❄️ Snowflake Recursive CTEs (Common Table Expressions) – Simplifying Hierarchical Data Queries

In data analytics, not all relationships are flat. Many datasets — such as organization charts, product categories, or directory trees — have a hierarchical structure.

For example:

• An employee reports to a manager who reports to a director.
• A category has subcategories that may have further subcategories.
• A file folder contains subfolders and files recursively.

How do we query such structures using SQL?

Enter Recursive CTEs (Common Table Expressions) — a feature in Snowflake SQL that allows you to traverse hierarchical or self-referential data efficiently.

🧠 What is a Recursive CTE?

A Recursive Common Table Expression (CTE) is a temporary result set that references itself. It’s ideal for exploring parent-child relationships or multi-level hierarchies in data.

🧩 General Syntax

WITH RECURSIVE cte_name AS (
    -- Anchor member (base result)
    SELECT ... FROM ... WHERE ...
    UNION ALL
    -- Recursive member (references cte_name)
    SELECT ... FROM cte_name JOIN ... ON ...
)
SELECT * FROM cte_name;

⚙️ CTE Components

🎨 ** – Recursive CTE Process**

💡 Why Recursive CTEs Matter

🧩 Example 1 – Organizational Hierarchy

🧱 Scenario:

You have an employee table with each employee’s manager. You want to build a full hierarchy tree from the CEO downwards.

💾 Step 1: Create Sample Data

CREATE OR REPLACE TABLE employees (
    emp_id INT,
    emp_name STRING,
    manager_id INT
);

INSERT INTO employees VALUES
(1, 'Alice', NULL),
(2, 'Bob', 1),
(3, 'Charlie', 1),
(4, 'David', 2),
(5, 'Eve', 2),
(6, 'Frank', 3);

💡 Step 2: Recursive CTE Query

WITH RECURSIVE org_hierarchy AS (
    -- Anchor: CEO (no manager)
    SELECT emp_id, emp_name, manager_id, 0 AS level
    FROM employees
    WHERE manager_id IS NULL

    UNION ALL

    -- Recursive: Fetch direct reports
    SELECT e.emp_id, e.emp_name, e.manager_id, oh.level + 1
    FROM employees e
    JOIN org_hierarchy oh ON e.manager_id = oh.emp_id
)
SELECT * FROM org_hierarchy;

✅ Output

🧠 Explanation

• Anchor Query: Starts with the CEO (no manager).
• Recursive Query: Finds employees whose manager_id matches an existing emp_id.
• Level Counter: Tracks hierarchy depth.

✅ Use Case: Organization charts, reporting structures.

🧩 Example 2 – Product Category Hierarchy

🧱 Scenario:

You have product categories where each category can have a parent category.

💾 Step 1: Create Sample Table

CREATE OR REPLACE TABLE categories (
    category_id INT,
    category_name STRING,
    parent_id INT
);

INSERT INTO categories VALUES
(1, 'Electronics', NULL),
(2, 'Laptops', 1),
(3, 'Mobiles', 1),
(4, 'Gaming Laptops', 2),
(5, 'Android Phones', 3),
(6, 'Accessories', NULL);

💡 Step 2: Recursive Query

WITH RECURSIVE category_tree AS (
    -- Anchor: Root categories
    SELECT category_id, category_name, parent_id, 0 AS level
    FROM categories
    WHERE parent_id IS NULL

    UNION ALL

    -- Recursive: Find subcategories
    SELECT c.category_id, c.category_name, c.parent_id, ct.level + 1
    FROM categories c
    JOIN category_tree ct ON c.parent_id = ct.category_id
)
SELECT * FROM category_tree ORDER BY level;

✅ Output

🧠 Explanation

• Parent-child mapping: Recursive join expands children categories.
• Level indicator: Helps visualize tree depth.
• ORDER BY level: Displays hierarchical flow neatly.

✅ Use Case: E-commerce category trees or product taxonomies.

🧩 Example 3 – Directory Tree Traversal

🧱 Scenario:

You have a file directory system where each folder may have subfolders.

