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NOTE: If multiple datasets within the same flow share the same variable name, they are treated as the same variable. |
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Tip: Type |
Default Value: If the variable value is not overridden at execution time, this value is inserted in the variable location in the path.
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NOTE: When you edit an imported dataset, if a variable is renamed, a new variable is created using the new name. Any override values assigned under the old variable name for the dataset must be re-applied. Instances of the variable and override values used in other imported datasets remain unchanged. |
Parameterize bucket names
You can create environment parameters to specify your bucket names. An environment parameter is a variable name and String value that can be referenced by all users of the environment.
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NOTE: A workspace administrator or project owner can create environment parameters. For more information, see Environment Parameters Page. |
Uses:
- Parameterized bucket names are very useful when you are moving flows between workspaces or projects. When the flow is imported into a new workspace, the environment parameter references the appropriate bucket name in the new workspace.
- If you change source buckets or move data to a new storage bucket, updating the paths to your objects can be as simple as changing the value of the environment parameter where your data is stored.
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.
Add Pattern Parameter
In the screen above, you can see an example of pattern-based parameterization. In this case, you are trying to parameterize the two digits after the value: POS-r.
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