Go SQL map 1:M relation json array to slice

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05-09-2024

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Mapping 1:M Relationships in Go with SQLx: A Comprehensive Guide

This article explores how to efficiently map one-to-many relationships between database tables in Go using the popular SQLx library. We'll build upon a common scenario: retrieving product data along with its associated images from a PostgreSQL database.

The Challenge

You want to represent a 1:M relationship in your Go code, where a Product can have multiple Image objects. While the sqlx library is great for handling simple queries, handling complex relationships requires additional techniques. Let's examine how to effectively handle this situation.

Understanding the Issue

The issue arises because sqlx doesn't automatically handle complex data structures, especially arrays returned from aggregate functions like JSON_AGG. Our initial attempt to use JSON_AGG encounters the error:

sql: Scan error on column index 26, name "images": unsupported Scan, storing driver.Value type []uint8 into type *model.ImageList

This error highlights the incompatibility between the []uint8 (raw bytes) returned from the database and the expected *model.ImageList struct.

The Solution: Custom Scanners

The core solution lies in implementing custom Scan methods for our struct. This allows us to define how sqlx should handle data conversion from the database format to our Go struct.

Step-by-Step Implementation

1. Define Our Structures:

   type Image struct {
     ID       int    `db:"id"`
     URL      string `db:"url"`
     ProductID int    `db:"product_id"`
   }
   
   type ImageList []*Image
   
   type Product struct {
     ID     int      `db:"id"`
     Name   string    `db:"name"`
     Images ImageList `db:"images"`
   }
   

2. Custom Scan Method for ImageList:

   func (il *ImageList) Scan(value interface{}) error {
       bytes, ok := value.([]byte)
       if !ok {
           return fmt.Errorf("failed to convert value to []byte")
       }
       var imageList []Image
       err := json.Unmarshal(bytes, &imageList)
       if err != nil {
           return fmt.Errorf("failed to unmarshal image list: %w", err)
       }
       *il = append(*il, imageList...) // Append individual images to the slice
       return nil
   }
   

   This Scan method allows us to receive the JSON_AGG output as []byte and then unmarshal it into a slice of Image structs. The *il = append(*il, imageList...) line ensures that the unmarshaled imageList is added to our existing ImageList pointer.

3. Updated Query:

   q := `SELECT 
         p.*,
         COALESCE(JSON_AGG(img.*) FILTER (WHERE img.product_id IS NOT NULL), '[]'::json) AS images
         FROM product p
         LEFT JOIN product_image img ON p.id = img.product_id
         WHERE p.id = 1
         GROUP BY p.id`
   

4. Fetching the Data:

   var p Product
   if err := sqlxdb.Get(&p, q); err != nil {
       fmt.Printf("Error: %v\n", err)
       return
   }
   

Key Takeaways:

• Embrace Custom Scanners: For complex data structures, custom Scan methods are your key to seamless data mapping.
• Leverage JSON_AGG: Using JSON_AGG in your SQL query provides a concise way to aggregate related data into a JSON array, which you can then parse in your Go code.
• Efficiency and Elegance: This approach avoids the need for multiple queries, ensuring efficient data retrieval and a cleaner codebase.

Beyond Basic Mapping

The concept of custom Scan methods extends far beyond basic JSON arrays. You can adapt this technique to handle various data formats and complex data structures. This gives you unparalleled control over how your database data is translated into your Go application's world.

Remember to cite the original Stack Overflow question: https://stackoverflow.com/questions/54601529/efficiently-mapping-one-to-many-many-to-many-database-to-struct-in-golang

This approach provides a flexible and robust solution for mapping 1:M relationships in your Go applications. You can adapt and extend these principles to handle complex data relationships, ultimately making your code more efficient and readable.