Understanding SQL Nested Queries: A Deep Dive into Case Statements and Grouping

Introduction

SQL nested queries can be a complex topic to master, especially when it comes to case statements and grouping. In this article, we’ll delve into the world of SQL and explore how to create effective nested queries using case statements.

What are Nested Queries?

Nested queries in SQL involve embedding one query inside another. This is done to improve performance, simplify complex logic, or perform calculations on sub-queries.

The Problem with Case Statements

In your original question, you tried to multiply a sum() with a case expression but encountered a syntax error. This highlights the importance of understanding how case statements work in SQL.

Understanding Case Statements

A case statement is used to select different values for each row based on certain conditions. In SQL, it’s typically used as part of an IF-THEN structure.

CASE 
  WHEN condition THEN value1
  ELSE value2
END

In your original query, you tried to use a case statement with multiplication:

SELECT SUM("nb"), app_name, user_id, api, CASE WHEN api='v1.pt_ob' THEN '0.7' WHEN api='v1.place_ur' THEN '1' WHEN api='V2' THEN '0.4' ELSE 'autre' END

However, using a case statement with multiplication like this would result in an error because the CASE expression is not a valid operator for multiplication.

Why Can’t We Multiply SUM() and CASE?

The issue here is that SUM() returns a numeric value, while CASE returns a string value. You can’t multiply two different data types together without casting them to the same type first.

{< highlight sql >}
SELECT SUM("nb") AS sum
FROM table_name;

In this example, SUM("nb") returns an integer value. However, when you add a CASE statement like in your original query, it changes the data type of the result to string:

{< highlight sql >}
SELECT SUM("nb"), app_name, user_id, api, CASE WHEN api='v1.pt_ob' THEN '0.7' ELSE NULL END
FROM table_name;

This is because the CASE expression returns a string value based on the condition, while SUM() returns an integer.

Solving the Problem: Using a Sub-Query

To solve your original problem, you need to use a sub-query with a different approach. Here’s one way to do it:

SELECT app_name, user_id, api,
       (SELECT SUM(nb) * 
        CASE WHEN 'v1.pt_ob' = api THEN 0.7
             WHEN 'v1.place_uri' = api THEN 1
             ELSE NULL
        END
       FROM stat_compiled.requests_calls_y2022m02) AS multiplication_result
FROM stat_compiled.requests_calls_y2022m02
WHERE app_name IN (
  'CMI_transilien'
, 'CMI - APM'
, 'Media_SNCF.com'
, 'Medias_TER'
, 'CMI PIV- sncf.com'
, 'CMI PIV - TER'
)
GROUP BY 
  app_name
, api
, user_id;

However, this approach can be slow and inefficient because it requires a sub-query. Instead, you can use a Common Table Expression (CTE) or a window function to achieve the same result.

Using Common Table Expressions (CTEs)

A CTE is a temporary result set that’s defined within a single SELECT, INSERT, UPDATE, or DELETE statement. Here’s how you can use a CTE in your query:

WITH multiplication_result AS (
  SELECT SUM(nb) AS sum, app_name, user_id, api,
         CASE WHEN 'v1.pt_ob' = api THEN 0.7
              WHEN 'v1.place_uri' = api THEN 1
              ELSE NULL
         END AS case_value
  FROM stat_compiled.requests_calls_y2022m02
)
SELECT app_name, user_id, api, multiplication_result.sum * multiplication_result.case_value AS result
FROM multiplication_result
WHERE app_name IN (
  'CMI_transilien'
, 'CMI - APM'
, 'Media_SNCF.com'
, 'Medias_TER'
, 'CMI PIV- sncf.com'
, 'CMI PIV - TER'
)
GROUP BY 
  app_name
, api
, user_id;

Using Window Functions

A window function is a type of aggregate function that performs calculations across a set of rows. Here’s how you can use the SUM window function to achieve your original result:

SELECT app_name, user_id, api,
       SUM(nb) * 
       CASE WHEN 'v1.pt_ob' = api THEN 0.7
            WHEN 'v1.place_uri' = api THEN 1
            ELSE NULL
       END AS multiplication_result
FROM stat_compiled.requests_calls_y2022m02
WHERE app_name IN (
  'CMI_transilien'
, 'CMI - APM'
, 'Media_SNCF.com'
, 'Medias_TER'
, 'CMI PIV- sncf.com'
, 'CMI PIV - TER'
)
GROUP BY 
  app_name
, api
, user_id;

In this example, we use the SUM window function to calculate the multiplication result for each row. This approach avoids the need for a sub-query or CTE.

Conclusion

SQL nested queries can be complex and challenging, but with practice and experience, you’ll become proficient in using case statements and grouping to solve problems efficiently. Remember to avoid quoted strings around numbers, use a sub-query when necessary, and consider using Common Table Expressions (CTEs) or window functions for more efficient solutions.

Tips and Variations

Always test your queries with sample data before running them on production datasets.
Use the EXPLAIN statement to analyze query performance and optimize your queries.
Consider using JOIN instead of sub-queries when possible, especially for large datasets.
Practice, practice, practice! The more you work with SQL, the more comfortable you’ll become with its syntax and semantics.

Last modified on 2024-10-12