Hi everyone, I am Emmanuel Katto. I’m working on a large-scale data warehousing project using dbt, and I’m running into performance issues with my models. Specifically, I have a large number of tables with millions of rows, and my dbt models are taking a long time to run and generate. I’ve tried various optimization techniques, but I’m still not seeing the performance improvements I need. I’ve tried various optimization techniques, such as:
Breaking down large tables into smaller chunks
Using subqueries instead of joins
Optimizing my SQL queries using indexes and statistics
Using dbt's built-in optimization features, such as materialized and partitioned
However, I’m still struggling to achieve the performance I need. Can anyone provide some best practices or advanced tips for optimizing dbt models for large-scale data warehousing?
Thanks!
Emmanuel Katto