auto loader

[databrickk]

source_df = (spark.readStream

                 .format("cloudFiles")

                 .option("cloudFiles.format", "csv")

                 .option("header", "true")

                 .option("timestampFormat", "d-M-y H.m")

                 .option("cloudFiles.schemaLocation", f"{landing_folder_path}/Opportunity_schema")

                 #.option("cloudFiles.inferColumnTypes", "true")

                 .schema(schema)  # Explicitly define schema to avoid invalid characters

                 .load(f"{landing_folder_path}/Opportunity")

    )

    source_df = source_df.filter("Id IS NOT NULL")  # Example of filtering out corrupt data

    write_query = (source_df.writeStream

                   .format("delta")

                   .option("checkpointLocation", f"{landing_folder_path}/Opportunity/checkpoint")

                   .option("mergeSchema", "false")

                   .outputMode("append")

                   .trigger(availableNow=True)

                   .toTable("dev.demo_db.Opportunity_raw")

    )

    write_query.awaitTermination()  # Ensure the stream is running

ingest()
i have issue with auto loader that i can't getting incremental load on this . if rerun the ingest() the some unstructured data ingecting into  Opportunity_raw