Recursive SQL for querying hierarchical data: Part 2 – Levels and Ancestors

Ok, so you’ve stored hierarchical data in a relational database, and written recursive CTEs to query the data and find relationships. Now the application team wants to query hierarchical levels and print the complete ancestry tree. Time to deep dive into some advance CTE constructs.

This is the second post of the series about the Recursive SQL for querying hierarchical data started in the previous post . If you haven’t read it already, I recommend reading it to understand the key concepts:

1. What is a hierarchical data?
2. How to store hierarchical data in a relational database?
3. And how to query hierarchical data using:
   • Self-Joins
   • Common Table Expressions (CTE)

In this post, we’ll discuss the advanced scenarios like displaying hierarchical levels and printing the “ancestry tree”. Let’s dive in…

Note: I’ll be re-using the employee dataset we created in the earlier post. Below is our hierarchical model and how it’s stored inside a database table.

Hierarchical model

     CEO -->  1
             / \
            /   \
           /     \
          /       \
CIO -->  2         3  <-- COO  
        / \       / \
       /   \     /   \
      4     5   6     7
     / \             / \ 
    /   \           /   \
   8     9        10    11
          \ 
           12

Relational model

Scenario 1. Show hierarchical level

This can done by adding the starting level as a constant in the non-recursive branch. In the recursive branch you simply add 1 to the level:

WITH RECURSIVE ctename AS (
      SELECT employee_id
      		 , full_name
      		 , 0 AS Level
      FROM employees
      WHERE employee_id = 1
   UNION ALL
      SELECT e.employee_id, 
      		 e.full_name,
             ctename.level + 1
      FROM employees e
         JOIN ctename ON e.manager_id = ctename.employee_id
)
SELECT * FROM ctename;

Scenario 2. Display Ancestor Tree

Another frequent requirement is to collect all the ancestors in a “hierarchy”

WITH RECURSIVE ctename AS (
      SELECT employee_id
            , '(' || upper(title) || ' ) ' || full_name AS hierarchy
      FROM employees
      WHERE employee_id = 1
   UNION ALL
      SELECT e.employee_id
             , ctename.hierarchy || ' -> ' || '(' || upper(e.title) || ') ' ||e.full_name
      FROM employees e
         JOIN ctename ON e.manager_id = ctename.employee_id
)
SELECT hierarchy AS "Org Hierarchy Chart" FROM ctename;

Conclusion – Do more within the database

We learned simple way to traverse through deep hierarchical data using CTEs, without having to write any line of application code to do the recursion. And this is the ultimate application performance tuning tip i.e. to do more within the database. PostgreSQL is already optimized for data storage, retrieval, and complex operations such as aggregates, JOINs, etc. So have your application code deal with displaying data and allow PostgreSQL to do computationally heavy tasks such as data manipulation and aggregations.

As always, thanks for reading!

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Author: Varun Dhawan

Hello dear reader, I'm a Product Manager @Microsoft based in MN, US (beautiful land of 10,000 lakes). I am perpetually curious and always willing to learn and engineer systems that can help solve complex problems using data. When I am not engineering or blogging, you’ll find me cooking and spending time with my family. Varun.Dhawan@gmail.com View all posts by Varun Dhawan