Retrieving All Child Categories: Understanding the Query

Introduction

The provided Stack Overflow post is about retrieving all child categories for a given category ID in a single table. The table contains multiple levels of nesting, making it challenging to fetch the desired hierarchy. In this article, we will delve into the problem and explore different solutions.

Background

To understand the query, let’s first examine the table structure and data. We have a categories table with three columns: id, name, and path. The id column is not unique; instead, it serves as an identifier for each category. The name column stores the category name, while the path column contains the hierarchical path.

Problem Statement

The user wants to retrieve all child categories for a given category ID. However, there are no limits on the number of nested levels. This means we need to fetch the hierarchy up to any depth level.

Solution Overview

To solve this problem, we will explore three different approaches:

1. Recursive Common Table Expression (CTE): Using recursive CTEs is a common approach for solving hierarchical problems in SQL.
2. Self-Join: Another method involves using self-join to match parent and child categories based on their paths.

Approach 1: Recursive Common Table Expression

The first solution uses recursive CTEs to build the hierarchy. We will break down this solution step by step:

Step 1: Building the Recursive CTE

with cte (id, name, parentId, path, ord) as (
    select id, name, parentId, path, 1 as ord
    from categories
    where id = 'A2'
    union all
    select c.id, c.name, c.parentId, c.path, t.ord+1
    from categories c join cte t
    on t.parentId = c.id 
)

Step 2: Selecting the Result

select id, name, parentId, path
from (
    select *  from cte
    union all
    select *  from cte
) T
where ord > 0 /* to avoid duplicates (one from each CTE) */
order by ord desc;

This recursive CTE starts with the top-level category and then recursively joins itself to build the hierarchy. The ord column is used to keep track of the depth level, allowing us to order the results correctly.

Approach 2: Self-Join

The second solution uses self-join to match parent and child categories based on their paths:

Up-Hierarchy Query

select C1.id, C1.parentId, C1.name, C1.path
from categories C1 join categories C2
on C2.path like CONCAT('%', C1.name, '%')
where C2.id='A2'
order by length(C1.path);

This query uses the CONCAT function to match the path of the child category (C2) with the name of its parent category (C1). The results are ordered based on the length of the parent’s path, ensuring that the most upper-level parent appears first.

Down-Hierarchy Query

select C1.id, C1.parentId, C1.name, C1.path
from categories C1 join categories C2
on C1.path like CONCAT('%', C2.name, '%')

This query uses the same CONCAT function but reverses the match direction. This allows us to retrieve the child categories in descending order of their path lengths.

Full-Hierarchy Query

select C1.id, C1.parentId, C1.name, C1.path
from (
    select *  from (select id, name, parentId, path, 0 as ord 
                     from categories
                     where id = 'A2') C1
    union all
    select C1.id, C1.parentId, C1.name, C1.path, t.ord+1
    from (select id, name, parentId, path, 0 as ord 
              from categories
              where id = 'A2') C1 join C2
          on C1.path like CONCAT('%', C2.name, '%')
) T
where ord > 0 /* to avoid duplicates (one from each query) */
order by ord;

This full-hierarchy query combines the up- and down-hierarchy queries using a union. The ord column keeps track of the depth level, ensuring that the results are ordered correctly.

Conclusion

In this article, we explored three different approaches to retrieve all child categories for a given category ID in a single table. Recursive Common Table Expression (CTE) and self-join are powerful techniques for solving hierarchical problems in SQL. By choosing the right approach, you can efficiently build the hierarchy and retrieve the desired data.

Last modified on 2023-10-10