that for equations all data measurements are in megabytes and time in milliseconds.

     **Algorithm**     **RMSE(ms)**   **R-Squared**   **Phase**
  ------------------- -------------- --------------- -----------
          SVM            4655.42          0.96         Shuffle
     Random Forest       5027.23          0.95         Shuffle
     Decision Tree       8370.37          0.78         Shuffle
   Linear Regression     4774.75          0.95         Shuffle
          SVM            2747.380         0.94          Write
     Random Forest       2940.09          0.93          Write
     DecisionTree        9366.400         0.68          Write
   Linear Regression     6256.47          0.88          Write

  : RMSE and R-Squared values for Shuffle and Write

\[table:rmsersquared\]

![**A plot and best fit for each of the generic phase: The main purpose of this plot is to show how performance(ms) changes with respect to data size (MB).** []{data-label="genericmodels"}](images/genericmodels2.png){width="8cm"}

**Read Model**
--------------

The Read Phase of Figure \[genericmodels\] supports our initial assumption in that there is a linear relationship between the size of input data and the processing time. The model obtained using linear regression is presented in Equation . The read plot in Figure \[crossvalidation\] and $RMSE$ value of $4.08$ proves a strong case for the accuracy of the model. $$T_{read} = 0.01 \times D + 1.33
\label{eq:readmodel}$$

**Collect Model**
-----------------

Map output data is collected as soon as map tasks complete; once the circular buffer of each map task reaches the predefined threshold of 80% data is then written 