What should you consider when increasing the number of threads in a dbt project?

When increasing the number of threads in a dbt project, it is essential to consider the impact on other tools in your data stack. This is because dbt runs in conjunction with your data warehouse and potentially other services that may be running in your environment. If you increase the number of threads, it can lead to resource contention, where multiple processes are trying to access the same resources simultaneously. This can cause performance degradation not only in dbt but also in other connected tools and processes that rely on the same infrastructure.

For example, if your data warehouse is nearing its concurrency limits or if other applications are running that also require database connections, increasing the number of threads in dbt might lead to query failures, increased latency, or slower performance across the board. Therefore, understanding the overall capacity and current load on your data stack is crucial to making informed decisions about adjusting the threading configuration in dbt.