Combining Query Results from Different Rows into One

As developers, we often encounter situations where we need to combine the results of multiple queries into a single result set. In this article, we’ll explore how to achieve this using Common Table Expressions (CTEs) and join operations in Oracle SQL.

Background

The problem at hand is as follows: you have two separate queries that return data for different periods of time. You want to combine these results into one result set where each row represents a single period, with the start date from one query and the end date from the other query.

For example, suppose we have two tables, foo.bar, which contains the following data:

We want to combine the results of two queries:

1. SELECT desc, start_date FROM foo.bar WHERE desc LIKE 'Fall%' AND desc NOT LIKE '%Med%'
2. SELECT desc, end_date FROM foo.bar WHERE desc LIKE 'Spring%' AND desc NOT LIKE '%Med%'

Our goal is to produce a result set with the following structure:

How to Achieve this using CTEs and Joins

Instead of using the UNION operator, which can be inefficient and may not always produce the desired results, we’ll use each query as a Common Table Expression (CTE) and then join them together.

Here’s an example of how you might do it:

with t_start as (
  select description, datum,
         row_number() Over (order by datum) rn
  from test
  where description like 'Fall%' and description not like '%Med%'
),
t_end as (
  select description, datum,
         row_number() Over (order by datum) rn
  from test
  where description like 'Spring%' and description not like '%Med%'
)
select s.description ||' - '|| e.description as description,
       s.datum start_date,
       e.datum end_date
from t_start s join t_end e on s.rn = e.rn
order by s.rn;

In this example:

1. We define two CTEs: t_start and t_end. Each CTE selects the description, datum, and a row number (rn) column.
2. The t_start CTE filters the data to include only rows where the description starts with “Fall” and does not contain “Med”.
3. The t_end CTE filters the data to include only rows where the description starts with “Spring” and does not contain “Med”.
4. We join the two CTEs together on the rn column, which ensures that we’re matching each row from t_start with the corresponding row from t_end.
5. Finally, we select the desired columns and concatenate them to form the final result set.

Benefits of Using CTEs and Joins

Using CTEs and joins offers several benefits over using the UNION operator:

• Improved performance: By avoiding unnecessary duplicates and allowing the database to optimize the join operation, we can improve query performance.
• More flexibility: With CTEs and joins, we have more control over how the data is combined and filtered.
• Easier maintenance: The resulting code is often easier to read and understand than a UNION-based solution.

Conclusion

Combining query results from different rows into one requires careful planning and execution. By using Common Table Expressions (CTEs) and joins, we can create more efficient, flexible, and maintainable queries that produce the desired result sets.

When working with data from multiple sources, it’s essential to consider the nuances of each source and how they might impact our queries. With practice and experience, you’ll become proficient in using CTEs and joins to combine query results in creative and effective ways.

Common Table Expressions (CTEs)

A Common Table Expression (CTE) is a temporary result set that’s defined within the execution of a single SQL statement. CTEs can be used to simplify complex queries, improve performance, and make code more readable.

Here are some key benefits of using CTEs:

• Simplified queries: CTEs allow you to break down complex queries into smaller, more manageable pieces.
• Improved performance: By avoiding unnecessary joins and subqueries, CTEs can improve query performance.
• Better code organization: CTEs provide a clear separation of concerns between the main query and the auxiliary calculations.

Example Use Cases for CTEs

CTEs are useful in a variety of scenarios:

1. Simplifying complex queries: By breaking down complex queries into smaller pieces, you can make them easier to understand and maintain.
2. Avoiding performance bottlenecks: By avoiding unnecessary joins and subqueries, you can improve query performance.
3. Improving code organization: CTEs provide a clear separation of concerns between the main query and the auxiliary calculations.

Real-world Applications of CTEs

CTEs are used in various real-world applications:

1. Data warehousing: CTEs can be used to create data mart hierarchies, summarize large datasets, or perform complex aggregations.
2. Business intelligence: CTEs can be used to create dynamic reports, analyze customer behavior, or optimize business processes.
3. Scientific computing: CTEs can be used to solve complex optimization problems, simulate systems, or perform data analysis.

Conclusion

Common Table Expressions (CTEs) are a powerful tool for simplifying complex queries, improving performance, and making code more readable. By understanding how to use CTEs effectively, you’ll become proficient in creating efficient and maintainable queries that produce the desired result sets.

Last modified on 2023-07-31