class_docstr: Runs Mapreduce job in Data Proc cluster.
  
  :param main_jar_file_uri: URI of jar file with job.
                            Can be placed in HDFS or S3. Can be specified instead of main_class.
  :param main_class: Name of the main class of the job. Can be specified instead of main_jar_file_uri.
  :param file_uris: URIs of files used in the job. Can be placed in HDFS or S3.
  :param archive_uris: URIs of archive files used in the job. Can be placed in HDFS or S3.
  :param jar_file_uris: URIs of JAR files used in the job. Can be placed in HDFS or S3.
  :param properties: Properties for the job.
  :param args: Arguments to be passed to the job.
  :param name: Name of the job. Used for labeling.
  :param cluster_id: ID of the cluster to run job in.
                     Will try to take the ID from Dataproc Hook object if it's specified. (templated)
  :param connection_id: ID of the Yandex.Cloud Airflow connection.
code: def execute(self, context: Context) -> None:
      hook = self._setup(context)
      hook.client.create_mapreduce_job(
          main_class=self.main_class,
          main_jar_file_uri=self.main_jar_file_uri,
          jar_file_uris=self.jar_file_uris,
          archive_uris=self.archive_uris,
          file_uris=self.file_uris,
          args=self.args,
          properties=self.properties,
          name=self.name,
          cluster_id=self.cluster_id,
      )
  
imports: from __future__ import annotations
  import warnings
  from dataclasses import dataclass
  from typing import TYPE_CHECKING, Iterable, Sequence
  from airflow.models import BaseOperator
  from airflow.providers.yandex.hooks.yandexcloud_dataproc import DataprocHook
label_desc: Use image node_id 2 for calling the DataprocCreateMapReduceJobOperator obj's underlying member method code with example usage: obj.execute(context) without return types