我正在使用一个sql炼金术会话在azuredatabricks中的数据库上运行sql查询。我的查询包含一个用户定义的函数，但是当我运行查询时它会返回
infomessages=[“*org.apache.hive.service.cli.hivesqlexception:error running 查询：org.apache.spark.sql.analysisexception:未定义function:my_method
下面的例子

class DatabaseQuery(DatabaseLibrary):
    def __init__(self):
        self.table_model = None
        self.column_names = []
        self.conn = None
        self.meta = None
        self.engine = None
        self.session = None
        self.query_list = []

    def connect_database(self, region, token, database, http_path):

        try:
            dbfs_engine = create_engine(
                "databricks+pyhive://token:"
                + token
                + "@"
                + region
                + "xxxxxx/"
                + database,
                connect_args={"http_path": http_path},
                echo=True,
            )
            self._set_metadata_databricks(dbfs_engine)
            Session = sessionmaker(bind=dbfs_engine)
            self.session = Session()
            self.engine = dbfs_engine
            self.conn = dbfs_engine.connect()
        except Exception as e:
            traceback.print_exc()
            raise

   def my_method(name):
       return Upper(name)

   query =("select my_method(names.NAME) from db.names").fetchall()
   result = self.session.execute(query).fetchall()

使用pyspark，我可以简单地通过向spark对象注册udf来做到这一点

convert_maximo_date = udf(common.convert_maximo_date)
self.spark.udf.register("convert_maximo_date", convert_maximo_date)

这样做是否可能与sql alchemy连接类似，以便可以执行带有用户定义函数的查询？