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Releases: oracle/dbt-oracle

v1.4.3

13 Oct 01:32
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1.4.3 is a patch version with the following bug fixes:

  • Relax version constraint for dbt-core to major and minor version #99. This enables to install a compatible patched version of dbt-core whenever it is released without upgrading dbt-oracle

  • Bugfix for #100

  • Bugfix for #86

  • Upgrade python driver to latest version 1.4.1

  • Set connection id prefix to track dbt connections in cman logs

Thanks to @rkope99 for contributing to this release version

v1.5.3

29 Sep 19:58
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1.5.3 is a patch version with the following bug fixes:

v1.6.0

15 Sep 22:34
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1.6.0 is a minor release version with the following features and fixes:

v1.5.2

19 Jul 22:41
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This minor release has the following updates

v1.5.1

12 Jul 19:23
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This release includes the following features and updates:

  • Implemented support for Python models using Oracle's Autonomous Database Serverless (ADB-S)
    • User Defined Python function is run in an ADB-S spawned Python 3.10 runtime
      Import 3rd party Python packages installed in the default Python runtime
    • Access to Database session in the Python function
    • DataFrame read API to read TABLES, VIEWS and ad-hoc SELECT queries as DataFrames
    • DataFrame write API to write DataFrames as TABLES
    • Supports both table and incremental materialization
  • dbt-core upgraded to 1.5.2
  • oracledb upgraded to 1.3.2

v1.5.0

10 May 23:06
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This is a minor release upgrade addressing #83 with the following updates

  1. Model Contracts

    • Implemented data_type_code_to_name to convert Python oracledb driver return types to strings
    • Implemented oracle__get_empty_subquery_sql and oracle__get_empty_schema_sql to generate SQL to assert column spec equivalence
    • Updated macro create_table_as; calls to two macros that assert column spec equivalence and template out DDL containing column names, types, and constraints
    • Updated macro create_view_as added a call to the macro asserting column spec equivalence
  2. Support the constraints data structure

    • Map constraint types to CONSTRAINT_SUPPORT
    • Override Adapter method render_column_constraint
  3. Dependencies upgraded; dbt-core==v1.5.0 and oracledb=1.3.1

  4. Test cases added to test constraints, simple seed, caching etc

v1.4.2

24 Mar 17:40
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This release includes the following fixes and features

  • Fixes #78 Flaky generic tests on multiple threads
  • Adds support for parallel execution for incremental materialization #80. Thanks to @Mirko-T for the macro changes
  • Upgrades dbt-core to v1.4.5

v1.4.1

06 Mar 17:19
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Fixes pytz dependency reported in #75 and dbt-labs/dbt-core#7077

v1.4.0

22 Feb 00:29
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This release includes the following features and fixes

  • Added support for faster Python 3.11
  • Added support for Incremental predicates which can be specified in incremental model configuration
       # this limits the scan of the existing table to the last 7 days of data
       incremental_predicates: ["DBT_INTERNAL_DEST.session_start > datediff(day, -7, current_date)"]
    
  • Upgrade dbt-core dependency requirement to 1.4.1
  • Replace deprecated exception functions defined in dbt-core v1.4.1
  • Added more test cases to the dbt-oracle test suite

v1.3.2

02 Feb 19:22
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This is a minor release upgrade with the following fixes and features

  • Upgraded dbt-core to 1.3.2

  • Upgraded oracledb driver to 1.2.2 which fixes some bugs

  • Added support for specifying CTAS degree of parallelism in dbt model config as requested in #65

  • Added support for specifying table compression clause in dbt model config as requested in #65

  • Bug fix for affected row count. Removed cursor.commit() which resets the affected rowcount. commit() is called by dbt-core after fetching the affected rowcount. Rowcount works for Thin driver mode. For Thick driver mode and old cx mode, rowcount is always 0 and a bug is logged with the driver team.

  • Bug fix for using alias in dbt model config. dbt alias can be used as a work around for "Identifier too long" issue in older Oracle DB versions (11 for example). This was discussed in dbt labs Slack channel