The proposed solution, with its backend and frontend components, ensures a user-friendly and efficient experience, ultimately leading to better experimental outcomes. This enhancement to the Job View will not only improve the clarity and transparency of experiments but also contribute to a more streamlined and reliable workflow for researchers and scientists. This comprehensive approach will undoubtedly enhance the user experience and contribute to more accurate and reproducible research outcomes. Guys, this is a huge step forward!