code: def run(self,
            job_name,
            handler_spec,
            input_reader_spec,
            output_writer_spec=None,
            params=None,
            shards=None,
            base_path=None):
      
      if shards is None:
        shards = parameters.config.SHARD_COUNT
      if base_path is None:
        base_path = parameters.config.BASE_PATH
      mapreduce_id = control.start_map(
          job_name,
          handler_spec,
          input_reader_spec,
          params or {},
          mapreduce_parameters={
              "done_callback": self.get_callback_url(),
              "done_callback_method": "GET",
              "pipeline_id": self.pipeline_id,
              "base_path": base_path,
          },
          shard_count=shards,
          output_writer_spec=output_writer_spec,
          queue_name=self.queue_name,
          )
      self.fill(self.outputs.job_id, mapreduce_id)
      self.set_status(console_url="%s/detail?mapreduce_id=%s" % (
          (base_path, mapreduce_id)))
docs: Start a mapreduce job.
  
      Args:
        job_name: mapreduce name. Only for display purpose.
        handler_spec: fully qualified name to your map function/class.
        input_reader_spec: fully qualified name to input reader class.
        output_writer_spec: fully qualified name to output writer class.
        params: a dictionary of parameters for input reader and output writer
          initialization.
        shards: number of shards. This provides a guide to mapreduce. The real
          number of shards is determined by how input are splited.