v0.7.1 dbt_klaviyo_source

PR #22 introduces the following updates:

🪲 Bug Fixes 🪛

• There were errors customers were encountering where numeric values were not being recognized in property_value, leading to database errors.
• To solve for that, we created the remove_string_from_numeric macro to be used in stg_klaviyo__event, which conducts the following operations:
  • We cast property_value as a string.
  • We then used a regex_replace function to retain only numerical values in these strings across all destinations (i.e. 0-9 values and .).
  • Finally we cast back to a numeric to ensure numeric_value is that particular data type.

🚘 Under the Hood 🚘

• Cast property_value in the integration_tests/dbt_project.yml to ensure the field was originally being cast as a string or varchar data type for testing purposes.
• Updated the event seed file to test for values that aren't numerics.
• Updated the pull request template.
• Included auto-releaser GitHub Actions workflow to automate future releases.

Contributors

• @vnguyen12 #21

Full Changelog: v0.7.0...v0.7.1

v0.7.0 dbt_klaviyo_source

PR #18 includes updates regarding the September 2023 changes to the Klaviyo connector.

🚨 Breaking Changes 🚨:

• As the integration table has been deprecated, we removed the stg_klaviyo__integration model, and instead have passed the integration columns through stg_klaviyo__metric.

• We have removed these deprecated columns from the following tables:

Table	Column
CAMPAIGN	is_segmented
FLOW	customer_filter
FLOW	trigger

• We have added these columns from the following tables and renamed them:

Table	Column	New Name
CAMPAIGN	archived	is_archived
CAMPAIGN	scheduled	scheduled_at
FLOW	archived	is_archived
FLOW	trigger_type	trigger_type
PERSON	last_event_date	last_event_date
METRIC	integration_name	integration_name
METRIC	integration_category	integration_category

For more information on the fields, refer to our docs.

Under the Hood:

• We removed the Snowflake-specific logic in place for passing through the trigger field in the Flow table as it was a reserved word. Now that the trigger field has been deprecated, we have also removed the associated logic in the package.
• We removed the not_null test for email in the stg_klaviyo__person model. This is because for the most recent schema, the only primary key is person_id rather than email, and email may not be present.

Full Changelog: v0.6.0...v0.7.0

v0.6.0 dbt_klaviyo_source

🚨 Breaking Changes 🚨:

• This change is made breaking due to impact on incremental models in the downstream transformation package.

Bug Fixes

PR #17 includes the following breaking changes:

• IDs used in downstream joins or coalesce functions are now cast using {{ dbt.type_string() }} to prevent potential datatype conflicts.
• _fivetran_synced is now cast using {{ dbt.type_timestamp() }} to prevent downstream datatype errors.

Under the Hood:

PR #16 includes the following updates:

• Incorporated the new fivetran_utils.drop_schemas_automation macro into the end of each Buildkite integration test job.
• Updated the pull request templates.

Full Changelog: v0.5.0...v0.6.0

dbt_klaviyo_source v0.5.0

🚨 Breaking Changes 🚨:

PR #15 includes the following breaking changes:

• Dispatch update for dbt-utils to dbt-core cross-db macros migration. Specifically {{ dbt_utils.<macro> }} have been updated to {{ dbt.<macro> }} for the below macros:
  • any_value
  • bool_or
  • cast_bool_to_text
  • concat
  • date_trunc
  • dateadd
  • datediff
  • escape_single_quotes
  • except
  • hash
  • intersect
  • last_day
  • length
  • listagg
  • position
  • replace
  • right
  • safe_cast
  • split_part
  • string_literal
  • type_bigint
  • type_float
  • type_int
  • type_numeric
  • type_string
  • type_timestamp
  • array_append
  • array_concat
  • array_construct
• For current_timestamp and current_timestamp_in_utc macros, the dispatch AND the macro names have been updated to the below, respectively:
  • dbt.current_timestamp_backcompat
  • dbt.current_timestamp_in_utc_backcompat
• dbt_utils.surrogate_key has also been updated to dbt_utils.generate_surrogate_key. Since the method for creating surrogate keys differ, we suggest all users do a full-refresh for the most accurate data. For more information, please refer to dbt-utils release notes for this update.
• Dependencies on fivetran/fivetran_utils have been upgraded, previously [">=0.3.0", "<0.4.0"] now [">=0.4.0", "<0.5.0"].

dbt_klaviyo_source 0.4.1

Updates

• Updates dbt-labs/spark_utils package in packages.yml from [">=0.2.0", "<0.3.0"] to [">=0.3.0", "<0.4.0"].

dbt_klaviyo_source 0.4.0

Happy Monday!

