Apply Changes Error in DLT Pipeline

[VReddy1601]

Hi Team,

Am Trying to use Apply changes from Bronze to Silver using the below. 

               

  @dlt.table(

           name="Silver_Orders",

           comment="This table - hive_metastore.silver.Orders reads data from the Bronze layer and writes it to the Silver layer.",

           table_properties={"quality": "silver"},

           path="/mnt/silver/Future-Orders/xxx/Orders"

        )

        def olo_orders_silver():

            try:

                # Read the Bronze table

                bronze_df = spark.table("hive_metastore.bronze.xxx_Orders")

                # Apply changes from the Bronze table to the Silver table

                dlt.apply_changes(

                    target="Silver_Orders",

                    source=bronze_df,

                    keys=["OrderId", "Label"],

                    sequence_by=F.col("processing_time")  # Assuming you have a timestamp column to order changes

                )

Here

1) bronze_df = spark.table("hive_metastore.bronze.Orders") 

That means it is the data frame with name bronze_df created on the Hive table. This will be source streaming table from Bronze layer. 

2) Silver_Orders is the Target Table which have mount location. 

While am running this Validation is notebook , am getting the below error. Kindly help to suggest what is causing the issue?

pyspark.errors.exceptions.captured.AnalysisException: APPLY CHANGE target 'Silver_Orders' should not have any query defined other than APPLY CHANGE INTO.