Skip to content

Report fallback reason for unsupported Iceberg scan data types #2427

Description

@weimingdiit

Is your feature request related to a problem? Please describe.

When Auron Iceberg native scan falls back because the read schema contains unsupported data types, the fallback does not provide a specific never-convert reason.

For example, an Iceberg table with an unsupported decimal field falls back to Spark execution, but the plan does not clearly explain which field/type caused native scan conversion to be skipped.

Describe the solution you'd like

Add an Iceberg fallback reason for unsupported scan schema data types.

The reason should include the unsupported field names and their Spark SQL types, so users and developers can quickly identify why the Iceberg native scan was not selected.

Describe alternatives you've considered

One alternative is to keep silent fallback behavior and rely on plan inspection or debug logs.

That makes diagnosis harder, especially when the scan schema has many columns or nested types.

Additional context

This change should only improve fallback diagnostics. It should not change native Iceberg scan eligibility or execution behavior.

Metadata

Metadata

Assignees

No one assigned

    Labels

    No labels
    No labels

    Type

    No type

    Projects

    No projects

    Milestone

    No milestone

    Relationships

    None yet

    Development

    No branches or pull requests

    Issue actions