tracing-downstream-lineage

Downstream Lineage: Impacts

Answer the critical question: "What breaks if I change this?"

Use this BEFORE making changes to understand the blast radius.

Impact Analysis

Step 1: Identify Direct Consumers

Find everything that reads from this target:

For Tables:

1. Search DAG source code: Look for DAGs that SELECT from this table

   • Use af dags list to get all DAGs
   • Use af dags source <dag_id> to search for table references
   • Look for: FROM target_table, JOIN target_table

2. Check for dependent views:

   -- Snowflake
   SELECT * FROM information_schema.view_table_usage
   WHERE table_name = '<target_table>'
   
   -- Or check SHOW VIEWS and search definitions
   

3. Look for BI tool connections:

   • Dashboards often query tables directly
   • Check for common BI patterns in table naming (rpt_, dashboard_)

On Astro

If you're running on Astro, the Lineage tab in the Astro UI provides visual dependency graphs across DAGs and datasets, making downstream impact analysis faster. It shows which DAGs consume a given dataset and their current status, reducing the need for manual source code searches.

For DAGs:

1. Check what the DAG produces: Use af dags source <dag_id> to find output tables
2. Then trace those tables' consumers (recursive)

Step 2: Build Dependency Tree

Map the full downstream impact:

SOURCE: fct.orders
    |
    +-- TABLE: agg.daily_sales --> Dashboard: Executive KPIs
    |       |
    |       +-- TABLE: rpt.monthly_summary --> Email: Monthly Report
    |
    +-- TABLE: ml.order_features --> Model: Demand Forecasting
    |
    +-- DIRECT: Looker Dashboard "Sales Overview"

Step 3: Categorize by Criticality

Critical (breaks production):

• Production dashboards
• Customer-facing applications
• Automated reports to executives
• ML models in production
• Regulatory/compliance reports

High (causes significant issues):

• Internal operational dashboards
• Analyst workflows
• Data science experiments
• Downstream ETL jobs