What problems can arise when working with large and complex queries through ORM?

When working with large and complex queries through ORM, the following issues may arise:

• Performance loss: ORM often generates less optimal SQL queries than manually written ones, leading to slow performance.
• N+1 query problem: when fetching related data, ORM may execute many separate queries instead of a single combined one, significantly slowing down execution.
• Debugging difficulty: generated ORM code can be hard to read and optimize.
• Functionality limitations: some complex SQL constructs (e.g., window functions, subqueries) may be poorly supported or inconvenient to implement via ORM.

Example of the N+1 problem in Django ORM:

# Poor: a separate query to books for each author
authors = Author.objects.all()
for author in authors:
    books = author.book_set.all()  # Separate query for each author

# Better to use select_related or prefetch_related
authors = Author.objects.prefetch_related('book_set').all()
for author in authors:
    books = author.book_set.all()  # Queries are optimized

For large queries, it is sometimes better to use raw SQL or optimize ORM queries using the methods provided by the framework.