Releases: databricks/dbt-databricks
v1.7.17
v1.8.4
What's Changed
- Fix dbt seed command error when seed file is partially defined in the config file by @kass-artur in #724
- Readd external type by @benc-db in #728
- Adding more tblproperties to ignore list for streaming tables by @benc-db in #736
New Contributors
- @kass-artur made their first contribution in #724
Full Changelog: v1.8.3...v1.8.4
v1.8.3
v1.8.2
What's Changed
- Reverting the decision to remove 'spark.sql.sources.partitionOverwriteMode = DYNAMIC' for insert_overwrite by @benc-db in #688
- Liquid clustering is now responsive to config changes with incremental models by @benc-db in #686
- Cancel running python jobs on Ctrl-C by @benc-db (thanks @gaoshihang for kicking this off!) in #693
- Change over to
system
catalog for metadata gathering to fix bug with renamed catalogs by @benc-db in #692 - Fix insert_overwrite replacement when changing from a different partition strategy by @benc-db in #697
- Feature/issue640 refresh spa token no longer writes error log by (thanks @thijs-nijhuis!) in #700
- Migrate remaining unit tests to pytest by @benc-db in #701
- Change default redirect_url and scopes of client dbt-databricks by @jackyhu-db in #704
- Fix serialization issue detected by dbt Labs by @benc-db in #708
New Contributors
- @jackyhu-db made their first contribution in #704
Full Changelog: v1.8.1...v1.8.2
v1.8.1
What's New?
Features
- Support Liquid Clustering for python models (663)
Fixes
- Rerunning seed with external location + persist_doc now more resilient (662)
- Fix issue with running while a refresh is in progress with MV/ST (674)
- Fix issue with running a refresh with MV/ST that need names to be escaped (674)
Under the Hood
- Delay loading of agate library to improve startup (thanks @dwreeves for getting this started!) (661)
- Updating to dbt-adapters~=1.2.0 (683)
Full Changelog: v1.8.0...v1.8.1
v1.8.0
This release carries a substantial structural change as it is the first release after moving to the new 'decoupled' dbt architecture; while today we retain a dependence on dbt-core so that users do not need to install/specify versions for both libraries, we have moved to depending on a shared abstraction layer between the adapter and dbt-core. As a result, we no longer need to match our feature version to that of dbt-core, and are free to adopt semantic versioning. No more releasing significant features like 'compute-per-model` as a patch version!
This release also brings improvements to the declaration and operation of Materialized Views and Streaming Tables, including the ability to schedule automatic refreshes.
A new feature introduced in this release is support for tags. To distinguish from dbt tags, which are metadata that is often used for selecting models in a dbt operation, these tags are named as databricks_tags
in the model configuration.
Big thanks to dbt Labs for significant help during the development and testing of this release.
What's Changed
Features
- Support
on_config_change
for materialized views, expand the supported config options (536) - Support
on_config_change
for streaming tables, expand the supported config options (569) - Support insert overwrite on SQL Warehouses (623)
- Support Databricks tags at model level for tables/views/incrementals (631)
Under the Hood
v1.7.16
It was brought to my attention that 1.7.15 didn't fix what it was intended to; this version should actually fix the issue where instead of getting a meaningful exception message when a connection could be created, you would get the message 'conn is referenced before being initialized'.
What's Changed
Full Changelog: v1.7.15...v1.7.16
v1.7.15
v1.8.0rc1
In concert with dbt Labs, we've decided the next release will be 1.8.0 after all. This release pulls everything that was in the 2.0.latest branch into 1.8.latest.
What's Changed
- Support for tags by @benc-db in #627
- Metadata gathering improvements by @benc-db in #655 and in #658
Everything from the 1.7.latest branch that had not yet made it to 1.8.latest
Full Changelog: v1.8.0b2...v1.8.0rc1
v1.7.14
Note: user configurable OAuth scopes currently only work for AWS, as the Databricks SDK does not let us override them for Azure. I'm working with the owning team to get that addressed.
What's Changed
- FIX #582: User Configurable OAuth Scopes in profiles.yml by @stevenayers in #641
- Fixing idle issue and improving debug logging by @benc-db in #648
New Contributors
- @stevenayers made their first contribution in #641
Full Changelog: v1.7.13...v1.7.14