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NOTE: Avoid creating datasets with parameters where individual files or tables have differing schemas. Either import these sources separately and then correct in the application before performing a union on the datasets, or make corrections in the source application to standardize the schemas. |
When working with datasets with parameters, it may be useful to do the following if you expect the underlying datasets to be less than 100% consistent with each other.
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- In the Import Data page, navigate your environment to locate one of the files or tables that you wish to parameterize.
Click Create Dataset with Parameters.
D caption Create Dataset with Parameters
- Within the Define Parameterized Path, select a segment of text. Then select one of the following options:
Tip /) as part of your parameterized value.- Add Datetime Parameter
- Add Variable
- Add Pattern Parameter - wildcards and patterns
- For more information on limitations, see Overview of Parameterization.
- If you need to navigate elsewhere, select Browse.
- Specify the parameter. Click Save.
Click Update matches. Verify that all of your preferred datasets are matching.
Info NOTE: If you are matching with more datasets than you wish, you should review your parameters.
Click Create.
The parameterized dataset is loaded. See Import Data Page.
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For example, suppose you have two environments: Dev and Prod. You can create an environment parameter called env.sourceBucketName to store the name of the bucket from which all data in the workspace or project is imported.
| Environment Name | Source Bucket Name | Environment Parameter Value | ||
|---|---|---|---|---|
| Dev | MyCo_Dev |
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| Prod | MyCo_Prod |
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For more information, see Overview of Parameterization.
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