Agent Skillsgoogle/skills › bigquery-basics

bigquery-basics

GitHub

管理BigQuery数据集、表及作业,支持SQL查询、资源管理和基础数据摄入。涵盖API启用、CLI操作、客户端库及MCP集成,适用于大数据平台交互与分析任务。

skills/cloud/bigquery-basics/SKILL.md google/skills

Trigger Scenarios

需要与BigQuery交互 运行SQL查询 管理BigQuery资源如数据集或表 执行基础数据摄入和分析

Install

npx skills add google/skills --skill bigquery-basics -g -y
More Options

Non-standard path

npx skills add https://github.com/google/skills/tree/main/skills/cloud/bigquery-basics -g -y

Use without installing

npx skills use google/skills@bigquery-basics

指定 Agent (Claude Code)

npx skills add google/skills --skill bigquery-basics -a claude-code -g -y

安装 repo 全部 skill

npx skills add google/skills --all -g -y

预览 repo 内 skill

npx skills add google/skills --list

SKILL.md

Frontmatter
{
    "name": "bigquery-basics",
    "metadata": {
        "category": "BigDataAndAnalytics"
    },
    "description": "Manages datasets, tables, and jobs in BigQuery. Use when you need to interact with BigQuery, run SQL queries, manage BigQuery resources (datasets, tables, views), or perform basic data ingestion and analysis."
}

BigQuery Basics

BigQuery is a serverless, AI-ready data platform that enables high-speed analysis of large datasets using SQL and Python. Its disaggregated architecture separates compute and storage, allowing them to scale independently while providing built-in machine learning, geospatial analysis, and business intelligence capabilities.

Setup and Basic Usage

  1. Enable the BigQuery API:

    gcloud services enable bigquery.googleapis.com --quiet
    
  2. Create a Dataset:

    bq mk --dataset --location=US my_dataset
    
  3. Create a Table:

    Create a file named schema.json with your table schema:

    [
      {
        "name": "name",
        "type": "STRING",
        "mode": "REQUIRED"
      },
      {
        "name": "post_abbr",
        "type": "STRING",
        "mode": "NULLABLE"
      }
    ]
    

    Then create the table with the bq tool:

    bq mk --table my_dataset.mytable schema.json
    
  4. Run a Query:

    bq query --use_legacy_sql=false \
    'SELECT name FROM `bigquery-public-data.usa_names.usa_1910_2013` \
    WHERE state = "TX" LIMIT 10'
    

Reference Directory

  • Core Concepts: Storage types, analytics workflows, and BigQuery Studio features.

  • CLI Usage: Essential bq command-line tool operations for managing data and jobs.

  • Client Libraries: Using Google Cloud client libraries for Python, Java, Node.js, and Go.

  • MCP Usage: Using the BigQuery remote MCP server and Gemini CLI extension.

  • Infrastructure as Code: Terraform examples for datasets, tables, and reservations.

  • IAM & Security: Roles, permissions, and data governance best practices.

If you need product information not found in these references, use the Developer Knowledge MCP server search_documents tool.

Related Skills

  • BigQuery AI & ML Skill: SKILL.md file for BigQuery AI and ML capabilities (forecast, anomaly detection, text generation).

Version History

  • aabe37a Current 2026-07-05 15:28

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