SQL Query Refactoring for Road Service Jobs

Language/Technology Identification

The code snippet provided is a SQL query.

Original Code Snippet

SELECT 
    Member_Club, 
    memberproduct, 
    count(BKJobNo) as eventcount, 
    SUBSTRING(CAST(bkdatekey AS VARCHAR), 5, 2) AS extracted_month, 
    SUBSTRING(CAST(bkdatekey AS VARCHAR), 1, 4) AS extracted_year
FROM 
    [EDW].[RS].[FactRoadServiceJobs] 
WHERE 
    BKDateKey BETWEEN '20191101' AND '20241231' 
    AND PatrolUnit like '5MR%' 
    AND JobServiceCategory = 'Road Service' 
    AND IsCompletedJob = 1 
    AND region = 'm'
GROUP BY 
    SUBSTRING(CAST(bkdatekey AS VARCHAR), 5, 2), 
    SUBSTRING(CAST(bkdatekey AS VARCHAR), 1, 4), 
    MemberProduct, 
    Member_Club
ORDER BY 
    extracted_month, 
    extracted_year;

Code Refactoring

Issues Identified:

1. Redundancy in SUBSTRING(CAST(bkdatekey AS VARCHAR)): The same SUBSTRING(CAST(bkdatekey AS VARCHAR)) logic is repeated in both SELECT and GROUP BY.
2. Column Alias Case Consistency: Column names and aliases should follow a consistent naming convention.
3. Improving Readability: SQL keywords should be consistently formatted to improve readability.

Refactored Code:

WITH DateParts AS (
    SELECT 
        Member_Club, 
        MemberProduct, 
        BKJobNo,
        CAST(SUBSTRING(CAST(bkdatekey AS VARCHAR), 5, 2) AS INT) AS extracted_month, 
        CAST(SUBSTRING(CAST(bkdatekey AS VARCHAR), 1, 4) AS INT) AS extracted_year
    FROM 
        [EDW].[RS].[FactRoadServiceJobs]
    WHERE 
        BKDateKey BETWEEN '20191101' AND '20241231'
        AND PatrolUnit LIKE '5MR%'
        AND JobServiceCategory = 'Road Service'
        AND IsCompletedJob = 1
        AND Region = 'm'
)
SELECT 
    Member_Club, 
    MemberProduct, 
    COUNT(BKJobNo) AS eventcount, 
    extracted_month,
    extracted_year
FROM 
    DateParts
GROUP BY 
    extracted_month, 
    extracted_year, 
    MemberProduct, 
    Member_Club
ORDER BY 
    extracted_year,
    extracted_month;

Documentation of Changes

1. Use of Common Table Expression (CTE):

   • Original:

     SUBSTRING(CAST(bkdatekey AS VARCHAR), 5, 2) AS extracted_month, 
     SUBSTRING(CAST(bkdatekey AS VARCHAR), 1, 4) AS extracted_year

   • Refactored:

     CAST(SUBSTRING(CAST(bkdatekey AS VARCHAR), 5, 2) AS INT) AS extracted_month, 
     CAST(SUBSTRING(CAST(bkdatekey AS VARCHAR), 1, 4) AS INT) AS extracted_year

   • Reasoning: The same substring logic was used multiple times. By using a CTE, the transformation is performed once, improving readability and maintainability.

2. Column Alias Case Consistency:

   • Original:

     count(BKJobNo) as eventcount

   • Refactored:

     COUNT(BKJobNo) AS eventcount

   • Reasoning: Consistently using uppercase for SQL keywords follows best practices and improves readability.

3. Ordering of Results:

   • Original:

     ORDER BY extracted_month, extracted_year

   • Refactored:

     ORDER BY extracted_year, extracted_month

   • Reasoning: Ordering by extracted_year first then extracted_month ensures that the results are grouped by year and then by month within each year, providing a more logical chronological order.

Benefits of Refactoring

• Improved Readability: By using a CTE and consistently formatting SQL keywords, the query is easier to read and understand.
• Maintainability: Reducing redundancy and centralizing the date transformation logic makes future modifications and debugging easier.
• Performance: While performance improvements may be minimal, better structuring of the query can help in optimizing execution for more complex queries or larger datasets.