class_docstr: A collection of data which can be pre-processed in parallel on Spark
class_docstr_tok: ["A","collection","of","data","which","can","be","pre-processed","in","parallel","on","Spark"]
code: def _get_class_name(self):
      if "class_name" in self.type:
          return self.type["class_name"]
      else:
          self.type["class_name"] = self._for_each(
              get_class_name
          ).first()
          return self.type["class_name"]
  
imports: from py4j.protocol import Py4JError
  from zoo.orca.data.utils import *
  from zoo.orca import OrcaContext
  from zoo.common.nncontext import init_nncontext
  from zoo import ZooContext, get_node_and_core_number
  from zoo.util import nest
label_desc: Use image node_id 21 for calling the SparkXShards obj's underlying member method code with example usage: obj._get_class_name() and returns: self, self