--- title: dbt - Deployment description: Run the generated dbt project with dbt run to create the tables and views of your solution and load them. --- [Skip to content](https://knowledge.bigenius-x.com/dbt-deployment#main-content) [Contact us](https://knowledge.bigenius-x.com/kb-tickets/new?hsLang=en) [Go to Customer Portal](https://knowledge.bigenius-x.com/customer-portal?hsLang=en) [![TRI\_Logo\_biGENIUS\_2020\_RGB\_s](https://knowledge.bigenius-x.com/hs-fs/hubfs/Marketing/TRI_Logo_biGENIUS_2020_RGB_s.png?width=150&height=42&name=TRI_Logo_biGENIUS_2020_RGB_s.png)](https://www.bigenius-x.com/) Open main navigation Close main navigation - [Contact us](https://knowledge.bigenius-x.com/kb-tickets/new) - [Go to Customer Portal](https://knowledge.bigenius-x.com/customer-portal) How can we help you? - There are no suggestions because the search field is empty. 1. [biGENIUS-X Knowledge Base](https://knowledge.bigenius-x.com/?hsLang=en) 2. [Generators](https://knowledge.bigenius-x.com/generators?hsLang=en) 3. [Deployment](https://knowledge.bigenius-x.com/generators?hsLang=en#deployment) # dbt - Deployment **Applies to** Platform: Snowflake dbt · Databricks dbt Run the generated dbt project with `dbt run` to create the tables and views of your solution and load them. dbt builds the models in dependency order, from Stage through Raw Vault to Business Vault. Afterwards the target schemas hold the loaded tables, and each later run adds the new source data. A dbt project has no separate deployment and no load control. The first `dbt run` creates the objects, and every run loads them in the order of their references. dbt takes the place of the load control described in [Understand Load Control](https://knowledge.bigenius-x.com/understand-load-control?hsLang=en). ### Prerequisites - The target environment is prepared: - Snowflake dbt: no target environment article available yet - Databricks dbt: [Target environment](https://knowledge.bigenius-x.com/databricks-dbt-target-environment?hsLang=en) - The artifacts are [generated](https://knowledge.bigenius-x.com/generate-artifacts?hsLang=en) and [downloaded](https://knowledge.bigenius-x.com/download-generated-artifacts?hsLang=en). - The values in `dbt_project.yml` are set, see [dbt - Placeholder values](https://knowledge.bigenius-x.com/dbt-placeholder-values?hsLang=en). ### Run the project for the first time 1. Open a terminal in the artifacts folder, the folder that contains `dbt_project.yml`. 2. Run `dbt debug`. The output ends with `All checks passed!`. 3. Run `dbt run`. dbt prints a line for each model it starts and finishes, and a summary at the end. On the first run, each model of an object with Implementation Type `Permanent` creates its table from the model's SQL. A Hub table, for example, receives the business keys of the source and the unknown-member row. Objects with Implementation Type `Cached`, such as Stage by default, create tables. `_source` models and `Virtual` objects create views. ### Load new source data Run `dbt run` again whenever the sources hold new data. On later runs the models behave as follows: - Stage tables are rebuilt with the current source data. - Hub and Link models insert only keys that are not yet in their table. Satellite models insert new versions. - The post-hook `bg_close_validity_merge` of historized satellites and PITs sets `BG_ValidToTimestamp` of the previous version. - All models of one run write the same `BG_LoadTimestamp`: the start time of the dbt run, in whole seconds. - New terms of a model object become new columns of the existing table. Columns of removed terms stay in the table. A model reads only new source rows when its `BG_IncrementalFilter` is mapped to the source's `BG_LoadTimestamp`. It then reads the rows whose `BG_LoadTimestamp` is later than the latest one in its table. Without this mapping it reads all source rows on every run. When `BG_IncrementalFilter` is mapped to another term, validation reports the warning `Model object has an incremental filter that is not mapped to the source's BG_LoadTimestamp. No dbt incremental read filter applied.` See [Configure an incremental load](https://knowledge.bigenius-x.com/configure-an-incremental-load?hsLang=en). ### Run part of the project Use `--select` with the [dbt selection syntax](https://docs.getdbt.com/reference/node-selection/syntax). The model names follow [dbt - Artifacts](https://knowledge.bigenius-x.com/dbt-artifacts?hsLang=en). Examples: - `dbt run --select path:models/rawvault` runs only the Raw Vault models and reads the existing Stage tables. - `dbt run --select +` runs a model and every model it reads from. - `dbt run --select +` runs a model and every model that reads from it. - `dbt run --select source:+` runs the models that read from a source system, directly or indirectly. ### Model objects with more than one dataflow A model object with more than one dataflow has an owner model with the model object's name and one loader per dataflow. The owner model creates the empty table on the first run, with the unknown-member row where the type has one. Each loader `__loader` then inserts the rows of its dataflow, after the loader of the previous dataflow. The owner model reads no source. A selection such as `source:+` therefore leaves it out, while `+` with the name of a loader model includes it. ### Full refresh With `--full-refresh`, dbt drops the tables of Hubs, Links, Satellites and the other Raw Vault and Business