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Job request: 26772

Organisation:
University of Oxford
Workspace:
vitamin-d-trends
ID:
qfvegundoz3mibf6

This page shows the technical details of what happened when the authorised researcher Jaidip Gill requested one or more actions to be run against real patient data within a secure environment.

By cross-referencing the list of jobs with the pipeline section below, you can infer what security level the outputs were written to.

The output security levels are:

  • highly_sensitive
    • Researchers can never directly view these outputs
    • Researchers can only request code is run against them
  • moderately_sensitive
    • Can be viewed by an approved researcher by logging into a highly secure environment
    • These are the only outputs that can be requested for public release via a controlled output review service.

Jobs

  • Action:
    generate_measures
    Status:
    Failed
    Job identifier:
    5gz7i55b5236s5tv
    Status message:
    nonzero_exit: Job exited with an error
  • Action:
    generate_covariate_plots
    Status:
    Failed
    Job identifier:
    vmblwfttzjlre737
    Status message:
    dependency_failed: Not starting as dependency failed
  • Action:
    generate_overall_trends
    Status:
    Failed
    Job identifier:
    5esmsnoxaujxfpqb
    Status message:
    dependency_failed: Not starting as dependency failed
  • Action:
    generate_decile_plots
    Status:
    Failed
    Job identifier:
    4nh2az6gfxrdhzig
    Status message:
    dependency_failed: Not starting as dependency failed

Pipeline

Show project.yaml
version: '5.0'

actions:

  generate_measures:
    run: ehrql:v1 generate-measures analysis/n50_measures.py
      --output output/measures.csv.gz
      --
      --full
    outputs:
      highly_sensitive:
        measures: output/measures.csv.gz

  generate_measures_test:
    run: ehrql:v1 generate-measures analysis/n50_measures.py
      --output output/measures_test.csv
      --
      --test
    outputs:
      highly_sensitive:
        measures: output/measures_test.csv


  assure_dataset:
    run: >
        ehrql:v1 generate-dataset
        analysis/n60_assure_definition.py
        --test-data-file analysis/n70_test_dataset.py
        --output output/dataset.csv
        --
        --assure
    outputs:
      highly_sensitive:
        population: output/dataset.csv


  generate_overall_trends:
    run: >
      r:v2 analysis/n91_overall_trends.R --full
    needs:
      - generate_measures
    outputs:
      moderately_sensitive:
        vitd_overall_trends: output/vitd_overall_trends.png

  generate_overall_trends_test:
    run: >
      r:v2 analysis/n91_overall_trends.R --test
    needs:
      - generate_measures_test
    outputs:
      moderately_sensitive:
        vitd_overall_trends_test: output/vitd_overall_trends_test.png
   

  generate_decile_plots:
    run: >
      r:v2 analysis/n92_practice_decile_plots.R --full
    needs:
      - generate_measures
    outputs:
      moderately_sensitive:
         vitd_practice_deciles: output/vitd_practice_deciles.png

  generate_decile_plots_test:
    run: >
      r:v2 analysis/n92_practice_decile_plots.R --test
    needs:
      - generate_measures_test
    outputs:
      moderately_sensitive:
        vitd_practice_deciles_test: output/vitd_practice_deciles_test.png


  generate_covariate_plots:
    run: >
      r:v2 analysis/n93_covariate_plots.R --full
    needs:
      - generate_measures
    outputs:
      moderately_sensitive:
        vitd_covariates_demographic_testing: output/vitd_covariates_demographic_testing.png
        vitd_covariates_demographic_prescribing: output/vitd_covariates_demographic_prescribing.png
        vitd_covariates_demographic_vit_d_calcium_prescribing: output/vitd_covariates_demographic_vit_d_calcium_prescribing.png
        vitd_covariates_geographic_practice_testing: output/vitd_covariates_geographic_practice_testing.png
        vitd_covariates_geographic_practice_prescribing: output/vitd_covariates_geographic_practice_prescribing.png
        vitd_covariates_geographic_practice_vit_d_calcium_prescribing: output/vitd_covariates_geographic_practice_vit_d_calcium_prescribing.png

  generate_covariate_plots_test:
    run: >
      r:v2 analysis/n93_covariate_plots.R --test
    needs:
      - generate_measures_test
    outputs:
      moderately_sensitive:
        vitd_covariates_demographic_testing_test: output/vitd_covariates_demographic_testing_test.png
        vitd_covariates_demographic_prescribing_test: output/vitd_covariates_demographic_prescribing_test.png
        vitd_covariates_demographic_vit_d_calcium_prescribing_test: output/vitd_covariates_demographic_vit_d_calcium_prescribing_test.png
        vitd_covariates_geographic_practice_testing_test: output/vitd_covariates_geographic_practice_testing_test.png
        vitd_covariates_geographic_practice_prescribing_test: output/vitd_covariates_geographic_practice_prescribing_test.png
        vitd_covariates_geographic_practice_vit_d_calcium_prescribing_test: output/vitd_covariates_geographic_practice_vit_d_calcium_prescribing_test.png

Job statistics

Status Count Percentage
Pending 0 0%
Running 0 0%
Succeeded 0 0%
Failed 4 100%

4 / 4 (100%) complete

Timeline

  • Created:

  • Started:

  • Finished:

  • Runtime: 00:00:31

These timestamps are generated and stored using the UTC timezone on the TPP backend.

Job request

Status
Failed
Backend
TPP
Workspace
vitamin-d-trends
Requested by
Jaidip Gill
Branch
main
Force run dependencies
No
Git commit hash
e31b819
Requested actions
  • generate_measures
  • generate_overall_trends
  • generate_decile_plots
  • generate_covariate_plots

Code comparison

Compare the code used in this job request

  • No previous job request available for comparison