Django QuerySet Performance guide: Slow Aggregation with Annotate and Fallback Values
I'm building a feature where I recently switched to Hey everyone, I'm running into an issue that's driving me crazy..... I'm relatively new to this, so bear with me. I'm working with a performance scenario while trying to generate a report in Django that uses the `annotate` method to aggregate values. I'm working with Django 3.2 and PostgreSQL as my database. The goal is to fetch the total sales for each product category, but the query takes a important time to execute, especially with a large dataset. I've tried adding a fallback value using `Coalesce`, but it seems to make the query even slower. Here's the code snippet I am using: ```python from django.db.models import Sum, F, Value from django.db.models.functions import Coalesce report = (ProductCategory.objects.annotate( total_sales=Coalesce(Sum('products__sales'), Value(0)) ).order_by('-total_sales')) ``` I've also added an index on the `sales` field in the `products` table, but it doesn't seem to help much. The `products` table has over 100,000 entries, and the `sales` field is frequently updated. Any advice on how to optimize this query or alternatives that could yield better performance? My current query execution time is around 4 seconds, which is unacceptable for our reporting needs. Additionally, I've checked the PostgreSQL execution plan using `EXPLAIN` and noticed a sequential scan, which might indicate that the index isn't being used effectively. Am I missing some indexing strategy or optimization techniques here? Has anyone else encountered this? The project is a CLI tool built with Python. Any advice would be much appreciated. The stack includes Python and several other technologies. I recently upgraded to Python stable. Hoping someone can shed some light on this.