Features
- Add grants to materializations (dbt-labs/dbt-spark#366, dbt-labs/dbt-spark#381)
- Add
connection_parameters
for databricks-sql-connector connection parameters (#135)- This can be used to customize the connection by setting additional parameters.
- The full parameters are listed at Databricks SQL Connector for Python.
- Currently, the following parameters are reserved for
dbt-databricks
. Please use the normal credential settings instead.- server_hostname
- http_path
- access_token
- session_configuration
- catalog
- schema
Fixes
- Incremental materialization updated to not drop table first if full refresh for delta lake format, as it already runs create or replace table (dbt-labs/dbt-spark#286, dbt-labs/dbt-spark#287)
Under the hood
- Update
SparkColumn.numeric_type
to returndecimal
instead ofnumeric
, since SparkSQL exclusively supports the former (dbt-labs/dbt-spark#380) - Make minimal changes to support dbt Core incremental materialization refactor (dbt-labs/dbt-spark#402, dbt-labs/dbt-spark#394, #136)
- Add new basic tests
TestDocsGenerateDatabricks
andTestDocsGenReferencesDatabricks
(#134) - Set upper bound for
databricks-sql-connector
when Python 3.10 (#154)- Note that
databricks-sql-connector
does not officially support Python 3.10 yet.
- Note that