52  
dotnet
Advertisement
Поиск  
Always will be ready notify the world about expectations as easy as possible: job change page
Nov 27, 2023

Insert 1 million dummy product data into SQL Server

Автор:
Источник:
Просмотров:
1139

Use the Bogus library to generate and insert 1 million dummy product data into the SQL Server database

C#

We need to create 1 million dummy product data into the SQL Server database, which can be used for development or performance testing purposes.

The Project

The project is a console application using .NET 6.0 as a framework.

The project name is InsertMillionRecords.

InsertMillionRecords

We will use the Bogus package to generate random product data.

We use Entity Framework Core as the data access layer.

Entity Framework Core

Product Model

To model the Products table in the database, we need to create the Product class:

public class Product
{
    public int Id { get; set; }
    public string Code { get; set; }
    public string Description { get; set; }
    public string Category { get; set; }
    public decimal Price { get; set; }
}

Entity Framework Data Context

Next, we create the Entity Framework data context class:

using Microsoft.EntityFrameworkCore;

namespace InsertMillionRecords;
public class DataContext : DbContext
{
    public DataContext(DbContextOptions<DataContext> options) : base(options)
    {
    }

    public DbSet<Product> Products { get; set; }
}

The Program.cs File

Initialize Data Context

First, we need to initialize the data context:

var connectionString = "Data Source=localhost; Initial Catalog=Product; Integrated Security=True";
var contextOptionsBuilder = new DbContextOptionsBuilder<DataContext>();
contextOptionsBuilder.UseSqlServer(connectionString);
var context = new DataContext(contextOptionsBuilder.Options);

We've made things simpler by hardcoding the connection string. No need to worry about it!

Create Database

Every time the script runs, we need to ensure that the database is recreated.

await context.Database.EnsureDeletedAsync();
await context.Database.EnsureCreatedAsync();

Setup Bogus Faker Class

First, we initialize the Faker<Product> object.

Next, we use the RuleFor() method to set up each property of the Product class.

The self-explained code:

var faker = new Faker<Product>();
faker.RuleFor(p => p.Code, f => f.Commerce.Ean13());
faker.RuleFor(p => p.Description, f => f.Commerce.ProductName());
faker.RuleFor(p => p.Category, f => f.Commerce.Categories(1)[0]);
faker.RuleFor(p => p.Price, f => f.Random.Decimal(1, 1000));

Generate 1 Million Dummy Product Data

var products = faker.Generate(1_000_000);

The products variable now contains 1 million of product data!

Create 10 Batches of Insertion

There is a possibility that a timeout will occur if we insert 1 million records at a time.

Therefore, we will split the process into 10 batches. Each batch will insert 100K records at a time.

var batches = products
    .Select((p, i) => (Product: p, Index: i))
    .GroupBy(x => x.Index / 100_000)
    .Select(g => g.Select(x => x.Product).ToList())
    .ToList();

Insert Each Batch into the Database

var count = 0;
foreach (var batch in batches)
{
    batchCount++;
    Console.WriteLine($"Inserting batch {count} of {batches.Count}...");

    await context.Products.AddRangeAsync(batch);
    await context.SaveChangesAsync();
}

The complete code of the Program.cs file:

using Bogus;
using InsertMillionRecords;
using Microsoft.EntityFrameworkCore;
using System.Diagnostics;

// initialize data context
var connectionString = "Data Source=localhost; Initial Catalog=Product; Integrated Security=True";
var contextOptionsBuilder = new DbContextOptionsBuilder<DataContext>();
contextOptionsBuilder.UseSqlServer(connectionString);
var context = new DataContext(contextOptionsBuilder.Options);

// create database
await context.Database.EnsureDeletedAsync();
await context.Database.EnsureCreatedAsync();

// setup bogus faker
var faker = new Faker<Product>();
faker.RuleFor(p => p.Code, f => f.Commerce.Ean13());
faker.RuleFor(p => p.Description, f => f.Commerce.ProductName());
faker.RuleFor(p => p.Category, f => f.Commerce.Categories(1)[0]);
faker.RuleFor(p => p.Price, f => f.Random.Decimal(1, 1000));

// generate 1 million products
var products = faker.Generate(1_000_000);

var batches = products
    .Select((p, i) => (Product: p, Index: i))
    .GroupBy(x => x.Index / 100_000)
    .Select(g => g.Select(x => x.Product).ToList())
    .ToList();

// insert batches
var stopwatch = new Stopwatch();
stopwatch.Start();

var count = 0;
foreach (var batch in batches)
{
    count++;
    Console.WriteLine($"Inserting batch {count} of {batches.Count}...");

    await context.Products.AddRangeAsync(batch);
    await context.SaveChangesAsync();
}

stopwatch.Stop();

Console.WriteLine($"Elapsed time: {stopwatch.Elapsed}");
Console.WriteLine("Press any key to exit...");

Run the Application

Now, let’s run the application. We can use Release mode to fasten the process.

It took 1 minute and 9 seconds on my machine:

Inserting batch

And now we have 1 million records in the Products table:

Products table

I am planning to use these dummy data for testing the full-text search feature in SQL Server.

The source code of this post can be found here: https://github.com/juldhais/InsertMillionRecords

Thanks for reading 👍

Похожее
Aug 9, 2021
Author: MBARK T3STO
If you’re anything like me, you’ve looked for ways of making your applications faster. In this article, I’ll show you a somewhat unknown class in the .NET framework that makes lazy creation of objects easy to do and thread safe.The...
Apr 3, 2023
Author: Hr. N Nikitins
Master the art of caching in .NET applications to improve performance and user experience.Caching is a powerful technique to improve application performance and response times. By temporarily storing the results of expensive operations or frequently accessed data, you can reduce...
May 14, 2023
Author: Ravi Raghav
What is Kafka?Kafka is a distributed streaming platform developed by the Apache Software Foundation. It is designed to handle high-volume, real-time data streams and is commonly used for building data pipelines, stream processing applications, and real-time analytics.At its core, Kafka...
Mar 18
Author: codezone
File reading operations in C# are crucial for many applications, often requiring efficiency and optimal performance. When handling file reading tasks, employing the right strategies can significantly impact the speed and resource utilization of your application. Here are some best...
Написать сообщение
Почта
Имя
*Сообщение


© 1999–2024 WebDynamics
1980–... Sergey Drozdov
Area of interests: .NET Framework | .NET Core | C# | ASP.NET | Windows Forms | WPF | HTML5 | CSS3 | jQuery | AJAX | Angular | React | MS SQL Server | Transact-SQL | ADO.NET | Entity Framework | IIS | OOP | OOA | OOD | WCF | WPF | MSMQ | MVC | MVP | MVVM | Design Patterns | Enterprise Architecture | Scrum | Kanban