Get Routine
bigquery.get_routine
ActionDatabases & warehousesconnection required
Calls bigquery v2 GET /projects/{projectsId}/datasets/{datasetsId}/routines/{routinesId}.
Gets the specified routine resource by routine ID.
Connection
- Required
- Yes — the node will not save without one
- Auth type
- OAuth 2.0
- Providers
- Google BigQuery
- Secret shape
- {"client_id", "client_secret", "refresh_token"}
- Config it needs
- project_id
- Resolved by
- config.connection_id, else node.connection_id
Configuration
2 fields, 2 required. A dotted path is a nested object and name[] an array of objects — the editor renders the same tree.
| Field | Type | Required | Default | Constraints | Example |
|---|---|---|---|---|---|
dataset Dataset name or id. | string | Yes | — | — | — |
routine Routine name or id. | string | Yes | — | — | — |
Output
One shape.
result
Extra keys beyond the ones listed can appear.
| Field | Type | Example |
|---|---|---|
arguments | array | — |
buildStatus | object | — |
creationTime | string | — |
dataGovernanceType | string | — |
definitionBody | string | — |
description | string | — |
determinismLevel | string | — |
etag | string | — |
externalRuntimeOptions | object | — |
importedLibraries | array | — |
language | string | — |
lastModifiedTime | string | — |
pythonOptions | object | — |
remoteFunctionOptions | object | — |
returnTableType | object | — |
returnType | object | — |
routineReference | object | — |
routineType | string | — |
securityMode | string | — |
sparkOptions | object | — |
strictMode | boolean | — |
{
"arguments": [],
"buildStatus": {},
"creationTime": "",
"dataGovernanceType": "",
"definitionBody": "",
"description": "",
"determinismLevel": "",
"etag": "",
"externalRuntimeOptions": {},
"importedLibraries": [],
"language": "",
"lastModifiedTime": "",
"pythonOptions": {},
"remoteFunctionOptions": {},
"returnTableType": {},
"returnType": {},
"routineReference": {},
"routineType": "",
"securityMode": "",
"sparkOptions": {},
"strictMode": false
}See Get Routine run in a workflow.
In a technical demo we add the Google BigQuery connection, drop the node on the canvas and let Workflow Health pre-flight it before the first real run.