SQL to Update Rows to Remove Words with Less Than N Characters

In this article, we will explore a solution for updating rows in a table where the values in a specific column need to be modified to exclude words that have fewer than a specified number of characters. We’ll delve into the concept of regular expressions and their application in SQL Server.

Understanding the Problem

The problem at hand involves a TAGS column in a Products table, which contains comma-separated values representing tags associated with each product. The task is to remove words from these tag values that have fewer than a specified number of characters (N). For instance, if N = 4, any word with fewer than 4 characters should be excluded.

Solution Overview

Before we dive into the solution, it’s essential to consider an optimal approach to this problem. Instead of modifying the original TAGS column directly in the table, it might be beneficial to restructure the database schema by creating a separate table for storing tags. This will allow us to easily exclude short words without affecting the data integrity or query performance.

Alternative Approach: Redesigning the Database Schema

One efficient way to solve this problem is to create a new table that stores the tag values with long words filtered out. Here’s an example of how to achieve this:

create table tags (id int identity primary key, mytable_id int, tag varchar(100))

insert into tags (mytable_id, tag)
select t.id,
       value
from   mytable t
  cross apply string_split(t.tag, ' ')

alter table mytable drop column tag

In this example, we create a new tags table to store the modified tag values. We use the cross apply function to split the original TAGS column into individual words and then insert each word into the tags table along with its corresponding mytable_id. Finally, we drop the original TAGS column.

Alternative Approach: Modifying the Original Column

If you’re not willing or able to modify your database schema immediately, there’s an alternative solution that can be used in conjunction with a user-defined function (UDF) or a stored procedure. Here’s how to implement this:

update m
set    m.tag = 
       ( select string_agg(value, ' ')
         from   mytable t
           cross apply string_split(m.tag, ' ')
         where len(value) > 3
         and   t.id = m.id
       ) 
from   mytable m  

In this modified version of the update statement, we use a subquery to filter out words with fewer than 4 characters (adjust according to your requirements) using the len() function. The string_agg() function is used to concatenate the remaining long words into a single string.

Using UDF or Stored Procedure

For better maintainability and reusability, you can create a user-defined function (UDF) that encapsulates the logic for filtering out short words:

create function FilterShortWords (@tag varchar(100), @minLength int)
returns varchar(max)
as
begin
    declare @filteredTag varchar(max) = ''

    declare cur cursor for 
        'select value from string_split(@tag, '' '') where len(value) > @minLength'

    open cur

    fetch next from cur into @filteredTag

    while @@FETCH_STATUS = 0
    begin
        print (@filteredTag)
        fetch next from cur into @filteredTag
    end

    close cur
    dealocate cur

    return @filteredTag
end

In this example, we create a UDF called FilterShortWords that takes two parameters: the input tag string and the minimum length of words to filter out. The function uses a cursor to iterate over each word in the tag value and prints (or returns) only the words with a specified minimum length.

Best Practices

It’s essential to consider the following best practices when implementing this solution:

• Regularly review your database schema to ensure that it remains optimal for performance and data integrity.
• Consider indexing columns frequently used in WHERE or JOIN clauses.
• Implement caching mechanisms, like database views or stored procedures, to improve query performance.

Conclusion

Modifying the original column with a short word filter can be achieved through various methods, including re-designing the database schema, using user-defined functions (UDFs), or creating stored procedures. By understanding the different approaches and their advantages, you can make informed decisions about which solution best fits your specific use case.

Last modified on 2023-08-02