Version 1.2.0

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 return decimal instead of numeric, 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 and TestDocsGenReferencesDatabricks (#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.