dbt-bigquery 1.3.0 - October 12, 2022
Features
- Implement
create_schemavia SQL, instead of Python method, allowing users to override if desired. drop_schema remains a Python method for the time being. (#182, #183) - Added table and incrementail materializations for python models via DataProc. (#209, #226)
- Add support for Dataproc Serverless (#248, #303)
- Array macros (#307, #308)
- add type_boolean as a data type macro (#315, #313)
- Migrate dbt-utils current_timestamp macros into core + adapters (#324, #323)
Under the Hood
- Implement minimal changes to support dbt Core incremental materialization refactor. (#232, #223)
- Add changie to dbt-bigquery (#254, #253)
- Add location/job_id/project_id to adapter response to enable easy job linking (#92, #250)
- Adding
slot_msgoBigQueryAdapterResponse(#194, #195) - specify supported_languages for materialization that support python models (#288, #290)
- Convert df to pyspark DataFrame if it is pandas before writing (#301, #301)
- Update BQ job and call retry settings (#311, #310)
- Enable pandas-on-Spark DataFrames for dbt python models (#316, #317)
- Convert df to pyspark DataFrame if it is koalas before writing (#320, #321)
Dependency
Contributors
- @Kayrnt (#250)
- @chamini2 (#301)
- @colin-rogers-dbt (#323, #310)
- @dbeatty10 (#308, #317, #321)
- @graciegoheen (#308)
- @jpmmcneill (#313)
- @ueshin (#321)
- @yu-iskw (#195)