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Comment: Published by Scroll Versions from space DEV and version r0810

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Excerpt

You can use the Job Details page to explore details about successful or failed jobs, including outputs, dependency graph, and other metadata. Download results to your local desktop or, if enabled, explore a visual profile of the data in the results for further iteration on your recipe.

Page options:

  • Cancel job: Click this button to cancel your job while it is still in progress.

    Info

    NOTE: This option may not be available for all running environments.

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    NOTE: If you do not have permission to cancel a

    D s dataflow
    job, the appropriate permissions must be added to your IAM role by an administrator. The default IAM role available with the product has these permissions, but these permissions may not be present if you are using a custom or personal IAM role in your account. For more information on IAM permissions, see Required Dataprep User Permissions .

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    NOTE: In some cases, the product is unable to cancel the job from the application. In these cases, click View in Dataflow, and from there you can cancel the job in progress .  


  • View dataflow job: View the job that was executed on

    D s dataflow
    .

  • View BigQuery job: If the job was able to be executed in BigQuery, you can review the job in the BigQuery console.

    InfoNOTE: When you view

    View dataflow job: View the job that was executed on

    D s dataflow
    .

  • View BigQuery job: If the job was able to be executed in BigQuery, you can review the job in the BigQuery console.

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    NOTE: When you view the job in BigQuery, you are using your own credentials to access the BigQuery console, which may be different from the service account that was used to execute the job. In this case, the job in BigQuery may be reported having errors when viewed using your credentials, when the job succeeded using the service account. To see the job properly, the bigquery.jobs.get and bigquery.jobs.list permissions must be added to your account. For more information, see Required Dataprep User Permissions.

    • Jobs can be executed in BigQuery if all data sources and outputs are located in BigQuery. Additional requirements apply. For more information, see Overview of Job Execution.
  • Download profile as PDF: If visual profiling was enabled for the job, you can download the profile in PDF format.
  • Download profile as JSON: If visual profiling was enabled for the job, you can download a JSON representation of the profile to your desktop.

    Tip

    Tip: When you download your JSON profile, any rules applied to the generated results are included in the profile. Search for profilerRules.

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NOTE: If a flow is unshared with you, you cannot see or access the datasources for any jobs that you have already run on the flow, including any PDF profiles that you generated. You can still access the job results. This is a known issuethat you have already run on the flow, including any PDF profiles that you generated. You can still access the job results. This is a known issue.

Datasets with parameters:

If your source is a dataset with parameters, you can review and count the individual files that were matched and imported.

  • For the imported dataset, click View details. Then, click the Files tab in the context panel.
  • This tab can be a good check to ensure that you have specified your dataset parameters correctly.

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Parameters Tab

If your flow references parameters, you can review the state of the parameters at the time of job execution.

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