If you use dbt-osmosis to maintain column descriptions for a long period of time, you often experience the following.
I want to modify the description of this column to a better description. However, the description of this column seems to have been propagated by dbt-osmosis. Which model column description should I modify?
It would be helpful if this information could be kept statically in yaml instead of at runtime. For this reason, the --add-progenitor-to-meta option has been added in this pull request (Default value is False so as not to change the existing behavior).
Example
For example, suppose you have the following data source
version: 2
sources:
- name: my_dataset
database: my-project
tables:
- name: order
columns:
- name: my_description
description: "This is description"
dbt-osmosis yaml refactor --add-progenitor-to-meta ... will output the following yaml. You can include information about which model the column description is derived from in meta.osmosis_progenitor. This information is very useful because it tells you which model to modify when modifying column descriptions.
This example is very simple, but when models are linked in multiple layering using dbt, it is difficult to quickly determine which model description is the progenitor. The meta.osmosis_progenitor is very useful because it tells you which model to modify when modifying a column description.
Background
If you use dbt-osmosis to maintain column descriptions for a long period of time, you often experience the following.
It would be helpful if this information could be kept statically in yaml instead of at runtime. For this reason, the
--add-progenitor-to-meta
option has been added in this pull request (Default value isFalse
so as not to change the existing behavior).Example
For example, suppose you have the following data source
dbt-osmosis yaml refactor --add-progenitor-to-meta ...
will output the following yaml. You can include information about which model the column description is derived from inmeta.osmosis_progenitor
. This information is very useful because it tells you which model to modify when modifying column descriptions.This example is very simple, but when models are linked in multiple layering using dbt, it is difficult to quickly determine which model description is the progenitor. The
meta.osmosis_progenitor
is very useful because it tells you which model to modify when modifying a column description.