Roadmap - Shutdown Docs AE Glossary

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/test-terms.md

@@ -0,0 +1,20 @@
+---
+title: "Testing Terms component"
+id: "test-terms"
+pagination_next: null
+pagination_prev: null
+---
+
+This should show a term: <Term id="deploying">Deploying</Term>
+
+This should show a term: <Term id="data-wrangling">Data wrangling</Term>
+
+This should show a term: <Term id="model">Model</Term>
+
+This should show demoTerm: <Term id="demoTerm" />
+
+This should show noDisplayText term id as children and displayText not set: <Term id="noDisplayText" />
+
+This has displayText set but no hoverSnippet set: <Term id="noHoverSnippet" />
+
+This should NOT show a hover snippet (but should still show children): <Term id="demo">Demo</Term>

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