class_docstr: Submits a Spark batch application to the underlying cluster; wraps the AnalyticDB Spark REST API.
  
  :param file: path of the file containing the application to execute.
  :param class_name: name of the application Java/Spark main class.
  :param args: application command line arguments.
  :param conf: Spark configuration properties.
  :param jars: jars to be used in this application.
  :param py_files: python files to be used in this application.
  :param files: files to be used in this application.
  :param driver_resource_spec: The resource specifications of the Spark driver.
  :param executor_resource_spec: The resource specifications of each Spark executor.
  :param num_executors: number of executors to launch for this application.
  :param archives: archives to be used in this application.
  :param name: name of this application.
  :param cluster_id: The cluster ID of AnalyticDB MySQL 3.0 Data Lakehouse.
  :param rg_name: The name of resource group in AnalyticDB MySQL 3.0 Data Lakehouse cluster.
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code: def __init__(
      self,
      *,
      file: str,
      class_name: str | None = None,
      args: Sequence[str | int | float] | None = None,
      conf: dict[Any, Any] | None = None,
      jars: Sequence[str] | None = None,
      py_files: Sequence[str] | None = None,
      files: Sequence[str] | None = None,
      driver_resource_spec: str | None = None,
      executor_resource_spec: str | None = None,
      num_executors: int | str | None = None,
      archives: Sequence[str] | None = None,
      name: str | None = None,
      cluster_id: str,
      rg_name: str,
      **kwargs: Any,
  ) -> None:
      super().__init__(**kwargs)
  
      self.spark_params = {
          "file": file,
          "class_name": class_name,
          "args": args,
          "conf": conf,
          "jars": jars,
          "py_files": py_files,
          "files": files,
          "driver_resource_spec": driver_resource_spec,
          "executor_resource_spec": executor_resource_spec,
          "num_executors": num_executors,
          "archives": archives,
          "name": name,
      }
  
      self._cluster_id = cluster_id
      self._rg_name = rg_name
  
imports: from __future__ import annotations
  import time
  from functools import cached_property
  from typing import TYPE_CHECKING, Any, Sequence
  from deprecated.classic import deprecated
  from airflow.exceptions import AirflowException, AirflowProviderDeprecationWarning
  from airflow.models import BaseOperator
  from airflow.providers.alibaba.cloud.hooks.analyticdb_spark import AnalyticDBSparkHook, AppState
label_desc: Use image node_id 1 to create a new AnalyticDBSparkBatchOperator object from inherited base classes: AnalyticDBSparkBaseOperator with example: obj = AnalyticDBSparkBatchOperator()