code: private static float computeRowUsageFraction(final long numRows, final long train_samples_per_iteration, final boolean replicate_training_data) {
      float rowUsageFraction = (float)train_samples_per_iteration / numRows;
      if (replicate_training_data) rowUsageFraction /= H2O.CLOUD.size();
      assert(rowUsageFraction > 0);
      return rowUsageFraction;
    }
docs: Compute the fraction of rows that need to be used for training during one iteration
  @param numRows number of training rows
  @param train_samples_per_iteration number of training rows to be processed per iteration
  @param replicate_training_data whether of not the training data is replicated on each node
  @return fraction of rows to be used for training during one iteration