The /bigquery command enables you to manage and analyze large datasets in Google BigQuery. Perfect for:

• Running SQL queries
• Analyzing large datasets
• Managing data warehouses
• Creating reports
• Data exploration

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Basic Usage

Use the command to interact with BigQuery:

/bigquery run query "SELECT * FROM dataset.table LIMIT 10"

/bigquery list all datasets in project my-project-id

/bigquery show tables in dataset analytics

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Key Features

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Query Execution

• Run SQL queries
• Get query results
• Use standard SQL
• Handle large datasets
• View query costs

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Project Management

• List projects
• Access project data
• Navigate datasets
• View permissions

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Dataset Operations

• List datasets
• Create datasets
• View dataset properties
• Manage locations

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Table Management

• List tables
• View table schemas
• Query table data
• Check table types

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Example Commands

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Run Query

/bigquery in project analytics-prod run "SELECT COUNT(*) FROM sales.transactions WHERE date > '2024-01-01'"

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List Projects

/bigquery show all my projects

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List Datasets

/bigquery list datasets in project data-warehouse-prod

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Show Tables

/bigquery show all tables in dataset customer_data

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Complex Query

/bigquery query "SELECT customer_id, SUM(amount) as total FROM sales.orders GROUP BY customer_id HAVING total > 1000"

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Get Query Results

/bigquery get results for job ID job_12345 in project analytics

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SQL Syntax

BigQuery supports standard SQL:

• SELECT, FROM, WHERE
• GROUP BY, ORDER BY
• JOIN, UNION
• Window functions
• CTEs (Common Table Expressions)

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Table References

Use fully qualified names:

• project.dataset.table
• dataset.table (uses default project)
• Backticks for special characters: `my-project.my_dataset.table`

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Tips

• Use LIMIT to preview data
• Check totalBytesProcessed for query costs
• Use useLegacySql: false for standard SQL
• Results are paginated for large datasets