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dbt-spark Changelog

  • This file provides a full account of all changes to dbt-spark.
  • Changes are listed under the (pre)release in which they first appear. Subsequent releases include changes from previous releases.
  • "Breaking changes" listed under a version may require action from end users or external maintainers when upgrading to that version.
  • Do not edit this file directly. This file is auto-generated using changie. For details on how to document a change, see the contributing guide

dbt-spark 1.2.1 - December 20, 2022

Features

  • backport changie to 1.2.latest (#417, #418)

Fixes

  • Support new error messages in the future Spark. (#515, #520)

Under the Hood

  • updating python version in tox (#536, #534)
  • fix post new release tox issues around passenv and allowlist_externals (#545, #545)

Contributors

dbt-spark 1.2.0 - July 26, 2022

Features

  • Add grants to materializations (#366, #381)

Fixes

  • Pin pyodbc to version 4.0.32 to prevent overwriting libodbc.so and libltdl.so on Linux (#397, #398)
  • Incremental materialization updated to not drop table first if full refresh for delta lake format, as it already runs create or replace table (#286, #287)
  • Apache Spark version upgraded to 3.1.1 (#348, #349)
  • adapter.get_columns_in_relation (method) and get_columns_in_relation (macro) now return identical responses. The previous behavior of get_columns_in_relation (macro) is now represented by a new macro, get_columns_in_relation_raw (#354, #355)

Under the hood

  • Update SparkColumn.numeric_type to return decimal instead of numeric, since SparkSQL exclusively supports the former (#380)
  • Initialize lift + shift for cross-db macros (#359)
  • Add invocation env to user agent string (#367)
  • Use dispatch pattern for get_columns_in_relation_raw macro (#365)

Contributors

Previous Releases

For information on prior major and minor releases, see their changelogs: