v0.5.2 dbt_tiktok_ads_source

PR #19 includes the following updates:

Bug Fixes

• This package now leverages the new tiktok_ads_extract_url_parameter() macro for use in parsing out url parameters. This was added to create special logic for Databricks instances not supported by dbt_utils.get_url_parameter().
  • This macro will be replaced with the fivetran_utils.extract_url_parameter() macro in the next breaking change of this package.

Under the Hood

• Included auto-releaser GitHub Actions workflow to automate future releases.

Full Changelog: v0.5.1...v0.5.2

v0.5.1 dbt_tiktok_ads_source

PR #14 includes the following updates:

Under the Hood:

• Updates the DECISIONLOG to clarify why there exist differences among aggregations across different grains.

Full Changelog: v0.5.0...v0.5.1

v0.5.0 dbt_tiktok_ads_source

PR #12 includes the following updates:

Breaking changes

• Updated the source identifier format for consistency with other packages and for compatibility with the fivetran_utils.union_data macro. Identifiers now are:

current	previous
tiktok_ads_adgroup_history_identifier	tiktok_ads__ad_group_history_identifier
tiktok_ads_ad_history_identifier	tiktok_ads__ad_history_identifier
tiktok_ads_advertiser_identifier	tiktok_ads__advertiser_identifier
tiktok_ads_campaign_history_identifier	tiktok_ads__campaign_history_identifier
tiktok_ads_ad_report_hourly_identifier	tiktok_ads__ad_report_hourly_identifier
tiktok_ads_adgroup_report_hourly_identifier	tiktok_ads__ad_group_report_hourly_identifier
tiktok_ads_campaign_report_hourly_identifier	tiktok_ads__campaign_report_hourly_identifier

• If you are using the previous identifier, be sure to update to the current version!

Feature update 🎉

• Unioning capability! This adds the ability to union source data from multiple tiktok_ads connectors. Refer to the Union Multiple Connectors README section for more details.

Under the hood 🚘

• Updated tmp models to union source data using the fivetran_utils.union_data macro.
• To distinguish which source each field comes from, added source_relation column in each staging model and applied the fivetran_utils.source_relation macro.
• Updated tests to account for the new source_relation column.

Full Changelog: v0.4.0...v0.5.0

v0.4.0 dbt_tiktok_ads_source

PR #10 applies the following updates:

🚨 Breaking Changes 🚨

• In the July 2023 connector update for TikTok Ads, we upgraded the connector to the v1.3 API. As a result the dependent fields and field names from the downstream staging models have changed.
  • In stg_tiktok_ads__ad_group_history, age has been renamed as age_groups.
  • In stg_tiktok_ads__advertiser, phone_number has been renamed as cellphone_number, and telephone has been renamed as telephone_number.
• Note: We coalesced the old API field names with these renamed fields to ensure backwards compatibility for these fields.

🔧 Under the Hood 🔩

• Incorporated the new fivetran_utils.drop_schemas_automation macro into the end of each Buildkite integration test job.
• Updated the pull request templates.
• Seed files were also renamed with the newest version of the fields, in case we decide to bring them in with future versions of the package.

Full Changelog: v0.3.0...v0.4.0

dbt_tiktok_ads v0.3.0

🚨 Breaking Changes 🚨:

PR #4 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
• packages.yml has been updated to reflect new default fivetran/fivetran_utils version, previously [">=0.3.0", "<0.4.0"] now [">=0.4.0", "<0.5.0"].

Bug Fixes

• Adjusted the get_ad_group_report_hourly_columns, get_ad_report_hourly_columns, and get_campaign_report_hourly_columns macros to ensure the passthrough variables are included in the returned columns and propogate within downstream models. (#5)

Contributors

• @andysmv (#5)

dbt_tiktok_ads_source 0.2.0

PR #3 applies the following updates:

🎉 Feature Enhancements 🎉

• Inclusion of passthrough metrics:
  • tiktok_ads__ad_group_hourly_passthrough_metrics
  • tiktok_ads__ad_hourly_passthrough_metrics
  • tiktok_ads__campaign_hourly_passthrough_metrics

This applies to all passthrough columns within the dbt_tiktok_ads_source package and not just the tiktok_ads__ad_group_hourly_passthrough_metrics example.

vars:
  tiktok_ads__ad_group_hourly_passthrough_metrics:
    - name: "my_field_to_include" # Required: Name of the field within the source.
      alias: "field_alias" # Optional: If you wish to alias the field within the staging model.

• Casts all timestamp fields using dbt_utils.type_timestamp() and rounds all monetary fields
• Adds not-null tests to key fields
• Introduces the identifier variable for all source models
• Add enable configs for this specific ad platform, for use in the Ad Reporting rollup package

dbt_tiktok_ads_source v0.1.1

🎉 Update configs 🎉

Hot off the v0.1.1 initial release, we updated the README and configs regarding:

• Removed whitespaces and updated naming in database and schema vars.

For more information refer to the README.

dbt_tiktok_ads_source v0.1.0

🎉 Initial Release of the Fivetran TikTok Ads dbt package 🎉

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 Postgres, Redshift, BigQuery, Databricks and Snowflake. Additionally, this package is designed to work with dbt versions [">=1.0.0", "<2.0.0"].

For more information refer to the README.