Vault objects and rebuilds them from the data that the sources hold now. History that the sources no longer hold is lost. Back up these tables before a full refresh, or exclude them from the selection. `dbt run --full-refresh` builds the selected models as on the first run. For an existing table of a `bg_` materialization, dbt drops the table and creates it again from the model's SQL. Loaders skip the full refresh, so a refreshed owner table is created empty and the loaders insert the rows of their dataflows again. ### Data Mart projects on Databricks dbt - A project with the configuration [`Databricks Dbt DataMart`](https://knowledge.bigenius-x.com/databricks-dbt-datamart?hsLang=en) reads the tables of its linked projects as dbt sources. dbt does not run the linked project, so load it before you run this project. - In a project with the configuration [`Databricks Dbt DataVault & Mart`](https://knowledge.bigenius-x.com/databricks-dbt-datavault-and-mart?hsLang=en), one `dbt run` builds Stage, Raw Vault, Business Vault and Mart in dependency order. `--select path:models/mart` runs only the Mart models on the existing vault tables. `--select +` on a Mart model includes the vault and Stage models it reads. ### Check the result A run without errors ends with `Completed successfully`, followed by a line that starts with `Done. PASS=` and counts the models. Query a table of each layer to check the rows, for example `SELECT * FROM ._rawvault.rdv_hub_common_customer`. ### Example To load the Satellite `common_customer` together with the models it depends on, first list the selection: ``` dbt ls --select +rdv_sat_common_customer --output name ``` dbt lists eight models and two source tables. The Satellite and its Hub read the Stage objects `st_customer` and `st_phonenumber`, which read the tables of the source system `bfmmssql`: ``` rdv_hub_common_customer rdv_hub_common_customer_source rdv_sat_common_customer rdv_sat_common_customer_source stg_st_customer stg_st_customer_source stg_st_phonenumber stg_st_phonenumber_source bfmmssql.customer bfmmssql.phonenumber ``` `dbt run --select +rdv_sat_common_customer` runs the eight models in dependency order: the Stage models first, then the Hub, then the Satellite. ### Failure symptoms and recovery #### dbt does not find the profile Message: `Could not find profile named ''` Cause: `profile` in `dbt_project.yml` is not set. Fix: Set the values as described in [dbt - Placeholder values](https://knowledge.bigenius-x.com/dbt-placeholder-values?hsLang=en) and run again. #### A model stops after the partitioning changed Message: `Partition columns changed for — Delta Lake does not support ALTER TABLE to change partitioning. Run with --full-refresh to recreate the table.` Cause: [Optimization Method](https://knowledge.bigenius-x.com/optimization-method-model-object?hsLang=en) or [Optimization Method Columns](https://knowledge.bigenius-x.com/optimization-method-columns-model-object?hsLang=en) of the model object now gives other partition columns than the existing table has. Databricks dbt only; changes of `Cluster By` are applied with `ALTER TABLE` without an error. Fix: Set the previous partition columns again, or recreate the table of this model with a full refresh. Read the warning in [Full refresh](https://knowledge.bigenius-x.com/dbt-deployment#full-refresh) first: the table loses the history that the sources no longer hold. #### A model fails and dbt skips the models that depend on it Cause: An error in one model, for example a missing source table. dbt marks the models that read from it as skipped. Fix: Correct the cause, then run `dbt retry`. dbt runs the failed and skipped models of the previous run again. For failures in other steps, see [Troubleshoot generation, deployment and load failures](https://knowledge.bigenius-x.com/troubleshoot-generation-deployment-and-load-failures?hsLang=en). ### Platform differences - Snowflake dbt: each layer runs on the warehouse of its `+snowflake_warehouse` value. The project has no `process_config_changes` macro, so the partition check of [A model stops after the partitioning changed](https://knowledge.bigenius-x.com/dbt-deployment#a-model-stops-after-the-partitioning-changed) does not apply. - Databricks dbt: the macro `process_config_changes` compares the partitioning, clustering and table properties of existing tables with the model, and stops a model whose partition columns changed. ### Related articles - Previous: [Generate artifacts](https://knowledge.bigenius-x.com/generate-artifacts?hsLang=en), [Download generated artifacts](https://knowledge.bigenius-x.com/download-generated-artifacts?hsLang=en), [dbt - Placeholder values](https://knowledge.bigenius-x.com/dbt-placeholder-values?hsLang=en) - Snowflake dbt: no target environment article available yet - Databricks dbt: [Target environment](https://knowledge.bigenius-x.com/databricks-dbt-target-environment?hsLang=en) - Reference: [Implementation Type (Model Object)](https://knowledge.bigenius-x.com/implementation-type-model-object?hsLang=en), [Optimization Method (Model Object)](https://knowledge.bigenius-x.com/optimization-method-model-object?hsLang=en), [Optimization Method Columns (Model Object)](https://knowledge.bigenius-x.com/optimization-method-columns-model-object?hsLang=en), [Persist Validity (Project)](https://knowledge.bigenius-x.com/persist-validity-project?hsLang=en) - 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