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bigquery-basics
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.
DeepseekModel
官方收录技能
质量 优秀 · 90
v1.0.0
获取
https://deepseekmodel.com/api/download.php?id=google-skills-skills-cloud-bigquery-basics-skill-md&format=skill
下载 .skill
标准格式,含 system_prompt 与 model_config,导入任意 Agent 框架即可使用
.skill 文件中 system_prompt 字段的实际内容。
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 Enable the BigQuery API: gcloud services enable bigquery.googleapis.com --quiet Create a Dataset: bq mk --dataset --location=US my_dataset 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 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. Change History : Tracking and querying incremental table changes using APPENDS and CHANGES. Continuous Queries : Running continuous SQL statements to analyze incoming data in real time. 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).
Agent 识别该技能的关键词,点击任意一个即可复制。
该技能未提供触发词。
下载的 .skill 包内含以下字段。
| 字段 | 说明 |
|---|---|
| format | 格式标识(skill/v1) |
| skill_id | 技能唯一 ID |
| name | 技能名称 |
| version | 版本号 |
| description | 技能描述 |
| category | 所属分类(数组) |
| trigger_words | 触发词列表 |
| tags | 标签列表 |
| source | 来源标识 |
| source_url | 来源链接(本页地址) |
| exported_at | 导出时间(每次下载生成) |
| system_prompt | 系统提示词正文 |
| model_config | 模型参数:provider / model / temperature / max_tokens / top_p |
| examples | 示例 |
| install_guide | 各平台导入说明(Coze / Dify / Claude / 自定义框架) |