Laravel Cursor and Eager loading

GitHub - miroslaws8/laravel-chunk-cursor: This allows you to fetch large datasets in chunks using a…

As I mentioned in my previous article, we’ve encountered an issue in Laravel when using the cursor method where we couldn’t eager load relationships. In this article, I’ll delve into my implementation to solve this problem.

How to Solve the Issue

I’ve developed a package that adds the chunkCursor method to the Eloquent builder, allowing us to harness the power of PHP generators and Laravel collections.

Let’s break it down with an example. Suppose we have a task to update all Users and their Account settings. Each User has one AccountSetting associated with them in a one-to-one relationship. To circumvent the n+1 problem, we typically use eager loading, but in this scenario, we want to use a cursor to avoid exceeding memory limits.

The issue arises because it’s not possible to load relationships with a cursor. This is where my package comes to the rescue, allowing us to use eager loading together with a cursor.

Let’s address this issue

First, we install the package:

composer require itsimiro/laravel-chunk-cursor

Then, we utilize the chunkCursormethod:

User::query()->with([‘settings’])->chunkCursor(50)->each(function (Collection $users) {
   foreach ($users as $user) {
     // Process user… With eager loading! 
   }
});

Now we can efficiently handle users and their associated customizations without worrying about memory scarcity and the n+1 problem.

Compare the execution time

If we compare the execution times, the chunkCursor method is approximately twice as fast as the regular cursor, and it significantly reduces the number of database queries.

By leveraging chunkCursor, we observe a notable improvement in performance, making it a more efficient choice for processing large datasets while maintaining eager loading capabilities.

Сonclusion

In conclusion, by utilizing the chunkCursor method provided by the itsimiro/laravel-chunk-cursor package, we've successfully tackled the challenge of eager loading within the context of cursors in Laravel. This approach not only enhances performance by approximately doubling the execution speed but also significantly reduces the number of database queries, resulting in more efficient processing of large datasets.

With the ability to seamlessly combine eager loading and cursor-based iteration, we can confidently handle tasks that involve updating or processing relationships between models without worrying about memory constraints or sacrificing performance.

Incorporating this technique into your Laravel projects can lead to smoother and more optimized data processing workflows, ultimately enhancing the overall performance and scalability of your applications.