💾 Step 1: Create Sample Table

CREATE OR REPLACE TABLE directories (
    dir_id INT,
    dir_name STRING,
    parent_dir INT
);

INSERT INTO directories VALUES
(1, 'root', NULL),
(2, 'documents', 1),
(3, 'images', 1),
(4, 'work', 2),
(5, 'personal', 2),
(6, 'vacation', 3);

💡 Step 2: Recursive Query

WITH RECURSIVE dir_tree AS (
    -- Base directory
    SELECT dir_id, dir_name, parent_dir, '/' || dir_name AS full_path
    FROM directories
    WHERE parent_dir IS NULL

    UNION ALL

    -- Recursive expansion
    SELECT d.dir_id, d.dir_name, d.parent_dir,
           dt.full_path || '/' || d.dir_name AS full_path
    FROM directories d
    JOIN dir_tree dt ON d.parent_dir = dt.dir_id
)
SELECT * FROM dir_tree;

✅ Output

🧠 Explanation

• Builds folder paths recursively.
• Each recursive level appends folder names to full_path.
• Stops when no subfolders remain.

✅ Use Case: File systems, nested folder structures, data lineage tracking.

🎨 ** – Directory Hierarchy**

🧩 Advantages of Recursive CTEs

⚙️ Performance Optimization Tips

1. Use proper WHERE filters to limit recursion depth.
2. Avoid large recursion chains unless necessary.
3. Add termination logic to prevent infinite loops.
4. Test output incrementally (start small).
5. Combine with caching or materialized views for faster reuse.

🧠 Mnemonic to Remember Recursive CTE Structure

A.R.T. – Anchor, Recursion, Termination

💡 Memory Hook: Think of recursive CTEs as “SQL loops for tree data.”

🧩 Common Interview Questions

1. What is a Recursive CTE in Snowflake?
2. How does recursion terminate in CTEs?
3. Can you track levels or paths in Recursive CTEs?
4. What’s the difference between normal and recursive CTEs?
5. Give a use case for hierarchical data in Snowflake.

🧠 How to Remember for Exam & Interviews

💡 Quick recall:

“Start at the root, connect the branches, stop when the tree ends.”

🧩 Real-World Use Cases

⚙️ Why It’s Important to Learn

1. Essential for Hierarchical Data Modeling Recursive CTEs are fundamental for representing multi-level data.

2. Used in Snowflake Certifications Frequently tested in SnowPro Core and Advanced Architect exams.

3. Common in Real-World Analytics Every industry uses hierarchical relationships — from teams to products.

4. Improves SQL Thinking Strengthens logical understanding of recursion within SQL.

5. Prepares You for Big Data Engineering Roles Recursive CTEs are used in ETL, data lineage, and aggregation logic.

🧭 ** – Recursive Expansion Example**

🧠 Common Mistakes to Avoid

🧩 Example 4 – Limiting Recursion Depth

WITH RECURSIVE org_hierarchy AS (
    SELECT emp_id, emp_name, manager_id, 0 AS level
    FROM employees
    WHERE manager_id IS NULL

    UNION ALL

    SELECT e.emp_id, e.emp_name, e.manager_id, oh.level + 1
    FROM employees e
    JOIN org_hierarchy oh ON e.manager_id = oh.emp_id
    WHERE oh.level < 3
)
SELECT * FROM org_hierarchy;

✅ Purpose: Prevents recursion from going beyond 3 levels.

🧠 Visualization – Recursive CTE Flow

🎯 Summary Table

🧩 Conclusion

The Snowflake Recursive CTE is a powerful tool for querying and visualizing hierarchical data. Whether you’re modeling organizational structures, category trees, or nested directories, Recursive CTEs let you elegantly express recursive logic in a single SQL query — without writing complex scripts or stored procedures.

By mastering this concept, you gain:

• 🔹 Stronger analytical problem-solving skills
• 🔹 Clearer understanding of hierarchical data
• 🔹 An edge in interviews & certifications

Remember:

“Recursive CTEs are the backbone of hierarchical SQL — they turn trees into tables.”