[Feature] Inject invocation_id into user_agent for BigQuery for better tracking in Logs Explorer

### Is this your first time submitting a feature request?

- [x] I have read the [expectations for open source contributors](https://docs.getdbt.com/docs/contributing/oss-expectations)
- [x] I have searched the existing issues, and I could not find an existing issue for this feature
- [x] I am requesting a straightforward extension of existing dbt functionality, rather than a Big Idea better suited to a discussion

### Describe the feature

> Caveat: not a GCP expert by any means.

When we run any SQL statement (however trivial) on BigQuery - GCP appear to break that out into many individual log events in the log explorer. Lets look at a quick example:

```yaml
# dbt_project.yml
name: analytics
profile: all
version: "1.0.0"

models:
analytics:
+materialized: table
```

```sql
-- models/foo.sql
select 1 c
```

```sh
$ dbt --debug run

03:52:57 Got an exception trying to initialize tracking
03:52:57 Running with dbt=1.10.9
03:52:57 running dbt with arguments {'log_format': 'default', 'log_path': '/Users/jeremy/git/dbt-basic/logs', 'indirect_selection': 'eager', 'version_check': 'True', 'cache_selected_only': 'False', 'use_colors': 'True', 'introspect': 'True', 'send_anonymous_usage_stats': 'True', 'warn_error_options': 'WarnErrorOptionsV2(error=[], warn=[], silence=[])', 'use_experimental_parser': 'False', 'printer_width': '80', 'write_json': 'True', 'invocation_command': 'dbt --debug run', 'log_cache_events': 'False', 'no_print': 'None', 'target_path': 'None', 'fail_fast': 'False', 'partial_parse': 'True', 'warn_error': 'None', 'empty': 'False', 'profiles_dir': '/Users/jeremy/.dbt', 'debug': 'True', 'static_parser': 'True', 'quiet': 'False'}
03:52:59 Registered adapter: bigquery=1.10.1
03:52:59 checksum: 6543b8b248ceda473ef0d611849d5d909085b6b714afa9b515e9635faea7af23, vars: {}, profile: , target: , version: 1.10.9
03:52:59 Unable to do partial parsing because a project config has changed
03:53:00 Wrote artifact WritableManifest to /Users/jeremy/git/dbt-basic/target/manifest.json
03:53:00 Wrote artifact SemanticManifest to /Users/jeremy/git/dbt-basic/target/semantic_manifest.json
03:53:00 Found 1 model, 496 macros
03:53:00
03:53:00 Concurrency: 4 threads (target='bq')
03:53:00
03:53:00 Acquiring new bigquery connection 'master'
03:53:00 Acquiring new bigquery connection 'list_cse-sandbox-319708'
03:53:00 Opening a new connection, currently in state init
03:53:02 Re-using an available connection from the pool (formerly list_cse-sandbox-319708, now list_cse-sandbox-319708_dbt_jyeo)
03:53:02 Opening a new connection, currently in state closed
03:53:03 Opening a new connection, currently in state init
03:53:03 Began running node model.analytics.foo
03:53:03 1 of 1 START sql table model dbt_jyeo.foo ...................................... [RUN]
03:53:03 Re-using an available connection from the pool (formerly list_cse-sandbox-319708_dbt_jyeo, now model.analytics.foo)
03:53:03 Began compiling node model.analytics.foo
03:53:03 Writing injected SQL for node "model.analytics.foo"
03:53:03 Began executing node model.analytics.foo
03:53:03 Opening a new connection, currently in state closed
03:53:04 Writing runtime sql for node "model.analytics.foo"
03:53:04 On model.analytics.foo: /* {"app": "dbt", "dbt_version": "1.10.9", "profile_name": "all", "target_name": "bq", "node_id": "model.analytics.foo"} */
create or replace table `cse-sandbox-319708`.`dbt_jyeo`.`foo`
OPTIONS()
as (
select 1 c
);
03:53:05 BigQuery adapter: https://console.cloud.google.com/bigquery?project=cse-sandbox-319708&j=bq:US:ce121c01-395a-47ca-88e2-28d7d0a7b531&page=queryresults
03:53:07 1 of 1 OK created sql table model dbt_jyeo.foo ................................. [CREATE TABLE (1.0 rows, 0 processed) in 3.91s]
03:53:07 Finished running node model.analytics.foo
03:53:07 Opening a new connection, currently in state closed
03:53:07 Connection 'master' was properly closed.
03:53:07 Connection 'model.analytics.foo' was properly closed.
03:53:07
03:53:07 Finished running 1 table model in 0 hours 0 minutes and 7.20 seconds (7.20s).
03:53:07 Command end result
03:53:07 Wrote artifact WritableManifest to /Users/jeremy/git/dbt-basic/target/manifest.json
03:53:07 Wrote artifact SemanticManifest to /Users/jeremy/git/dbt-basic/target/semantic_manifest.json
03:53:07 Wrote artifact RunExecutionResult to /Users/jeremy/git/dbt-basic/target/run_results.json
03:53:07
03:53:07 Completed successfully
03:53:07
03:53:07 Done. PASS=1 WARN=0 ERROR=0 SKIP=0 NO-OP=0 TOTAL=1
03:53:07 Resource report: {"command_name": "run", "command_success": true, "command_wall_clock_time": 9.875144, "process_in_blocks": "0", "process_kernel_time": 0.488256, "process_mem_max_rss": "391938048", "process_out_blocks": "0", "process_user_time": 2.570171}
03:53:07 Command `dbt run` succeeded at 15:53:07.533506 after 9.88 seconds
03:53:07 Flushing usage events
```

