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Job request: 19798

Organisation:
Bennett Institute
Workspace:
opioids-covid-research
ID:
r5bkw6lcl6yoaz4d

This page shows the technical details of what happened when the authorised researcher Andrea Schaffer 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:
    measures_demo
    Status:
    Status: Failed
    Job identifier:
    4n6avkequyyrrno5
    Error:
    nonzero_exit: Job exited with an error
  • Action:
    measures_overall
    Status:
    Status: Succeeded
    Job identifier:
    wxurjrgqmwcuoe3b
  • Action:
    measures_type
    Status:
    Status: Succeeded
    Job identifier:
    dn4zvnwsnzovdhdj
  • Action:
    measures_carehome
    Status:
    Status: Succeeded
    Job identifier:
    zh7enlpx2pwefwf2
  • Action:
    process_data_ts
    Status:
    Status: Failed
    Job identifier:
    6vvtg77fomxwgzwj
    Error:
    dependency_failed: Not starting as dependency failed
  • Action:
    rounding_ts
    Status:
    Status: Failed
    Job identifier:
    26llhsmjmof64nhi
    Error:
    dependency_failed: Not starting as dependency failed

Pipeline

Show project.yaml
######################################
# This script defines the project pipeline - 
# it specifies the execution orders for all the code in this
# repo using a series of actions.
######################################

version: '3.0'

expectations:
  population_size: 10000

actions:

  generate_dataset_table:
    run: ehrql:v0 generate-dataset analysis/define_dataset_table.py 
      --output output/data/dataset_table.csv.gz
    outputs:
      highly_sensitive:
        cohort: output/data/dataset_table.csv.gz  

  # Measures - overall
  measures_overall:
    run: ehrql:v0 generate-measures analysis/measures_overall.py 
      --output output/measures/measures_overall.csv
      --
      --start-date "2018-01-01"
      --intervals 54
    outputs:
      moderately_sensitive:
        measure_csv: output/measures/measures_overall.csv

  # Measures - by demographic categories
  measures_demo:
    run: ehrql:v0 generate-measures analysis/measures_demo.py 
      --output output/measures/measures_demo.csv
      --
      --start-date "2018-01-01"
      --intervals 54
    outputs:
      moderately_sensitive:
        measure_csv: output/measures/measures_demo.csv

  # Measures - by opioid type
  measures_type:
    run: ehrql:v0 generate-measures analysis/measures_type.py 
      --output output/measures/measures_type.csv
      --
      --start-date "2018-01-01"
      --intervals 54
    outputs:
      moderately_sensitive:
        measure_csv: output/measures/measures_type.csv 

  # Measures - in people in care home
  measures_carehome:
    run: ehrql:v0 generate-measures analysis/measures_carehome.py 
      --output output/measures/measures_carehome.csv
      --
      --start-date "2018-01-01"
      --intervals 54
    outputs:
      moderately_sensitive:
        measure_csv: output/measures/measures_carehome.csv
        
  ## Process data - time series
  process_data_ts:
   run: r:latest analysis/process/process_data_ts.R
   needs: [measures_overall, measures_demo, measures_type, measures_carehome]
   outputs:
      moderately_sensitive:
        timeseries_csv: output/timeseries/ts_*.csv

  ## Time series - rounding
  rounding_ts:
   run: r:latest analysis/process/rounding_ts.R
   needs: [process_data_ts]
   outputs:
      moderately_sensitive:
        timeseries_csv: output/timeseries/ts*.csv

  ## Results table 
  table:
    run: r:latest analysis/descriptive/table_stand.R
    needs: [generate_dataset_table]
    outputs:
      moderately_sensitive:
        table: output/tables/table_*.csv

  
  # OLD COHORTEXTRACTOR CODE

  # ## Cohort data
  # generate_study_population_1:
  #   run: cohortextractor:latest generate_cohort
  #     --study-definition study_definition
  #     --index-date-range "2018-01-01 to 2018-12-01 by month" 
  #     --output-dir=output 
  #     --output-format=csv
  #   outputs:
  #     highly_sensitive:
  #       cohort: output/input_*.csv

  # generate_study_population_2:
  #   run: cohortextractor:latest generate_cohort 
  #     --study-definition study_definition
  #     --index-date-range "2019-01-01 to 2019-12-01 by month" 
  #     --output-dir=output 
  #     --output-format=csv
  #   outputs:
  #     highly_sensitive:
  #       cohort: output/input*.csv

  # generate_study_population_3:
  #   run: cohortextractor:latest generate_cohort 
  #     --study-definition study_definition
  #     --index-date-range "2020-01-01 to 2020-12-01 by month" 
  #     --output-dir=output 
  #     --output-format=csv
  #   outputs:
  #     highly_sensitive:
  #       cohort: output/inpu*.csv

  # generate_study_population_4:
  #   run: cohortextractor:latest generate_cohort 
  #     --study-definition study_definition
  #     --index-date-range "2021-01-01 to 2021-12-01 by month" 
  #     --output-dir=output 
  #     --output-format=csv
  #   outputs:
  #     highly_sensitive:
  #       cohort: output/inp*.csv
  
  # generate_study_population_5:
  #   run: cohortextractor:latest generate_cohort 
  #     --study-definition study_definition
  #     --index-date-range "2022-01-01 to 2022-03-01 by month" 
  #     --output-dir=output 
  #     --output-format=csv
  #   outputs:
  #     highly_sensitive:
  #       cohort: output/in*.csv

  # ## Ethnicity      
  # generate_ethnicity_cohort:
  #   run: >
  #     cohortextractor:latest generate_cohort
  #       --study-definition study_definition_ethnicity
  #   outputs:
  #     highly_sensitive:
  #       cohort: output/input_ethnicity.csv


  # # Data processing ----
  
  # ## Add ethnicity
  # join_cohorts:
  #   run: >
  #     cohort-joiner:v0.0.48
  #       --lhs output/input_*.csv
  #       --rhs output/input_ethnicity.csv
  #       --output-dir output/data
  #   needs: [generate_study_population_1,  generate_study_population_2, 
  #     generate_study_population_5, generate_study_population_3, 
  #     generate_study_population_4, generate_ethnicity_cohort]
  #   outputs:
  #     highly_sensitive:
  #       cohort: output/data/input_*.csv 


  # ## Generate measures - full population
  # generate_measures:
  #   run: >
  #     cohortextractor:latest generate_measures 
  #       --study-definition study_definition
  #       --output-dir output/data
  #   needs: [join_cohorts]
  #   outputs:
  #     moderately_sensitive:
  #       measure_csv: output/data/measure_*.csv

Timeline

  • Created:

  • Started:

  • Finished:

  • Runtime: 129:28:56

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

Job request

Status
Failed
Backend
TPP
Requested by
Andrea Schaffer
Branch
main
Force run dependencies
No
Git commit hash
1a0879b
Requested actions
  • measures_overall
  • measures_demo
  • measures_type
  • measures_carehome
  • process_data_ts
  • rounding_ts

Code comparison

Compare the code used in this job request