Hi @yit337 ,

As @IM_01 and @pradeep_singh  mentioned you can use configuration under settings in LDP and provide key and value pairs. Then you can refer to those parameters using spark.conf.get(your_parameter_name) in pyspark or using ${} notation in  SQL (as in example screenshot below):

But those parameters are static. If you really want to provide a dynamic values there's an ugly workaround. You can use databricks cli to override parameters as suggested in following reply:

Below you have a link to entire discussion:

Triggering DLT Pipelines with Dynamic Parameters - Databricks Community - 111581