Solving EF Core Challenges with INNER JOINS and LEFT JOINS

Описание: Discover how to effectively handle `INNER JOINS` and `LEFT JOINS` in `Entity Framework Core` (EF Core) and overcome common difficulties when querying complex data structures.
---
This video is based on the question https://stackoverflow.com/q/67999448/ asked by the user 'spoilerd do' ( https://stackoverflow.com/u/9480116/ ) and on the answer https://stackoverflow.com/a/68000470/ provided by the user 'spoilerd do' ( https://stackoverflow.com/u/9480116/ ) at 'Stack Overflow' website. Thanks to these great users and Stackexchange community for their contributions.

Visit these links for original content and any more details, such as alternate solutions, latest updates/developments on topic, comments, revision history etc. For example, the original title of the Question was: EF Core difficulty with INNER JOINS and LEFT JOINS

Also, Content (except music) licensed under CC BY-SA https://meta.stackexchange.com/help/l...
The original Question post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license, and the original Answer post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license.

If anything seems off to you, please feel free to write me at vlogize [AT] gmail [DOT] com.
---
Understanding the Challenge with EF Core Joins

When working with large databases in Entity Framework Core (EF Core), developers often encounter challenges related to the use of INNER JOINS and LEFT JOINS. This becomes particularly evident when retrieving data that spans multiple related tables, where the relationships can get quite complex. This guide will guide you through a scenario that exemplifies these challenges and provide a detailed breakdown of possible solutions.

A Real-World Problem

Imagine you are trying to fetch data involving multiple entities, where you need to perform six joins to pull together necessary information. The complexity of these relationships can lead to issues with your queries returning either too much or not enough data due to EF Core's handling of joins.

The Attempt

In an attempt to retrieve data, the developer tried using the Include and ThenInclude methods in EF Core. Here is the initial code snippet that demonstrates this approach:

[[See Video to Reveal this Text or Code Snippet]]

While this approach maps very well to the Enquiry class, it relies heavily on LEFT JOINS, which may introduce unwanted data and complicate retrieval.

Exploring Available Solutions

Given the challenges outlined, let's explore two primary options for approaching queries in EF Core, particularly focusing on how to efficiently manage joins.

Option 1: Leveraging LINQ for INNER JOINS

One effective method is to construct a LINQ query that inherently uses INNER JOINS. Here’s the adapted query:

[[See Video to Reveal this Text or Code Snippet]]

While this LINQ query uses INNER JOINS, it effectively pairs each piece of related data, ensuring the results reflect only the intended information without the unnecessary overhead of extra data.

Option 2: Building a Multi-Step JOIN

As a refinement of the LINQ approach, it was suggested by community feedback to start with the most granular entity and build up from there. By performing the joins starting with your base class—such as Deviation—and working up to Enquiry, you can ensure that only the necessary joins are executed.

Here’s how you can structure that:

[[See Video to Reveal this Text or Code Snippet]]

This nested structure reflects a careful consideration of which joins are actually required, thus enabling a more focused query result.

Conclusion

In summary, while EF Core's default behavior may often lean towards LEFT JOINS, understanding how to construct your queries—either through LINQ or strategic join ordering—can provide the necessary control to ensure you retrieve precisely the data you need. This not only improves performance but also enhances the clarity and maintainability of your code.

By employing these techniques, you can face EF Core challenges with confidence and efficiency, optimizing your data retrieval processes effectively.