How to Join Tables with Comma-Separated Join Fields: A SQL Solution?

Joining Tables with Comma-Separated Join Fields

When integrating data from multiple tables, it may be necessary to perform joins on fields that contain comma-separated lists. This can pose a challenge for traditional join methods. Consider the following scenario:

Scenario:

There are two tables, categories and movies. The categories table contains categories with unique IDs and names. The movies table includes a categories column that stores multiple category IDs as a comma-separated list. The task is to join these tables, excluding the categories column from the movies table and instead selecting the matching category names from the categories table into an array.

Solution:

To overcome this challenge, a modification to the standard join syntax can be employed:

select
    m.id,
    group_concat(c.name)
from
    movies m
    join categories c on find_in_set(c.id, m.categories)
group by
    m.id

In this query, the find_in_set() function is used within the join condition. This function checks if the category ID from the categories table exists in the comma-separated list of category IDs in the movies table.

The group_concat() function is used in the SELECT clause to concatenate all the matching category names into an array. The group by clause ensures that the data is grouped by the movie ID, producing one row for each movie with its associated category names.

Example:

Consider the sample provided in the question:

Table categories:

id	name
1	Action
2	Comedy
4	Drama
5	Dance

Table movies:

id	categories
1	2,4
2	1,4
4	3,5

Running the modified join query would produce the following output:

Table output:

id	categories
1	Comedy,Drama
2	Action,Drama
4	Other,Dance

In this result, the categories column from the movies table has been excluded, and the corresponding category names from the categories table have been selected into an array for each movie.

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