code: def update_predict_xshards(xshard, pred_xshards):
      def updates(d1_d2):
          d1, d2 = d1_d2
          d1.update(d2)
          return d1
  
      result = SparkXShards(
          xshard.rdd.zip(pred_xshards.rdd).map(updates)
      )
      return result
  
file_path: analytics-zoo/pyzoo/zoo/orca/learn/utils.py
imports: from zoo.common.utils import get_file_list
  from zoo.orca.data import SparkXShards
  from zoo.orca.data.utils import get_size
  from zoo.util.utils import convert_row_to_numpy
  import numpy
label_desc: Use image node_id 3 for calling a global function with example usage: update_predict_xshards(xshard, pred_xshards) and returns: result, d1