Datalineage Bigquery Asset Impact Analysis

作者 google55b4e13eba6d無授權條款21K 個星標收錄於 2026年10月8日更新於 2026年10月8日儲存庫今天更新

Analyzes the downstream impact (blast radius) when a BigQuery table or view is broken, stale, or modified. Identifies all downstream tables, dashboards, and processes that will be affected. Use when: - Performing a blast radius or impact analysis for a BigQuery table or view. - Assessing the consequences of modifying, deleting, or pausing updates to a BigQuery asset. - Identifying downstream dependencies (tables, dashboards, processes) of a BigQuery asset. Don't use for: - General BigQuery querying or data analysis (use BigQuery-related tools instead). - Non-BigQuery assets (e.g., Cloud Storage files) unless they are part of the BigQuery lineage. - Creating or modifying lineage links directly.

AI 產生的概覽

引導代理使用資料血緣對 BigQuery 資料表或檢視表進行下游影響(爆炸半徑)分析。

功能
此技能引導代理在 BigQuery 資料表或檢視表損毀、過期、遺失或即將被修改時評估其下游影響。它會解析資產的完整合格名稱,判斷資料集位置與父路徑,並透過 Data Lineage MCP 伺服器取得下游血緣關係。接著建立影響圖,區分直接影響與間接影響,並產出執行摘要、關鍵路徑、爆炸半徑表格與分析中繼資料。
適用情境
適用於對 BigQuery 資料表或檢視表進行爆炸半徑或影響分析,或評估修改、刪除、暫停更新某個 BigQuery 資產的後果。也用於識別下游相依項目,例如資料表、儀表板和流程。
執行需求
需要存取 Google Cloud Data Lineage API,並與 Data Lineage MCP 伺服器建立有效的用戶端連線,同時需要 bq 命令列工具來探索位置。此技能不含指令碼,僅為指示文件,並附有一份關於 MCP 用法的參考文件。

BigQuery Asset Impact Analysis

This skill guides the agent in performing a downstream impact analysis (blast radius assessment) when a BigQuery table or view is reported as broken, stale, missing, or when a user is planning maintenance and wants to know the consequences of modifying or pausing updates to an asset.

It relies primarily on the Google Cloud Data Lineage (Knowledge Catalog) MCP Server to discover relationships between assets.

Prerequisites

This skill requires access to the Google Cloud Data Lineage API and an active client connection to the Data Lineage MCP Server. For detailed connection configurations and tool schemas, refer to MCP Usage [blocked].

Analysis Workflow

1. Resolve the Asset's Fully Qualified Name (FQN)

  • Ensure you have the correct FQN format for the BigQuery asset:
    • Format: bigquery:{project_id}.{dataset_id}.{table_or_view_id}
    • Example: bigquery:my-prod-project.analytics.orders

2. Determine Locations and Parent Path

Identify the locations to search and construct the Data Lineage API request:

  • Discover Asset Location: Run the command bq show --format=json {project_id}:{dataset_id} and extract the location field (e.g., us-central1 or us). If location discovery fails due to permissions or missing tools, prompt the user for the dataset's location.
  • Set Parent Path: Set the parent path using the project ID and the MCP server's location. Consult the DataLineageServer tool definition to find the configured region or location (e.g., us). The format is: projects/{project_id}/locations/{mcp_server_location}.
  • Configure Search Scope: Include the discovered asset location in the locations array of the payload (e.g., ["us-central1"] or ["us", "us-central1"]).

3. Retrieve the Downstream Lineage Graph

Call the DataLineageServer:search_lineage tool to fetch downstream relationships.

  • Direction: Set to DOWNSTREAM.
  • Search Parameters: Use max_depth = 10 and max_process_per_link = 5 as robust defaults.

4. Identify the Blast Radius

Traverse the returned lineage links to build the impact graph:

  • Affected Assets: The target of each link represents a downstream asset that depends on your source asset.
  • Transform Processes: Inspect the processes field on each link. This identifies the ETL pipelines, BigQuery Views, or Scheduled Queries that propagate the data.
  • Direct vs. Indirect Impact:
    • Direct Impact (Depth 1): Assets directly consuming the source asset. If a link has dependency_type: EXACT_COPY, mark the target as "Directly Stale / Identical Copy".
    • Indirect Impact (Depth > 1): Assets further down the stream that will experience cascading stale data or failures.

5. Summarize and Format the Output

Present your findings clearly to the user using the following structure:

  1. Executive Summary: State the total number of downstream assets affected and the maximum depth of the impact.

  2. Critical Path: Highlight high-priority downstream assets (e.g., assets containing "prod", "dashboard", "reporting", or "master" in their names).

  3. Blast Radius Table: A clean Markdown table listing the dependencies. You MUST include all columns:

    Downstream AssetTransform ProcessDepthImpact Type
    bigquery:project.dataset.tableprojects/p/locations/l/processes/proc1Direct
    bigquery:project.dataset.viewprojects/p/locations/l/processes/view2Indirect
  4. Analysis Metadata: Provide transparency on the parameters and boundaries of your search so the user can choose to expand them:

    • Locations Searched: {list_of_locations_queried}
    • Parent Location: {parent_path}
    • Depth Limit: {max_depth}
    • Process per Link Limit: {max_process_per_link}
    • Tip for User: Let the user know they can request to rerun the analysis with expanded locations or larger depth limits.

Crucial Constraints & Guardrails

  1. Interpret Empty Responses Correctly:
    • If the lineage response is empty, immediately assume that no dependencies exist in the queried locations and report this to the user.
  2. Strictly Banned Bypasses:
    • Exclusively retrieve downstream relationships using the DataLineageServer:search_lineage tool.
  3. Verify Asset Existence First:
    • If bq show indicates the source table does not exist, stop and report this directly to the user. Do not attempt to guess alternative table names unless the user explicitly instructs you to do so.
  4. No Output Shortcutting or Hallucinated Artifacts:
    • Present the complete downstream blast radius table directly in your final response. Avoid telling the user you have created a separate Markdown file or artifact containing the details unless you have explicitly executed file-writing tools to create it.

Reference Directory

  • MCP Usage [blocked]: Using the Google Cloud Data Lineage remote MCP server and tool preferences.

External Documentation

來源與署名

來源:google/skills位於skills/cloud/datalineage-bigquery-asset-impact-analysis提交55b4e13

授權條款: 無授權條款

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