Version 1.1.5

Fixes

• Fix cancellation (#173)
• http_headers should be dict in the profile (#174)

Version 1.2.2

Fixes

• Data is duplicated on reloading seeds that are using an external table (#114, #149)

Under the hood

• Explicitly close cursors (#163)
• Upgrade databricks-sql-connector to 2.0.5 (#166)
• Embed dbt-databricks and databricks-sql-connector versions to SQL comments (#167)

Version 1.1.4

Fixes

• Data is duplicated on reloading seeds that are using an external table (#114, #149)

Under the hood

• Explicitly close cursors (#163)
• Upgrade databricks-sql-connector to 2.0.5 (#166)
• Embed dbt-databricks and databricks-sql-connector versions to SQL comments (#167)

Version 1.2.1

Features

• Support Python 3.10 (#158)

Version 1.1.3

Features

• Support Python 3.10 (#158)
• 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

Version 1.1.2

Under the hood

• 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.

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.

Version 1.1.1

Features

• Support for Databricks CATALOG as a DATABASE in DBT compilations (#95, #89, #94, #105)
  • Setting an initial catalog with session_properties is deprecated and will not work in the future release. Please use catalog or database to set the initial catalog.
  • When using catalog, spark_build_snapshot_staging_table macro will not be used. If trying to override the macro, databricks_build_snapshot_staging_table should be overridden instead.

Fixes

• Block taking jinja2.runtime.Undefined into DatabricksAdapter (#98)
• Avoid using Cursor.schema API when database is None (#100)

Under the hood

• Drop databricks-sql-connector 1.0 (#108)

Version 1.1.0

Features

• Add support for Delta constraints (#71)
  Delta constraints are only available in Databricks Runtime 7.4 and above. So DBR 7.3 LTS won't support this feature.

Under the hood

• Port testing framework changes from dbt-labs/dbt-spark#299 and dbt-labs/dbt-spark#314 (#70)

Version 1.0.3

Fixes

• Make internal macros use macro dispatch pattern (#72)
  • The old macro names are still available during 1.0.x releases, but will not be available in 1.1.0 release.