Best practices for optimizing Django queries with AWS RDS for large datasets
This might be a silly question, but I'm wondering if anyone has experience with Currently developing a Django application that utilizes PostgreSQL on AWS RDS, and performance has become a significant concern as our dataset grows. I've been profiling the database queries and noticed that certain queries take too long to execute, especially when filtering large result sets. For instance, I've implemented the following query to retrieve data: ```python class MyModel(models.Model): name = models.CharField(max_length=100) created_at = models.DateTimeField(auto_now_add=True) # Fetching records with a filter results = MyModel.objects.filter(created_at__gte='2023-01-01').order_by('name') ``` This query works fine for smaller datasets but seems to lag when the number of records exceeds a certain threshold. I tried adding indexes to the `created_at` field, which did help somewhat, but the performance is still not optimal. In addition, I’ve explored using `select_related` and `prefetch_related`, yet the performance gains aren't as noticeable as I hoped. Here's a snippet of how I attempted to apply those: ```python results = MyModel.objects.select_related('related_model').filter(created_at__gte='2023-01-01') ``` I also read about using pagination with Django's `Paginator` class to limit the number of results returned at once, but I'm unsure if that will address the underlying query performance issues. Would leveraging AWS-specific features like read replicas or using Amazon ElastiCache for caching data yield better results? I'm hesitant about making changes that could impact the existing application workflow. Any insights or suggestions on how to approach database optimization in this context would be greatly appreciated. What other strategies could I consider to enhance the efficiency of my database queries in this setup? This is my first time working with Python latest. Thanks, I really appreciate it!