Overcoming Optimization Challenges with Morphic Relationships in Laravel

Introduction

In Laravel development, leveraging morphic relationships adds flexibility to entity configuration. However, as projects scale and entities interconnect via polymorphic relationships, optimization challenges arise. This article delves into strategies to tackle these challenges effectively.

Exploring Optimization Challenges

As our project evolved, we increasingly relied on polymorphic relationships to connect entities. This architectural choice, while enhancing flexibility, posed optimization hurdles, especially concerning entity manipulation such as copying, updating, and deleting.

The Deletion Dilemma

Consider a scenario where a Hub entity connects to a Section, which in turn relates to a Page, and subsequently to an Asset via polymorphic associations. Deleting such interconnected entities posed a significant challenge. Standard cascade deletion didn’t suffice for polymorphic relationships, necessitating a custom deletion implementation. Despite crafting an observer for the forceDelete event, we encountered inefficiencies. An inspection revealed approximately 300 queries being executed due to the cursor() method’s incompatibility with eager loading. Transitioning to chunkById() or lazy() resolved this issue.

Navigating Entity Duplication

Copying an entity, particularly a Hub along with its associated entities, proved daunting. Employing cursor() initially resulted in over 300 queries, impacting performance. Mitigating this, we devised a solution utilizing batch insert to consolidate inserts into a single query. Additionally, transitioning to chunkById() or lazy() addressed the incompatibility with eager loading, streamlining the process.

Key Takeaways

- Utilize cursor() when execution time is non-critical.
- Explore alternatives to cursor() when preloading relations is necessary.
- Employ batchInsert for bulk data insertion, reducing database queries.
- Chunk data inserts to optimize performance, avoiding attempts to insert large volumes of data in a single operation.

Conclusion

Optimizing morphic relationships in Laravel demands strategic thinking and tailored solutions. By understanding the nuances of these relationships and adopting appropriate optimization techniques, developers can overcome performance bottlenecks and ensure the scalability of Laravel applications.