Merge branch 'current' into update-ratio-metrics

website/docs/docs/build/incremental-models.md

@@ -94,7 +94,7 @@ Not specifying a `unique_key` will result in append-only behavior, which means d
 
 The optional `unique_key` parameter specifies a field (or combination of fields) that defines the grain of your model. That is, the field(s) identify a single unique row. You can define `unique_key` in a configuration block at the top of your model, and it can be a single column name or a list of column names.
 
-The `unique_key` should be supplied in your model definition as a string representing a single column or a list of single-quoted column names that can be used together, for example, `['col1', 'col2', …])`. Columns used in this way should not contain any nulls, or the incremental model run may fail. Either ensure that each column has no nulls (for example with `coalesce(COLUMN_NAME, 'VALUE_IF_NULL')`), or define a single-column [surrogate key](/terms/surrogate-key) (for example with [`dbt_utils.generate_surrogate_key`](https://github.com/dbt-labs/dbt-utils#generate_surrogate_key-source)).
+The `unique_key` should be supplied in your model definition as a string representing a single column or a list of single-quoted column names that can be used together, for example, `['col1', 'col2', …])`. Columns used in this way should not contain any nulls, or the incremental model run may fail. Either ensure that each column has no nulls (for example with `coalesce(COLUMN_NAME, 'VALUE_IF_NULL')`), or define a single-column [surrogate key](https://www.getdbt.com/blog/guide-to-surrogate-key) (for example with [`dbt_utils.generate_surrogate_key`](https://github.com/dbt-labs/dbt-utils#generate_surrogate_key-source)).
 
 :::tip
 In cases where you need multiple columns in combination to uniquely identify each row, we recommend you pass these columns as a list (`unique_key = ['user_id', 'session_number']`), rather than a string expression (`unique_key = 'concat(user_id, session_number)'`).
@@ -103,15 +103,15 @@ By using the first syntax, which is more universal, dbt can ensure that the colu
 
 When you pass a list in this way, please ensure that each column does not contain any nulls, or the incremental model run may fail.
 
-Alternatively, you can define a single-column [surrogate key](/terms/surrogate-key), for example with [`dbt_utils.generate_surrogate_key`](https://github.com/dbt-labs/dbt-utils#generate_surrogate_key-source).
+Alternatively, you can define a single-column [surrogate key](https://www.getdbt.com/blog/guide-to-surrogate-key), for example with [`dbt_utils.generate_surrogate_key`](https://github.com/dbt-labs/dbt-utils#generate_surrogate_key-source).
 :::
 
 When you define a `unique_key`, you'll see this behavior for each row of "new" data returned by your dbt model:
 
 * If the same `unique_key` is present in the "new" and "old" model data, dbt will update/replace the old row with the new row of data. The exact mechanics of how that update/replace takes place will vary depending on your database, [incremental strategy](/docs/build/incremental-strategy), and [strategy specific configs](/docs/build/incremental-strategy#strategy-specific-configs).
 * If the `unique_key` is _not_ present in the "old" data, dbt will insert the entire row into the table.
 
-Please note that if there's a unique_key with more than one row in either the existing target table or the new incremental rows, the incremental model may fail depending on your database and [incremental strategy](/docs/build/incremental-strategy). If you're having issues running an incremental model, it's a good idea to double check that the unique key is truly unique in both your existing database table and your new incremental rows. You can [learn more about surrogate keys here](/terms/surrogate-key).
+Please note that if there's a unique_key with more than one row in either the existing target table or the new incremental rows, the incremental model may fail depending on your database and [incremental strategy](/docs/build/incremental-strategy). If you're having issues running an incremental model, it's a good idea to double check that the unique key is truly unique in both your existing database table and your new incremental rows. You can [learn more about surrogate keys here](https://www.getdbt.com/blog/guide-to-surrogate-key).
 
 :::info
 While common incremental strategies, such as`delete+insert` + `merge`, might use `unique_key`, others don't. For example, the `insert_overwrite` strategy does not use `unique_key`, because it operates on partitions of data rather than individual rows. For more information, see [About incremental_strategy](/docs/build/incremental-strategy).

website/docs/docs/dbt-versions/release-notes.md

@@ -20,6 +20,7 @@ Release notes are grouped by month for both multi-tenant and virtual private clo
 
 ## October 2024
 
+- **Enhancement**: In dbt Cloud Versionless, snapshots defined in SQL files can now use `config` defined in `schema.yml` YAML files. This update resolves the previous limitation that required snapshot properties to be defined exclusively in `dbt_project.yml` and/or a `config()` block within the SQL file. This enhancement will be included in the upcoming dbt Core v1.9 release.
 - **New:** dbt Explorer now includes trust signal icons, which is currently available as a [Preview](/docs/dbt-versions/product-lifecycles#dbt-cloud). Trust signals offer a quick, at-a-glance view of data health when browsing your dbt models in Explorer. These icons indicate whether a model is **Healthy**, **Caution**, **Degraded**, or **Unknown**. For accurate health data, ensure the resource is up-to-date and has had a recent job run. Refer to [Trust signals](/docs/collaborate/explore-projects#trust-signals-for-resources) for more information. 
 - **New:** Auto exposures are now available in Preview in dbt Cloud. Auto-exposures helps users understand how their models are used in downstream analytics tools to inform investments and reduce incidents. It imports and auto-generates exposures based on Tableau dashboards, with user-defined curation. To learn more, refer to [Auto exposures](/docs/collaborate/auto-exposures).
 

website/docs/reference/snapshot-configs.md

@@ -80,7 +80,31 @@ snapshots:
 
 <TabItem value="property-yaml">
 
-**Note:** Required snapshot properties _will not_ work when defined in `config` YAML blocks. We recommend that you define these in `dbt_project.yml` or a `config()` block within the snapshot `.sql` file.
+<VersionBlock lastVersion="1.8">
+
+**Note:** Required snapshot properties _will not_ work when only defined in `config` YAML blocks. We recommend that you define these in `dbt_project.yml` or a `config()` block within the snapshot `.sql` file or upgrade to v1.9.
+
+</VersionBlock>
+
+<VersionBlock firstVersion="1.9">
+
+<File name='snapshots/schema.yml'>
+
+```yml
+snapshots:
+  - name: <string>
+    config:
+      database: <string>
+      schema: <string>
+      unique_key: <column_name_or_expression>
+      strategy: timestamp | check
+      updated_at: <column_name>
+      check_cols: [<column_name>] | all
+
+```
+</File>
+
+</VersionBlock>
 
 </TabItem>
 

website/docs/sql-reference/aggregate-functions/sql-sum.md

@@ -11,7 +11,7 @@ slug: /sql-reference/sum
 
 The SQL SUM function is handy and ever-present in data work. Let’s unpack what it is, how to use it, and why it's valuable.
 
-Jumping into it, the SUM aggregate function allows you to calculate the sum of a numeric column or across a set of rows for a column. Ultimately, the SUM function is incredibly useful for calculating meaningful business metrics, such as Lifetime Value (LTV), and creating key numeric fields in [`fct_` and `dim_` models](/terms/dimensional-modeling).
+Jumping into it, the SUM aggregate function allows you to calculate the sum of a numeric column or across a set of rows for a column. Ultimately, the SUM function is incredibly useful for calculating meaningful business metrics, such as Lifetime Value (LTV), and creating key numeric fields in [`fct_` and `dim_` models](https://www.getdbt.com/blog/guide-to-dimensional-modeling).
 
 ## How to use the SUM function in a query