If you're using the dbt CLI, you'll need to set up a
You can learn more about this in the article on Connecting to your warehouse.
This article lists the parts of your
profile.yml which are not database specific. Check out the article for your database for exact connection details.
partial_parse: <true | false>use_colors: <true | false>printer_width: <integer>send_anonymous_usage_stats: <true | false><profile-name>:target: <target-name>outputs:<target-name>:type: <bigquery | postgres | redshift | snowflake | other>schema: <schema_identifier>threads: <natural_number>### database-specific connection details...<target-name>: # additional targets...<profile-name>: # additional profiles...
Partial parsing can improve the performance characteristics of dbt runs by limiting the number of files that are parsed by dbt. Here, "parsing" means reading files in a dbt project from disk and capturing
config() method calls. dbt uses these method calls to determine 1) the shape of the dbt DAG and 2) the supplied configurations for dbt resources.
If partial parsing is enabled and files are unchanged between invocations of dbt, then dbt does not need to re-parse these files — it can instead use the parsed representation from the last invocation of dbt. If a file has changed between invocations of dbt, then dbt will re-parse the file and update the parsed node cache accordingly.
Use caution when enabling partial parsing in dbt. If environment variables or variables specified on the CLI with
--vars control the parsed representation of your project, then the logic executed by dbt may differ from the logic specified in your project. Partial parsing should only be used when all of the logic in your dbt project is encoded in the files inside of that project.
partial_parse is set to
To enable partial parsing for all dbt projects, specify
partial_parse: true in your
You can also achieve this by using the
--partial-parse command line flag.
The value in your
profiles.yml can be overridden with the
By default, dbt will colorize the output it prints in your terminal. You can turn this off by adding the following to your
By default, dbt will print out lines padded to 80 characters wide. You can change this setting by adding the following to your
We want to build the best version of dbt possible, and a crucial part of that is understanding how users work with dbt. To this end, we've added some simple event tracking to dbt (using Snowplow). We do not track credentials, model contents or model names (we consider these private, and frankly none of our business).
Usage statistics are fired when dbt is invoked and when models are run. These events contain basic platform information (OS + python version). The schemas for these events can be seen here
By default this is turned on – you can opt out of event tracking at any time by adding the following to your