Handling Ordering in Rails with includes and Aliased Joins

Handling Ordering in Rails with includes and Aliased Joins

When working with ActiveRecord in Rails, it’s common to use includes to eager-load associations and prevent N+1 queries. However, issues arise when ordering by an associated table’s column—especially if Rails aliases the table name in SQL.

In this article, we’ll explore different approaches to ordering records without breaking eager loading and causing unexpected errors.

The Problem: Ordering by an Associated Table

Consider the following query:

report.viewers
  .includes(user: :organization)
  .order("users.last_name_alphabet DESC")

🚨 Potential Issues:

• Missing Join: includes(:user) does not guarantee a SQL JOIN. If Rails decides to load users in a separate query, the ORDER BY users.last_name_alphabet will fail.
• Aliased Table Name: If Rails automatically assigns an alias to users, referencing users.last_name_alphabet directly will cause an error.

Fixing the N+1 Query Problem: Two Approaches

1️⃣ Using a Single Big Query (JOIN)

To ensure all data is retrieved in a single SQL query, we can force a JOIN using references:

report.viewers
  .includes(user: :organization)
  .references(:user)
  .order("users.last_name_alphabet DESC")

✅ Pros:

• Ensures everything is fetched in one query, reducing overall database load.
• Prevents N+1 issues by retrieving all necessary data at once.

⚠️ Cons:

• Can result in huge queries when multiple associations are included, leading to performance issues.
• Increases memory consumption because all data is loaded at once.

Example of the Generated SQL:

SELECT viewers.*, users.* FROM viewers
LEFT JOIN users ON users.id = viewers.user_id
ORDER BY users.last_name_alphabet DESC;

🔹 Dangerous Scenario: If users has a large number of columns or there are additional complex joins (e.g., joining organizations), this query can slow down significantly.

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2️⃣ Using Multiple Queries (Eager Loading)

Alternatively, we can allow Rails to run multiple queries while still preventing N+1 queries:

report.viewers
  .includes(user: :organization)
  .order(User.arel_table[:last_name_alphabet].desc)

✅ Pros:

• Loads viewers first, then fetches associated users and organizations in separate queries.
• Reduces query complexity, making it more efficient in cases with large datasets.
• Uses indexed lookups instead of potentially costly joins.

⚠️ Cons:

• Rails may not automatically apply the order to the in-memory objects after retrieval.
• Can still cause multiple queries, increasing overall query count.

Example of the Generated SQL:

SELECT * FROM viewers;
SELECT * FROM users WHERE id IN (...);
SELECT * FROM organizations WHERE id IN (...);

✅ Better Performance for Large Datasets: Instead of one massive query with joins, Rails fetches necessary data separately, reducing memory overhead.

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Understanding references and When to Use It

The references method in ActiveRecord ensures that includes performs an SQL JOIN instead of a separate query. If ordering by an associated table’s column, adding references helps avoid missing table errors:

report.viewers
  .includes(user: :organization)
  .order("users.last_name_alphabet DESC")
  .references(:user)

✅ Why Use references(:user)?

• Forces a JOIN, ensuring the users table is included in the query.
• Prevents missing table errors when ordering by an associated column.

🚨 However, references alone does not solve aliasing issues, which is where Arel comes in.

Solution 1: Use Arel to Handle Table Names Dynamically

Arel helps us reference columns dynamically without worrying about aliasing:

report.viewers
  .includes(user: :organization)
  .order(User.arel_table[:last_name_alphabet].desc)

✅ Why This Works:

• User.arel_table[:last_name_alphabet] ensures the column reference is dynamic.
• Avoids hardcoding users.last_name_alphabet, making it resilient to aliasing.

Solution 2: Ensure users is in the Query Using left_joins

If ordering still fails, force users into the query using left_joins:

report.viewers
  .includes(user: :organization)
  .left_joins(:user)
  .order(User.arel_table[:last_name_alphabet].desc)

🔹 When to Use This:

• If Rails optimizes includes(:user) into a separate query, left_joins(:user) ensures users is part of the main query.
• Useful when ordering by an associated table’s column without breaking eager loading.

Solution 3: Check for Table Aliases in SQL

To verify if Rails is aliasing users, inspect the generated SQL:

puts report.viewers
  .includes(user: :organization)
  .order(User.arel_table[:last_name_alphabet].desc)
  .to_sql

If the output shows something like:

SELECT ... FROM viewers
LEFT JOIN users AS u ON u.id = viewers.user_id
ORDER BY users.last_name_alphabet DESC;

🚨 This will fail because users.last_name_alphabet does not exist (it’s u.last_name_alphabet).

✅ Fix: Reference the correct alias dynamically:

user_alias = report.viewers.arel_table.alias('u')
report.viewers
  .joins("LEFT JOIN users AS u ON u.id = viewers.user_id")
  .order("u.last_name_alphabet DESC")

Comparison Table: Which Approach to Use?

Approach	Fixes N+1?	Prevents Aliasing Issues?	Ensures users is in Query?
includes(:user).order("users.last_name_alphabet DESC")	✅	❌ (Fails if alias is applied)	❌ (Might run a second query)
includes(:user).references(:user).order("users.last_name_alphabet DESC")	✅	❌ (Fails if alias is applied)	✅
includes(:user).order(User.arel_table[:last_name_alphabet].desc)	✅	✅	❌ (Might still use a second query)
includes(:user).left_joins(:user).order(User.arel_table[:last_name_alphabet].desc)	✅	✅	✅
joins("LEFT JOIN users AS u ON u.id = viewers.user_id").order("u.last_name_alphabet DESC")	❌	✅	✅

Conclusion

• Use a single JOIN query (references) for simple cases but avoid it for large datasets.
• For large datasets, prefer multiple queries (includes without references) to avoid performance issues.
• If aliasing is detected, manually reference the alias (u.last_name_alphabet).
• Arel is the safest and most flexible way to reference columns while avoiding SQL errors.

By understanding how Rails generates SQL and when aliasing occurs, we can confidently sort records while avoiding N+1 pitfalls. 🚀