Nfiann-bigquery-cloud-config

website/docs/docs/cloud/connect-data-platform/connnect-bigquery.md

@@ -52,6 +52,114 @@
 
 To learn how to optimize performance with data platform-specific configurations in dbt Cloud, refer to [BigQuery-specific configuration](/reference/resource-configs/bigquery-configs).
 
+### Optional configurations
+
+In BigQuery, optional configurations let you tailor settings for tasks such as running queries, loading or exporting data, and creating tables. While not necessary for basic operations, these options give you greater control over how BigQuery functions behind the scenes to meet your requirements.
+
+To customize your optional configurations in dbt Cloud:
+
+- Select your BigQuery project from the left-hand menu
+- Click **Settings** towards the top right
+- Scroll down to **Development Connection** and select BigQuery
+- Click **Edit** and then scroll down to **Optional settings**
+
+<Lightbox src="/img/bigquery/bigquery-optional-config.png" width="70%" title="BigQuery optional configuration"/>
+
+The following are the optional configs you can set in dbt Cloud:
+
+#### Priority
+
+The `priority` for the BigQuery jobs that dbt executes can be configured with the `priority` configuration in your BigQuery profile. The priority field can be set to one of `batch` or `interactive`. For more information on query priority, consult the [BigQuery documentation](https://cloud.google.com/bigquery/docs/running-queries).
+
+#### Retries
+
+Retries in BigQuery help to ensure that jobs complete successfully by trying again after temporary failures, making your operations more robust and reliable.
+
+#### Location
+
+The `location` of BigQuery datasets can be set using the `location` setting in a BigQuery profile. As per the [BigQuery documentation](https://cloud.google.com/bigquery/docs/locations), `location` may be either a multi-regional location (e.g. `EU`, `US`), or a regional location (e.g. `us-west2`).
+
+You can specify the `location` parameter in your `dbt_project.yml` file or in your `models'` configuration. You can set the `location` to either a multi-regional location (e.g., `US`, `EU`) or a regional location such as `us-west2`.
+
+```yml
+
+models:
+  my_project:
+    +location: 'us-west2'  # Set the BigQuery dataset location
+
+```
+
+
+
+#### Maximum bytes build
+
+When a `maximum_bytes_billed` value is configured for a BigQuery profile, that allows you to limit how much data your query can process. It’s a safeguard to prevent your query from accidentally processing more data than you expect, which could lead to higher costs. Queries executed by dbt will fail if they exceed the configured maximum bytes threshhold. This configuration should be supplied as an integer number of bytes.
+
+```jinja
+
+my-profile:
+  target: dev
+  outputs:
+    dev:
+      type: bigquery
+      method: oauth
+      project: abc-123
+      dataset: my_dataset
+      # If a query would bill more than a gigabyte of data, then
+      # BigQuery will reject the query
+      maximum_bytes_billed: 1000000000
+
+```
+
+Example output:
+
+```
+
+Database Error in model debug_table (models/debug_table.sql)
+  Query exceeded limit for bytes billed: 1000000000. 2000000000 or higher required.
+  compiled SQL at target/run/bq_project/models/debug_table.sql
+
+```
+
+#### Execution project
+
+By default, dbt will use the specified `project`/`database` as both:
+
+1. The location to materialize resources (models, seeds, snapshots, etc), unless they specify a custom project/database config
+2. The GCP project that receives the bill for query costs or slot usage
+
+Optionally, you may specify an execution_project to bill for query execution, instead of the project/database where you materialize most resources.
+
+#### Impersonate service account
+
+This feature allows users authenticating via local OAuth to access BigQuery resources based on the permissions of a service account.
+
+For a general overview of this process, see the official docs for [Creating Short-lived Service Account Credentials](https://cloud.google.com/iam/docs/create-short-lived-credentials-direct).
+
+#### Job retry deadline seconds
+
+Job retry deadline seconds is the maximum amount of time BigQuery will spend retrying a job before it gives up.
+
+#### Job creation timeout seconds
+
+Job creation timeout seconds is the maximum time BigQuery will wait to start the job. If the job doesn’t start within that time, it times out.
+
+#### Google cloud storage bucket
+
+Everything you store in Cloud Storage must be placed inside a [bucket](https://cloud.google.com/storage/docs/buckets). Buckets help you organize your data and manage access to it.
+
+#### Dataproc region
+
+A designated location in the cloud where you can run your data processing jobs efficiently. This region must match the location of your BigQuery dataset if you want to use Dataproc with BigQuery to ensure data doesn't move across regions, which can be inefficient and costly.
+
+For more information on [dataproc regions](https://cloud.google.com/bigquery/docs/locations), refer to the BigQuery documentation.
+
+#### Dataproc cluster name
+
+A unique label you give to your group of virtual machines to help you identify and manage your data processing tasks in the cloud. When you integrate Dataproc with BigQuery, you need to provide the cluster name so BigQuery knows which specific set of resources (the cluster) to use for running the data jobs.
+
+Have a look at [Dataproc's document on Create a cluster](https://cloud.google.com/dataproc/docs/guides/create-cluster) for an overview on how clusters work.
+
 ### Account level connections and credential management
 
 You can re-use connections across multiple projects with [global connections](/docs/cloud/connect-data-platform/about-connections#migration-from-project-level-connections-to-account-level-connections). Connections are attached at the environment level (formerly project level), so you can utilize multiple connections inside of a single project (to handle dev, staging, production, etc.).
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