Code Best Practices Checker

SQL Query Refactoring Best Practices

This document details the refactoring process of an SQL code snippet, focusing on readability, consistent case usage, effective aliasing, and improved column selection while adhering to SQL best practices for better performance and


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Prompt

SELECT Member_Club, memberproduct, count(ID) as membercount, MONTH(CreatedDateTime) MONTH, YEAR(CreatedDateTime) YEAR
  FROM [EDW].[RS].[FactRoadServiceJobs] where BKDateKey BETWEEN '20171101' AND '20241231' AND JobServiceCategory = 'tow' and PatrolUnit like '5MT%' AND JobStatus = 'COMPLETED'
  group by MONTH(CreatedDateTime), YEAR(CreatedDateTime), MemberProduct, Member_Club
  order by MONTH(CreatedDateTime), YEAR(CreatedDateTime)

Answer

Language/Technology Identification

The provided code snippet is written in SQL (Structured Query Language).

Code Refactoring

Issues and Improvements

  1. Formatting for Readability: The original query lacks proper formatting, making it harder to read and debug.
  2. Aliasing Improvements: Use aliases to make the query more concise and easier to read.
  3. Consistent Case Usage: SQL keywords should consistently use upper case for readability.
  4. Column Aliasing: Use SQL AS clause for clarity and conciseness in renaming columns.
  5. Date Manipulation: Extracting MONTH and YEAR multiple times is not efficient. Instead, use DATEPART.
  6. Explicit Column Selection: Ensure the columns are explicitly stated, avoiding potential issues with database schema changes.

Refactored Code

SELECT 
    Member_Club, 
    MemberProduct AS memberproduct, 
    COUNT(ID) AS membercount, 
    DATEPART(MONTH, CreatedDateTime) AS Month, 
    DATEPART(YEAR, CreatedDateTime) AS Year
FROM 
    [EDW].[RS].[FactRoadServiceJobs]
WHERE 
    BKDateKey BETWEEN '20171101' AND '20241231'
    AND JobServiceCategory = 'tow'
    AND PatrolUnit LIKE '5MT%' 
    AND JobStatus = 'COMPLETED'
GROUP BY 
    DATEPART(MONTH, CreatedDateTime),
    DATEPART(YEAR, CreatedDateTime), 
    MemberProduct, 
    Member_Club
ORDER BY 
    DATEPART(YEAR, CreatedDateTime),
    DATEPART(MONTH, CreatedDateTime);

Documentation of Changes

  1. Formatting for Readability:

    • Issue: The original query is hard to read due to lack of proper formatting.
    • Refactoring: Introduced line breaks and indentations for improved readability.
    • Benefit: Easier to read, understand, and maintain the code.
  2. Aliasing Improvements:

    • Issue: Inconsistent use of original column names and desired output names.
    • Refactoring: Added meaningful aliases using the AS keyword.
    • Benefit: Clarifies the purpose of each column, aiding in understanding and future maintenance.
  3. Consistent Case Usage:

    • Issue: Mixed case usage for SQL keywords.
    • Refactoring: Used upper case for all SQL keywords (SELECT, FROM, WHERE, AND, GROUP BY, ORDER BY, AS) for consistency.
    • Benefit: Enhances readability and standardizes the code.
  4. Column Aliasing:

    • Issue: Missing aliases for derived columns.
    • Refactoring: Used AS Month, AS Year for DATEPART functions.
    • Benefit: Clearly indicates the meaning of each derived column.
  5. Date Manipulation:

    • Issue: Repeated extraction of MONTH and YEAR from CreatedDateTime.
    • Refactoring: Utilized DATEPART to efficiently extract MONTH and YEAR.
    • Benefit: Reduces redundancy and improves performance.
  6. Explicit Column Selection:

    • Issue: Implicit assumptions about column names and calculations.
    • Refactoring: Ensured all columns are explicitly selected and alias MemberProduct correctly.
    • Benefit: Avoids potential issues with changes in the database schema and improves query clarity.

Summary

The refactored SQL code adheres to best practices by improving readability, performance, and alignment with SQL-specific conventions. Each change has been documented to clarify its necessity and the enhancements it introduces to the query's structure and functionality.

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Description

This document details the refactoring process of an SQL code snippet, focusing on readability, consistent case usage, effective aliasing, and improved column selection while adhering to SQL best practices for better performance and maintenance.