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References → Save MV Recipe

The Save MV recipe is the final step of any data flow. The save MV recipe will take all the upstream logic of the data flow and deploy it into a physical schema as a Materialized View (MV) written in PySpark.

Important: Incremental Mode

For the releases of 2024.1.5, 2024.1.6, 2024.7.0, 2024.7.1, activating the Incremental Mode toggle on this Recipe will result in failure to deploy the Dataflow to publish to the target Schema. Turn off Incremental Mode, deploy, then edit the incremental logic in the Physical Schema.

This issue has been resolved in 2024.1.7 and 2024.7.2.

Configuration

ConfigurationDescription
InputSelect a previously constructed recipe as an input
SchemaSelect a schema to save the data flow logic to
MV NameGive a name to the MV to be created
Enable MV Incremental ModeToggle on this option to deploy the MV with incremental mode set to true.
Spark Properties → + Add PropertySelect Add Property to configure Spark properties by defining key–value pairs. You can add, edit, or delete configurations as needed.
Note: This configuration option is available starting 2026.2.0.

Previewing the Code

To review the code generated in the data flow, select the desired recipe and select Preview Code

Deploying the Data Flow

Now that you have saved the Save MV recipe, you have two options for deployment.

  1. With the Save MV recipe highlighted, select Deploy from the More Options (⋮) menu in the Action bar.

  2. With the Save MV recipe highlighted, select Deploy from the toolbar.

Note

Deploying an MV will overwrite any existing MV with the same name in the same physical schema.