Developing a Go-Based ETL Pipeline for Database Migration

Table of Contents

  1. Introduction
  2. Prerequisites
  3. Setting up the Database
  4. Connecting to the Database
  5. Extracting Data
  6. Transforming Data
  7. Loading Data
  8. Conclusion

Introduction

In this tutorial, we will learn how to develop an ETL (Extract, Transform, Load) pipeline using Go for database migration. The ETL process involves extracting data from a source database, transforming it as needed, and loading it into a target database. By the end of this tutorial, you will have a solid understanding of how to build a Go-based ETL pipeline and be able to apply it to other database migration scenarios.

Prerequisites

To follow this tutorial, you should have a basic understanding of the Go programming language. Familiarity with databases and SQL would also be beneficial. Additionally, you will need the following software and tools:

  • Go programming language (version 1.16 or later)
  • MySQL or PostgreSQL database

Setting up the Database

To start, we need to set up a source and target database. In this example, let’s assume we want to migrate data from a MySQL database to a PostgreSQL database. Follow these steps:

  1. Install and set up MySQL and PostgreSQL databases if you haven’t already.

  2. Create a source MySQL database and a target PostgreSQL database.

  3. In the source MySQL database, create a table called products with the following schema:

     CREATE TABLE products (
   id INT PRIMARY KEY,
   name VARCHAR(255),
   price DECIMAL(10, 2),
   created_at TIMESTAMP
 );

  4. Populate the products table with some sample data.

  5. Confirm that the target PostgreSQL database is empty.

Connecting to the Database

Let’s start by establishing connections to both the source and target databases using Go.

Create a new Go file called main.go and import the necessary packages:

package main

import (
	"database/sql"
	"fmt"

	_ "github.com/go-sql-driver/mysql"
	_ "github.com/lib/pq"
)

In the main function, establish connections to the MySQL and PostgreSQL databases:

func main() {
	mysqlDB, err := sql.Open("mysql", "root:password@tcp(localhost:3306)/source_db")
	if err != nil {
		panic(err)
	}
	defer mysqlDB.Close()

	postgresDB, err := sql.Open("postgres", "postgres://user:password@localhost/target_db?sslmode=disable")
	if err != nil {
		panic(err)
	}
	defer postgresDB.Close()

	fmt.Println("Connected to databases successfully.")

	// Continue with ETL pipeline implementation
}

Replace root:password@tcp(localhost:3306)/source_db with the correct MySQL connection details, and postgres://user:password@localhost/target_db?sslmode=disable with the correct PostgreSQL connection details.

Extracting Data

Next, we need to extract data from the source MySQL database.

func main() {
	// ...

	rows, err := mysqlDB.Query("SELECT * FROM products")
	if err != nil {
		panic(err)
	}
	defer rows.Close()

	for rows.Next() {
		var id int
		var name string
		var price float64
		var createdAt time.Time

		err := rows.Scan(&id, &name, &price, &createdAt)
		if err != nil {
			panic(err)
		}

		// Perform required data transformations

		// Load data into the target database

		fmt.Println(id, name, price, createdAt)
	}

	// ...
}

The code above executes a SQL query to select all rows from the products table. It then iterates over the result set using rows.Next() and retrieves the values into variables. You can perform any necessary data transformations inside the loop.

Transforming Data

Now that we have extracted the data, we can perform transformations as needed.

For example, let’s assume we want to convert the price from USD to EUR using a fixed exchange rate of 0.86. We can modify the data transformation part of the loop as follows:

for rows.Next() {
	// ...

	priceEUR := price * 0.86

	// ...
}

You can apply any required data transformations based on your specific migration needs.

Loading Data

Finally, we need to load the transformed data into the target PostgreSQL database.

func main() {
	// ...

	stmt, err := postgresDB.Prepare("INSERT INTO products (id, name, price, created_at) VALUES ($1, $2, $3, $4)")
	if err != nil {
		panic(err)
	}
	defer stmt.Close()

	for rows.Next() {
		// ...

		_, err := stmt.Exec(id, name, priceEUR, createdAt)
		if err != nil {
			panic(err)
		}

		fmt.Println("Data loaded successfully.")
	}

	// ...
}

The code above prepares an INSERT statement for the products table in the PostgreSQL database. Inside the loop, it executes the statement using the values retrieved from the source MySQL database.

Conclusion

Congratulations! You have successfully developed a Go-based ETL pipeline for database migration. By following this tutorial, you learned how to connect to source and target databases, extract data from the source database, perform transformations, and load the transformed data into the target database. This foundational knowledge can be applied to various real-world scenarios and help you migrate data efficiently and effectively.

Throughout the tutorial, we covered the basics of establishing database connections, querying and iterating over result sets, and performing data transformations. Remember to adapt the code according to your specific database setup and migration requirements.

Please note that this tutorial provides a simplified example. In production scenarios, you should handle errors, use batch inserts for better performance, and implement proper logging and error handling strategies.

Good luck with your future database migration projects!

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