ActionGoogle BigQueryUpdated September 2026

How do I run a SQL query on BigQuery?

Short answer: You can run bigquery sql query in Google BigQuery by hand from its own interface, but it won’t repeat itself. On TinyCommand, add the Google BigQuery Run BigQuery SQL Query action to a workflow, map its 5 inputs from any upstream app, and it runs automatically every time the trigger fires. No code, and a free tier to start.

Run BigQuery SQL Query in Google BigQuery — start free All 3 Google BigQuery actions

Run BigQuery SQL Query in Google BigQuery — start free

Inputs

The fields this action accepts.

Every field can be mapped from an upstream trigger, AI step, table row, or hard-coded literal.

Field	Type	Required	Description
Project ID project_id	string	Required	GCP project that billing/quotas apply to.
SQL Query query	string	Required	Standard SQL. Use fully-qualified table names: `project.dataset.table`.
Use Legacy SQL use_legacy_sql	boolean	Optional	Leave off for standard SQL (recommended). On only for legacy BQ syntax.
Max Results max_results	number	Optional	Rows per page.
Query Timeout (ms) timeout_ms	number	Optional	How long to wait for the query to finish before returning a jobId for async polling.

Sample request

{
  "project_id": "my-gcp-project-12345",
  "query": "SELECT name, COUNT(*) AS count FROM `bigquery-public-data.usa_names.usa_1910_2013` WHERE state = 'CA' GROUP BY name ORDER BY count DESC LIMIT 10",
  "use_legacy_sql": "{{trigger.use_legacy_sql}}",
  "max_results": "{{trigger.max_results}}",
  "timeout_ms": "{{trigger.timeout_ms}}"
}

Returns

{
  "kind": "bigquery#queryResponse",
  "rows": [
    {
      "f": [
        {
          "v": "John"
        },
        {
          "v": "12345"
        }
      ]
    }
  ],
  "schema": {
    "fields": [
      {
        "name": "name",
        "type": "STRING"
      },
      {
        "name": "count",
        "type": "INTEGER"
      }
    ]
  },
  "totalRows": "10",
  "jobComplete": true,
  "jobReference": {
    "jobId": "job_abc123",
    "projectId": "my-project"
  }
}

Use these fields in downstream nodes for routing, logging, or error handling.

Triggered by

Apps that pair well as the trigger for Run BigQuery SQL Query.

Any of these apps can fire this action as part of a workflow.

Gmail → Google BigQuery

1 Gmail triggers

Slack → Google BigQuery

13 Slack triggers

Google Sheets → Google BigQuery

2 Google Sheets triggers

HubSpot → Google BigQuery

18 HubSpot triggers

FAQ

Questions about Run BigQuery SQL Query.

What does the Run BigQuery SQL Query action do in Google BigQuery?

Executes a Standard SQL query and returns the resulting rows. Cost scales with bytes scanned, so tight WHERE clauses on partitioned columns save real money. Use dry_run=true to preview cost before running large queries.

What inputs does Run BigQuery SQL Query require?

Required: Project ID, SQL Query. Every input accepts a static value or a variable from any upstream node in your workflow.

Can I use dynamic inputs from earlier workflow nodes?

Yes. Any field on this action can pull values from upstream nodes, whether that's a form response, a trigger payload, an AI output, or a lookup result.

What happens if Google BigQuery returns an error?

The run history shows the failed step with its input and the error message Google BigQuery returned, so you can fix the input and run the workflow again. Automatic retries are built into HTTP steps only, where you can also set your own retry count and delay.

Does Run BigQuery SQL Query support batch operations?

Run Run BigQuery SQL Query inside a loop to process each item in an array. TinyCommand does not throttle calls for you, so for large arrays add a Delay step if you need to stay within Google BigQuery's rate limits.

More actions

Other Google BigQuery actions.

Action

List Datasets

Returns every dataset in the connected GCP project with name, location, default retention. Useful for resolving dataset names in workflow setup and for inventorying the project's data warehouse structure.

Action

List Tables in Dataset

Returns the tables, views, and external tables in a dataset with size and row counts. Useful for query-construction workflows that need to validate table existence before running a query.

Run BigQuery SQL Query in Google BigQuery — start free