Skip to content

Releases: fivetran/dbt_github_source

BIO user field bug fix

16 Feb 17:42
3405ad4
Compare
Choose a tag to compare

This release contains the following non-breaking change:

  • removal of the BIO field description within the staging and source .yml files.

dbt 0.19.0 Compatibility and Teams Addition

03 Feb 21:04
c3f4ce6
Compare
Choose a tag to compare

This release updates the Github source package to include the following non-breaking changes:

  • Compatibility with dbt v0.19.0
  • Removal of unnecessary pass through columns.
  • Addition of team and repo_team tables to allow repository team visibility in downstream models.

Package Updates

01 Dec 23:08
aaa8c49
Compare
Choose a tag to compare

🚨This update introduces a breaking change: Output models are renamed to include a double underscore between the source name and the table name. For example, stg_github_issue.sql is now stg_github__issue.sql

The release also:

  • Introduces CircleCI testing
  • Introduces the use of pass-through columns, so that you can include your custom or standard Github columns in the output tables
  • Utilizes our fill_staging_columns macro for the creation of staging tables. If you do not have a required column necessary for this package, the fill_staging_column will produce this column (filled with nulls) and prevent the error

dbt 0.18.0 Compatibility

11 Sep 21:21
Compare
Choose a tag to compare

Updates package to be compatible with dbt 0.18.0. This is a breaking change!
🚨 dbt v0.18.0 or greater is required for this release. If you are not ready to upgrade, consider using a previous release of this package

Initial Release

26 May 17:23
146e5d1
Compare
Choose a tag to compare

This is the initial release of this package.

This package is designed enrich your Fivetran data by doing the following:

  • Add descriptions to tables and columns that are synced using Fivetran
  • Add freshness tests to source data
  • Add column-level testing where applicable. For example, all primary keys are tested for uniqueness and non-null values.
  • Model staging tables, which will be used in our transform package

Currently the package supports Redshift, BigQuery and Snowflake.