class_docstr: Spark Rating Evaluator
class_docstr_tok: ["Spark","Rating","Evaluator"]
docstr: Calculate Root Mean Squared Error.
  
  Returns:
      float: Root mean squared error.
docstr_tok: ["Calculate","Root","Mean","Squared","Error",".","Returns",":","float",":","Root","mean","squared","error","."]
code: def rmse(self):
      """Calculate Root Mean Squared Error.
  
      Returns:
          float: Root mean squared error.
      """
      return self.metrics.rootMeanSquaredError
  
imports: import numpy
  from recommenders.utils.constants import DEFAULT_PREDICTION_COL, DEFAULT_USER_COL, DEFAULT_ITEM_COL, DEFAULT_RATING_COL, DEFAULT_RELEVANCE_COL, DEFAULT_SIMILARITY_COL, DEFAULT_ITEM_FEATURES_COL, DEFAULT_ITEM_SIM_MEASURE, DEFAULT_TIMESTAMP_COL, DEFAULT_K, DEFAULT_THRESHOLD
label_desc: Use image node_id 2 for calling the SparkRatingEvaluation obj's underlying member method code with example usage: obj.rmse() and returns: self