Problems with joinedload?

Avoiding N+1 Queries in SQLAlchemy with Joined Load

What’s an N+1 Query Problem?

The N+1 query problem happens when you fetch a list of items (1 query) and then make additional queries for each item in the list (N queries), leading to (N+1) queries and poor performance.

Understanding N+1 Queries in SQLAlchemy

In SQLAlchemy, this occurs when you load parent objects and lazily load their related child objects. Lazy loading means that related objects are not fetched until they are accessed. Here’s an example:

python

parents = session.query(Parent).all()  # 1 query
for parent in parents:
    print(parent.children)  # N queries

Mitigating N+1 with Eager Loading

To avoid the N+1 problem, we use eager loading, which fetches related objects as part of the initial query.

Joined Load

joinedload lets you load related objects in the same query:

python

from sqlalchemy.orm import joinedload

parents = session.query(Parent).options(joinedload(Parent.children)).all()

This reduces the queries to just one. Here’s the SQL it generates:

sql

SELECT parent.*, child.*
FROM parent
LEFT OUTER JOIN child ON parent.id = child.parent_id

This approach works well for simple relationships but can become problematic with deeply nested or large relationships because it can result in a large result set with many redundant data rows.

Example Problem with Joined Load

If a Parent has many Children and each Child has many Grandchildren, using joinedload for both levels can generate a huge result set:

python

parents = session.query(Parent).options(joinedload(Parent.children).joinedload(Child.grandchildren)).all()

While this only runs one query, the result set can become enormous, leading to increased memory usage and longer query times.

Subquery Load

subqueryload mitigates this by generating separate queries for related objects, reducing redundancy:

python

from sqlalchemy.orm import subqueryload

parents = session.query(Parent).options(subqueryload(Parent.children)).all()

Here’s the SQL it generates:

sql

SELECT parent.*
FROM parent;

SELECT child.*
FROM child
WHERE child.parent_id IN (<list_of_parent_ids>);

Why Use Subquery Load?

Efficiency with Large Data Sets: subqueryload is more efficient when dealing with large or deeply nested relationships, as it avoids generating a huge result set with redundant data.

Avoiding Cartesian Products: With deeply nested relationships, joinedload can lead to a Cartesian product of rows, making queries slow and memory-intensive.

However, keep in mind that subqueryload introduces the overhead of additional queries, which can be a trade-off depending on your specific use case.

Summary

Use joinedload for simple, direct relationships to minimize the number of queries.

Use subqueryload for complex, large, or deeply nested relationships to avoid large result sets and improve performance.

That’s it! Keep your queries efficient and your applications fast.