Upgrading to v1.12
dbt Core v1.12 is not yet available in beta. We will update this guide when it becomes available.
Resources
- dbt Core v1.12 changelog (coming soon)
- dbt Core CLI Installation guide
- Cloud upgrade guide
What to know before upgrading
dbt Labs is committed to providing backward compatibility for all versions 1.x. Any behavior changes will be accompanied by a behavior change flag to provide a migration window for existing projects. If you encounter an error upon upgrading, please let us know by opening an issue.
dbt provides the functionality from new versions of dbt Core via release tracks with automatic upgrades. If you have selected the Latest release track in dbt, you already have access to all the features, fixes, and other functionality included in the latest dbt Core version! If you have selected the Compatible release track, you will have access to the next monthly Compatible release after the dbt Core v1.12 final release.
We continue to recommend explicitly installing both dbt-core and dbt-<youradapter>. This may become required for a future version of dbt. For example:
python3 -m pip install dbt-core dbt-snowflake
New and changed features and functionality
Coming soon
Managing changes to legacy behaviors
dbt Core v1.12 introduces new flags for managing changes to legacy behaviors. You may opt into recently introduced changes (disabled by default), or opt out of mature changes (enabled by default), by setting True / False values, respectively, for flags in dbt_project.yml.
You can read more about each of these behavior changes in the following links:
- (Introduced, disabled by default)
require_valid_schema_from_generate_schema_name. This flag is set toFalseby default. With this setting, dbt raises theGenerateSchemaNameNullValueDeprecationwarning when a customgenerate_schema_namemacro returns anullvalue. When set toTrue, dbt enforces stricter validation and raises a parsing error instead of a warning.
Adapter-specific features and functionalities
Coming soon
Quick hits
Coming soon
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