Stable Modeling on Resource Usage Parameters of MapReduce Application-Figure 2. ACF plot of Residuals of Regression Model of Terasort

<p>, are uncorrelated. If the error term is uncorrelated, it proves that there exists strong randomness in residuals of the model and provides the evidence for the unbiased estimate for the true standard error. The autocorrelation plot is used to check this assumption. Figure 2 shows the autocorrelation plot of residuals of regression models of TeraSort application. In Figure 2, the horizontal axis represents lag time and the vertical axis indicates the autocorrelation between residual at time t and residual at other lag time. At lag 0, autocorrelation is always equal to 1 and represents time series itself. Most of the autocorrelation at other lag time fall into the 95% confidence interval, only few of them violate the dashed line. Such a shape of ACF plot proves that residuals are uncorrelated and respects to the independent assumption of the linear regression model residuals.