What can you do with it?
Manage and analyze large datasets in Google Cloud BigQuery, including listing projects and datasets, querying tables, and executing SQL queries for data analysis and reporting.How to use it?
Basic Command Structure
Parameters
Required:action
- The operation to perform (list-projects, list-datasets, list-tables, run-query, get-query-results)
project-id
- Google Cloud project IDdataset-id
- BigQuery dataset IDjob-id
- Query job ID for result retrieval
Tools
List Projects
Retrieve a list of projects to which the user has been granted any project role Parameters:- No additional parameters required
List Datasets
List all datasets in the specified project to which the user has been granted the READER dataset role Parameters:project-id
(required) - The project ID containing the datasets
List Tables
Lists all tables in the specified dataset Parameters:project-id
(required) - The project ID containing the datasetdataset-id
(required) - The dataset ID containing the tables
Run Query
Runs a BigQuery SQL query synchronously and returns query results if the query completes within a specified timeout Parameters:project-id
(required) - The project ID to run the query inquery
(required) - The SQL query to executeuse-legacy-sql
(optional) - Whether to use legacy SQL syntax (default: false)
Get Query Results
Retrieves the results of a query job Parameters:project-id
(required) - The project ID containing the query jobjob-id
(required) - The query job ID
Notes
BigQuery supports standard SQL syntax and provides detailed schema information for query results. Use backticks around fully qualified table names in the formatproject-id.dataset_id.table_id
.