How Can We Efficiently Retrieve All Child Nodes in a Hierarchical Database Table with Parent-Child Relationships?

Hierarchy and parent-child relationships: a more efficient approach

In the field of data modeling, establishing hierarchical and parent-child relationships is crucial for many applications. This article delves into an effective and efficient way to achieve this goal within the constraints of a given data model.

Question

Consider a database table that stores site information and parent-child relationships:

<code class="language-sql">create table site
(
site_Id int(5),
parent_Id int(5),
site_desc varchar2(100)
);</code>

The requirement is to retrieve all child nodes of a given site ID, representing a hierarchy like this:

<code>                    A
                   / \
                  B   C
                / | \ /\
               D  E F G H
              /\
             I  J</code>

Input: Site B
Output: D, E, F, I, J

Current method

Existing methods involve multiple nested queries and may be inefficient. Let's explore an optimized solution.

Data model constraints

In the given data model, every node has a parent node, except the root node. This constraint limits the options available for efficient hierarchical retrieval.

Alternative Data Model

While the adjacency list model works well for the given data, it is less efficient when dealing with deep hierarchies. Closure tables, nested sets, and path enumeration models provide more efficient solutions, but require changes to the data model, which is not possible in this case.

Practical solutions

Given the constraints of the data model, we recommend using a modified adjacency list model and adding a "root_id" column:

<code class="language-sql">create table site
(
site_Id int(5),
parent_Id int(5),
root_id int(5)
);</code>

For each node, the "root_id" column stores the highest ancestor node in its tree. This allows us to retrieve the entire tree with a single query:

<code class="language-sql">SELECT * FROM site WHERE root_id = <root_id></code>

Algorithm:

1. Retrieve all root nodes.
2. Traverse the root node.
3. For each root node, retrieve all child nodes using the "root_id" column.
4. Build hierarchies in memory.

This approach provides efficient hierarchical traversal without database overhead, making it suitable for moderately sized trees.

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