code: function(predictionAndLabels) {
          this.logger = Logger.getLogger("RankingMetrics_js");
          var jvmObject;
          if (predictionAndLabels instanceof org.apache.spark.mllib.evaluation.RankingMetrics) {
              jvmObject = predictionAndLabels;
          } else {
              jvmObject = new org.apache.spark.mllib.evaluation.RankingMetrics(predictionAndLabels);
          }
  
  
           JavaWrapper.call(this, jvmObject);
  
      }
docs: ::Experimental::
  Evaluator for ranking algorithms.
  
  Java users should use [[RankingMetrics$.of]] to create a {@link RankingMetrics} instance.
  
  @param predictionAndLabels an RDD of (predicted ranking, ground truth set) pairs.
  @classdesc
   
  @param {module:eclairjs.RDD} predictionAndLabels
  @class
  @memberof module:eclairjs/mllib/evaluation