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Possibilities and Limitations of Delta Live Tables (DLT) with Direct Publish mode

susanne
New Contributor II

Hi all,

I am implementing a DLT table with the new Direct Publish feature which is still in Private Preview.

Is it a limitation of DLT with Direct Publish that you can not query the event_log of the DLT?
When I use this query:

SELECT *
FROM event_log('pipeline_id');

Then I always get this error message regardless of what type of compute I am using:
[INTERNAL_ERROR] The Spark SQL phase analysis failed with an internal error. You hit a bug in Spark or the Spark plugins you use. Please, report this bug to the corresponding communities or vendors, and provide the full stack trace. SQLSTATE: XX000

2 REPLIES 2

Walter_C
Databricks Employee
Databricks Employee

The error you are encountering when querying the event log in Delta Live Tables (DLT) with Direct Publish mode is a known limitation. Specifically, the event log Table-Valued Function (TVF) does not work in Direct Publishing Mode. This is documented in the private preview guide for DLT Direct Publishing Mode.

As a workaround, you can directly query the delta table that stores the pipeline’s event log. The event log for a Direct Publishing pipeline is stored in a specific format:

  1. Default Catalog: The catalog specified in the pipeline settings.
  2. Default Schema: The schema specified in the pipeline settings.
  3. Underscored Pipeline ID: The pipeline’s UUID with dashes replaced by underscores.

For example, if your pipeline ID is 5e9e3c89-2a4b-4dcd-baaf-48f58c2c54ae, and the default catalog and schema are catalog and test respectively, the event log table would be named catalog.test.__5e9e3c89_2a4b_4dcd_baaf_48f58c2c54ae_event_log.

susanne
New Contributor II

@Walter_Cthank you so much, that worked perfectly 🙂

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