🎉 dbt v1.0.0 Compatibility 🎉

🚨 Breaking Changes 🚨

• Adjusts the require-dbt-version to now be within the range [">=1.0.0", "<2.0.0"]. Additionally, the package has been updated for dbt v1.0.0 compatibility. If you are using a dbt version <1.0.0, you will need to upgrade in order to leverage the latest version of the package.
  • For help upgrading your package, I recommend reviewing this GitHub repo's Release Notes on what changes have been implemented since your last upgrade.
  • For help upgrading your dbt project to dbt v1.0.0, I recommend reviewing dbt-labs upgrading to 1.0.0 docs for more details on what changes must be made.
• Upgrades the package dependency to refer to the latest dbt_fivetran_utils. The latest dbt_fivetran_utils package also has a dependency on dbt_utils [">=0.8.0", "<0.9.0"].
  • Please note, if you are installing a version of dbt_utils in your packages.yml that is not in the range above then you will encounter a package dependency error.
• The union_schemas and union_databases variables have been replaced with klaviyo_union_schemas and klaviyo_union_databases respectively. This allows for multiple packages with the union ability to be used and not locked to a single variable that is used across packages.

Under the Hood

• Unioning: The unioning occurs in the tmp models using the fivetran_utils.union_data macro. (#8)
• Unique tests: Because columns that were previously used for unique tests may now have duplicate fields across multiple sources, these columns are combined with the new source_relation column for unique tests and tested using the dbt_utils.unique_combination_of_columns macro. (#8)
• Source Relation column: To distinguish which source each field comes from, we added a new source_relation column in each staging model and applied the fivetran_utils.source_relation macro. (#8)

Contributors

• @pawelngei #8

dbt_klaviyo_source 0.3.0

Happy Tuesday! This 0.3.0 release of the dbt_klaviyo_source package contains the below changes. Refer to the CHANGELOG for additional information on the below changes.

Features

• Allow for multiple sources by unioning source tables across multiple Klaviyo connectors.
  (#8 & #9)
  • Refer to the README for more details.

Under the Hood

• Unioning: The unioning occurs in the tmp models using the fivetran_utils.union_data macro. (#8)
• Unique tests: Because columns that were previously used for unique tests may now have duplicate fields across multiple sources, these columns are combined with the new source_relation column for unique tests and tested using the dbt_utils.unique_combination_of_columns macro. (#8)
• Source Relation column: To distinguish which source each field comes from, we added a new source_relation column in each staging model and applied the fivetran_utils.source_relation macro. (#8)

Contributors

• @pawelngei #8

dbt 0.20.0 Compatibility

🎉 dbt 0.20.0 Compatibility 🎉

🚨 This is a breaking change! 🚨 dbt v0.20.0 or greater is required for this release. If you are not ready to upgrade, consider using a previous release of this package.

Additional considerations when upgrading to this package:

• This package utilizes the latest v0.7.x release of the dbt-labls/dbt_utils package. If your project also utilizes a version of the fishtown-analytics/dbt_utils package then you will receive a duplicate package error. If this is the case you will need to consider upgrading your other packages to be compatible with this update or use a previous release of this package.
• Similar to the above point, all previous Fivetran dbt packages utilize the fishtown-analytics/dbt_utils package and you will need to upgrade all Fivetran dbt packages to the latest dbt 0.20.0 compatibility releases in order for your packages to run without package conflicts.
• For Databricks users this compatibility is currently only available for >=dbt 0.20.1rc1. If you want more information on upgrading your dbt-spark version, you can refer to the dbt-spark release for further details.

Fivetran Utils Dependency Update

🚧 Fivetran Utils Dependency Update 🚧

This release includes the following non-breaking changes:

• Update to the packages.yml to reference the recently released Fivetran Utils package. This is a necessary update to ensure this package is compatible with previous dbt releases before dbt v0.20.0 updates take place.

Databricks Compatibility

Happy Tuesday! This tiny release introduces compatibility with Databricks 🧱