Available for Enterprise Edition only.
Type & Format
BigQuery supports the following materialization types for target models. The type determines the underlying physical format of your target model.| Materialization type | Description |
|---|---|
| View (default) | Rebuilt as a view on each run. Views always reflect the latest source data but don’t store any data themselves. |
| Table | Rebuilt as a table on each run. Tables are fast to query but can take longer to build. Target tables support multiple write modes. |
| Ephemeral | Not built in the database. The model’s logic is inlined into downstream models using a common table expression (CTE). Use for lightweight transformations early in your DAG. |
| Materialized View | Acts like a hybrid of a view and a table. Supports use cases similar to incremental models. Creates a materialized view in the target warehouse. |
Location
Review the location where your model will be written. Any changes you make to the Overwrite location section will be reflected in the Location that Prophecy generates.| Location Parameter | Description | Advanced mode |
|---|---|---|
| Project ID | Google Cloud project where the model will be built. | Yes |
| Database (BigQuery dataset) | Name of the BigQuery dataset where the model will be created. Acts as the schema in BigQuery. | Yes |
| Alias | Sets the name of the resulting table or view. Defaults to the model name if not specified. | No |
Schema
Define the schema of the dataset and optionally configure additional properties. The schema includes column names, column data types, and optional column metadata. When you expand a row in the Schema table, you can add a column description, apply column tags, and enable/disable quoting for column names.Properties
Each property maps to a certain dbt configuration that may be generic to dbt or specific to a platform like BigQuery. If you do not add a property explicitly in the Schema tab, Prophecy uses the dbt default for that property.| Property | Description | Config type |
|---|---|---|
| Dataset Tags | Add tags to the dataset. These tags can be used as part of the resource selection syntax in dbt. | Generic |
| Contract Enforced | Enforce a contract for the model schema, preventing unintended changes. | Generic |
| Show Docs | Control whether or not nodes are shown in the auto-generated documentation website. | Generic |
| Enabled | Control whether the model is included in builds. When a resource is disabled, dbt will not consider it as part of your project. | Generic |
| Meta | Set metadata for the table using key-value pairs. | Generic |
| Group | Assign a group to the table. | Generic |
| Persist Docs Columns | Save column descriptions in the database. | Generic |
| Persist Docs Relations | Save model descriptions in the database. | Generic |
| Cluster By | Cluster data in the table by the values of specified columns to improve query performance and reduce costs. | BigQuery |
| Partition Expiration Days | If using date or timestamp partitions, this property defines the number of days from the partition date to expiration. | BigQuery |
| Require Partition Filter | Requires anyone querying this model to specify a partition filter, otherwise their query will fail. | BigQuery |
| Time Ingestion Partitioning | Enables partitioning based on when data is ingested into the table, using BigQuery’s _PARTITIONTIME column. | BigQuery |
For more detailed information, see the dbt reference
documentation.