A single `create or replace ...` statement was sent to BQ.

Observations:

### BQ Job History UI

From the BQ Job History UI, we can see the entry and the associated query + the dbt invocation id - so we can tie that back to the dbt invocation.

### GCP Logs Explorer

That singular SQL statement execution had materialized into 7 different log entries in GCP Logs Explorer. (I cannot explain why this became 7 log entries but I will call this "GCP Backend Operations").

^ Within the 7 entries, 3 of them:

* methodName: "jobservice.getqueryresults"
* methodName: "jobservice.jobcompleted"
* methodName: "jobservice.insert"

Will show `jobConfiguration.labels.dbt_invocation_id: "5d52c585-4241-4058-b4b6-a5dd73e95959"`

The other 4:
* methodName: "google.cloud.bigquery.v2.JobService.InsertJob"
* methodName: "google.cloud.bigquery.v2.JobService.InsertJob"
* methodName: "google.cloud.bigquery.v2.JobService.InsertJob"
* methodName: "google.cloud.bigquery.v2.JobService.InsertJob"

Do not have any keys that reflect the invocation id.

All 7 of them will have a user agent key:

```
requestMetadata.callerSuppliedUserAgent: "dbt-bigquery-1.10.1 gl-python/3.11.9 grpc/1.74.0 gax/2.25.1 gapic/3.35.1 gccl/3.35.1,gzip(gfe)"
```

The proposal is to inject the invocation id into the user agent string so we can see something like:

```
requestMetadata.callerSuppliedUserAgent: "dbt-bigquery-1.10.1 5d52c585-4241-4058-b4b6-a5dd73e95959 gl-python/3.11.9 grpc/1.74.0 gax/2.25.1 gapic/3.35.1 gccl/3.35.1,gzip(gfe)"
```

P.s. this single statement / BQ Job entry into N GCP log explorer entries (aka "GCP Backend Operations") is not specific to dbt. Simply running a create statement in the BQ UI itself will also do this.

### Describe alternatives you've considered

NA

### Who will this benefit?

Large enterprise customers looking to attribute dbt invocations to each log line in their audit tool / Logs explorer.

### Are you interested in contributing this feature?

_No response_

### Anything else?

We can probably import the invocation_id generating method and inject it here:

https://github.com/dbt-labs/dbt-adapters/blob/87e81a47baa11c312003377091a9efc0ab72d88e/dbt-bigquery/src/dbt/adapters/bigquery/clients.py#L67

Maybe something like:

```python
# dbt-bigquery/src/dbt/adapters/bigquery/clients.py
from dbt_common.invocation import get_invocation_id

...

@BQ_DEFAULT_RETRY
def _create_bigquery_client(credentials: BigQueryCredentials) -> BigQueryClient:
return BigQueryClient(
credentials.execution_project,
create_google_credentials(credentials),
location=getattr(credentials, "location", None),
client_info=ClientInfo(user_agent=f"dbt-bigquery-{dbt_version.version} invocation_id:{get_invocation_id()}"),
client_options=ClientOptions(
quota_project_id=credentials.quota_project, api_endpoint=credentials.api_endpoint
),
)

...
```