metadata.yaml

name: databricksreceiver
attributes:
  databricks.instance.name:
    description: The name of the Databricks instance as defined by the value of the "instance_name" field in the config
  job_id:
    description: The numeric ID of the Databricks job
  task_id:
    description: The name of the Databricks task
  task_type:
    description: The type of the Databricks task
    enum:
      - NotebookTask
      - SparkJarTask
      - SparkPythonTask
      - PipelineTask
      - PythonWheelTask
      - SparkSubmitTask
metrics:
  databricks.jobs.total:
    enabled: true
    description: A snapshot of the total number of jobs registered in the Databricks instance taken at each scrape
    unit: "{jobs}"
    gauge:
      value_type: int
  databricks.jobs.schedule.status:
    enabled: true
    description: A snapshot of the pause/run status per job taken at each scrape
    extended_documentation: 0=PAUSED, 1=UNPAUSED, 2=NOT_SCHEDULED
    unit: "{status}"
    gauge:
      value_type: int
    attributes:
      [job_id]
  databricks.tasks.schedule.status:
    enabled: true
    description: A snapshot of the pause/run status per task taken at each scrape
    extended_documentation: 0=PAUSED, 1=UNPAUSED, 2=NOT_SCHEDULED
    unit: "{status}"
    gauge:
      value_type: int
    attributes:
      [job_id, task_id, task_type]
  databricks.jobs.active.total:
    enabled: true
    description: A snapshot of the number of active jobs taken at each scrape
    unit: "{jobs}"
    gauge:
      value_type: int
  databricks.jobs.run.duration:
    enabled: true
    description: The execution duration in milliseconds per completed job
    unit: ms
    gauge:
      value_type: int
    attributes:
      [job_id]
  databricks.tasks.run.duration:
    enabled: true
    description: The execution duration in milliseconds per completed task
    unit: ms
    gauge:
      value_type: int
    attributes:
      [job_id, task_id]