docs/integrations/sources/linkedin-ads-migrations.md
With LinkedIn Ads v5.0.0, we modified primary keys for stream(s): ad_campaign_analytics, Custom Ad Analytics Reports, account_users.
This enhances data integrity and improves the efficiency of your syncs. Users with deduping enabled on those streams might have missing data as records would have been collapsed on the wrong primary key. We highly recommend initiating a connection refresh to ensure all the data is available in the destination.
ad_campaign_analyticsCustom Ad Analytics Reports| Old PK | New PK |
|---|---|
[string_of_pivot_values, end_date] | [string_of_pivot_values, end_date, sponsoredCampaign] |
account_users| Old PK | New PK |
|---|---|
[account] | [account, user] |
Clearing your data is required for the affected streams in order to continue syncing successfully. To clear your data for the affected streams, follow the steps below:
This will clear the data in your destination for the subset of streams with schema changes. After the clear succeeds, trigger a sync by clicking Sync Now. For more information on clearing your data in Airbyte, see this page.
Version 3.X.X introduced a regression in the connector that was reverted in 4.0.0. If you were using 3.X.X, please go through the migration steps. If you were still using 2.X.X, please upgrade to 4.0.0; after that, there are no additional actions required.
Clearing your data is required for the affected streams in order to continue syncing successfully. To clear your data for the affected streams, follow the steps below:
This will clear the data in your destination for the subset of streams with schema changes. After the clear succeeds, trigger a sync by clicking Sync Now. For more information on clearing your data in Airbyte, see this page.
We're continuously striving to enhance the quality and reliability of our connectors at Airbyte. As part of our commitment to delivering exceptional service, we are transitioning source-linkedin-ads from the Python Connector Development Kit (CDK) to our innovative low-code framework. This is part of a strategic move to streamline many processes across connectors, bolstering maintainability and freeing us to focus more of our efforts on improving the performance and features of our evolving platform and growing catalog. However, due to differences between the Python and low-code CDKs, this migration constitutes a breaking change.
Clearing your data is required for the affected streams in order to continue syncing successfully. To clear your data for the affected streams, follow the steps below:
This will clear the data in your destination for the subset of streams with schema changes. After the clear succeeds, trigger a sync by clicking Sync Now. For more information on clearing your data in Airbyte, see this page.
Version 2.0.0 introduces changes in the primary key selected for all *-analytics streams (including custom ones) from pivotValues[array of strings] to string_of_pivot_values[string] so that it is compatible with more destination types.
Clearing your data is required for the affected streams in order to continue syncing successfully. To clear your data for the affected streams, follow the steps below:
This will clear the data in your destination for the subset of streams with schema changes. After the clear succeeds, trigger a sync by clicking Sync Now. For more information on clearing your data in Airbyte, see this page.
Version 1.0.0 introduces changes in the primary key selected for all *-analytics streams (including custom ones).
Clearing your data is required for the affected streams in order to continue syncing successfully. To clear your data for the affected streams, follow the steps below:
This will clear the data in your destination for the subset of streams with schema changes. After the clear succeeds, trigger a sync by clicking Sync Now. For more information on clearing your data in Airbyte, see this page.