Asana connector limitations

Important

This feature is in Beta. To use it, a workspace admin must turn on Lakeflow Connect for Asana from the Previews page. See Manage Azure Databricks previews.

The managed Asana connector in Lakeflow Connect ingests only tasks that are in a project, includes only portfolios that the authorizing user owns, and doesn't ingest project data from workspaces that aren't organizations.

General software as a service (SaaS) connector limitations

The limitations in this section apply to all SaaS connectors in Lakeflow Connect.

• When you run a scheduled pipeline, alerts don't trigger immediately. Instead, they trigger when the next update runs.
• When a source table is deleted, the destination table is not automatically deleted. You must delete the destination table manually. This behavior is not consistent with Spark Declarative Pipelines on Lakeflow behavior.
• During source maintenance periods, Databricks might not be able to access your data.
• If a source table name conflicts with an existing destination table name, the pipeline update fails.
• Multi-destination pipeline support is API-only.
• You can optionally rename a table that you ingest. If you rename a table in your pipeline, it becomes an API-only pipeline, and you can no longer edit the pipeline in the UI.
• If you select a column after a pipeline has already started, the connector does not automatically backfill data for the new column. To ingest historical data, manually run a full refresh on the table.
• Databricks can't ingest two or more tables with the same name in the same pipeline, even if they come from different source schemas.
• The source system assumes that the cursor columns are monotonically increasing.
• The connector ingests raw data without transformations. Use downstream Spark Declarative Pipelines on Lakeflow pipelines for transformations.

Connector-specific limitations

The limitations in this section apply to the Asana connector.

• To ingest projects and tasks, use an Asana organization. Teams exist only in organizations, and the connector reads projects through teams, so a workspace that isn't an organization has no records in the team_memberships, projects, sections, tasks, stories, task_attachments, time_tracking_entries, project_memberships, custom_field_settings, project_status_updates, and project_attachments tables. Workspace-level tables such as users, tags, custom_fields, and goals are still ingested. See the Asana teams reference.
• To ingest a task, add it to a project. The connector reads tasks from project sections, so tasks that aren't in a project, and their stories, attachments, and time tracking entries, aren't ingested.
• To count each record one time, deduplicate on gid. The tasks, stories, task_attachments, and time_tracking_entries tables include the section in their primary key, so records for a task in more than one project appear one time for each section that contains the task.
• To ingest a portfolio, authorize the connection as the user who owns it. Asana lists only the authorizing user's own portfolios, so the portfolios, portfolio_memberships, portfolio_items, and portfolio_status_updates tables omit portfolios that other users own. See the Asana portfolios reference.
• To ingest every object, confirm that the authorizing user can access it and that your Asana plan includes its feature. The connector skips objects that Asana denies access to, so the affected tables contain fewer records, or none, and the pipeline doesn't fail.