Databricks 최신 업데이트: 데이터 커넥터, AI 어시스턴트 및 파운데이션 모델 통합

def df_refund_road_update():
    df = spark.read_table("caspersdev.recommender.refund_recommendations")
    # ... (중략)

@dp.foreach_batch_sink(target="merge_into_sink")
def feb_batch_update(batch_df, batch_id):
    batch_df.createOrReplaceTempView("batch_df_view")
    df.sparkSession.sql("""
        MERGE INTO caspersdev.recommender.df_refund_rcmd_update AS T
        USING batch_df_view AS S
        ON T.order_id = S.order_id
        WHEN MATCHED THEN UPDATE SET T.agent_response = S.agent_response
    """)