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Logging Method (Project)

Applies to
Platform: Databricks · Fabric Lakehouse

Logging Method (LoggingMethod) selects where the generated notebooks write their log messages during deployment and load. Choose Delta Table to keep the messages in a table you can query, or Python Logger to see them only in the notebook output.

Fabric Warehouse and the dbt generators do not offer the property.

Values

A single choice in Project Settings:

  • Delta Table (default): every message is written to a Delta table in the load-control schema. The table name comes from the placeholder loadcontrol#loadcontrol#execution_log_table_name, default execution_log.
  • Python Logger: the messages go to the Python logger and appear only in the output of the running notebook.

Effect on generated output

The load-control deployment notebook creates the log table in the schema given by loadcontrol#loadcontrol#database_name and loadcontrol#loadcontrol#schema_name. Its columns include log_timestamp, log_level, project_name, load_timestamp, task_name, target_object_name and message. The same notebook also creates the table named by deployment_log_table_name, default deployment_log.

Example

With the default value, list the newest messages first. <load-control database> and <load-control schema> are the values of the two placeholders above:

SELECT log_timestamp, log_level, task_name, message
FROM <load-control database>.<load-control schema>.execution_log
ORDER BY log_timestamp DESC;

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