Conditional Aggregation and Location Counting in PL/SQL

In this article, we will explore how to count similar identifiers in a single column using PL/SQL. We’ll dive into the world of conditional aggregation and group by clauses to extract meaningful insights from your database data.

Understanding the Problem

Suppose you have a database with 1069 rows, each containing a unique identifier known as TRIAL_ID. The first three identifiers belong to one location (OAD), the next three to another (ROT), and the remaining ones have no discernible pattern. Your goal is to display a count for each of these locations.

Initial Attempts

You attempt to solve this problem using a combination of LIKE operators and OR conditions:

select (
    select count(trial_id) from locations where trial_id like 'oad%'),
    (select count(trial_id) from locations where trial_id like 'rot%'),
    (select count(trial_id) from locations where trial_id not like 'rot%' or trial_id not like 'oad%') 
from locations

Unfortunately, this approach yields incorrect results. Let’s understand why.

The Issue with LIKE Operators

The primary issue lies in the use of OR operators (or) instead of AND operators (and). In boolean logic, not (NOT) is equivalent to not x (x NOT). Therefore, when combining conditions like trial_id not like 'rot%' and trial_id not like 'oad%', Oracle interprets this as (not (trial_id not like 'rot%')) and (not (trial_id not like 'oad%')).

This results in a logical contradiction, causing the condition to always evaluate as FALSE. Consequently, the count for the “other” location is incorrect.

Conditional Aggregation: A Better Approach

To accurately count similar identifiers, we can utilize conditional aggregation techniques. This approach involves creating separate values for each condition (e.g., trial_id like 'oad%') and then aggregating those values using SUM or COUNT functions.

Here’s the corrected code:

select sum(case when trial_id like 'oad%' then 1 else 0 end) as oad,
       sum(case when trial_id like 'rot%' then 1 else 0 end) as rot,
       sum(case when trial_id not like 'oad%' and trial_id not like 'rot%' then 1 else 0 end) as other
from locations;

This query scans the table only once, making it more efficient than your initial attempt. By using a SUM function with CASE expressions, we can accurately count the occurrences of each identifier pattern.

Alternative Approach Using GROUP BY

Another way to achieve this is by employing a GROUP BY clause:

select (case when trial_id like 'oad%' then 'oad'
             when trial_id like 'rot%' then 'rot'
             else 'other'
        end) as location,
       count(*)
from locations
group by (case when trial_id like 'oad%' then 'oad'
               when trial_id like 'rot%' then 'rot'
               else 'other'
          end);

In this approach, we create a derived table using the same CASE expression. The GROUP BY clause groups rows with identical values in the location column, allowing us to count the occurrences of each location.

Conclusion

Conditional aggregation and group by clauses provide effective solutions for counting similar identifiers in a single column using PL/SQL. By understanding boolean logic and logical operators, we can avoid common pitfalls like incorrect results from LIKE operators.

When working with conditional statements, it’s essential to use AND instead of OR operators to ensure accurate evaluations. Conditional aggregation techniques offer a concise and efficient way to extract insights from your data.

Best Practices

• Use CASE expressions to create separate values for each condition.
• Employ SUM or COUNT functions to aggregate those values.
• Avoid using LIKE operators with OR conditions; instead, use AND conditions to combine logical statements.
• Utilize GROUP BY clauses when working with multiple aggregation functions.

By following these best practices and understanding the concepts discussed in this article, you’ll be better equipped to tackle similar problems in your PL/SQL endeavors.

Last modified on 2024-02-12