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  1. on a specified set of rows (firstrows)
  2. on a quick scan across the dataset 

    TipTip: Quick scan
    1. By default, Quick Scan samples are executed

    in the
    1. on the 

      D s photon
       running environment. 

    2. If 
      D s photon
       is not available or is disabled, the 
      D s webapp
       attempts to execute the Quick Scan sample on an available clustered running environment
    3. If the clustered running environment is not available or doesn't support Quick Scan sampling, then the Quick Scan sample job fails.
  3. on a full scan of the entire dataset 

    tip

    Tip:

    1. Full

    scan
    1. Scan samples are executed in the cluster running environment.

Sampling mechanics

When a non-initial sample is executed for a single dataset-recipe combination, the following steps occur:

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  • Parameters: Subsequent samples generated from the Transformer page are sampled across all datasets matched by parameter values.
  • Variables: You can apply override values to the defaults for your dataset's variables at sample execution time. In this manner, you can draw your samples from specific sources files within your dataset with parameters.

Samples management

After you have created a sample, you cannot delete it through the application.

Info

NOTE:

D s product
does not delete samples after they have been created. If you are concerned about data accumulation, you should configure periodic purges of the appropriate directories on the base storage layer. For more information, please contact your IT administrator.

For more information, see Sample Jobs Page.

Cancel Sample Jobs

Generating a sample can consume significant time, system resources, and in some deployments cost. As needed, you can cancel a sample job that is in progress in either of the following ways:

  • Locate the in-progress sampling job in the Samples panel. Click X.
  • Click the Jobs icon in the left nav bar. Select Sample jobs. For more information, see Sample Jobs Page.

Choosing Samples

After you have collected multiple samples of multiple types on your dataset, you can choose the proper sample to use for your current task, based on:

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