## 4 Results and Discussion
### Synthetic Workflows
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline
**Node** & **Task Name** & **Task Type** & **Task Class** & **Rows** & **Columns** & **Categorical Columns** & **Dataset Size (MB)** \\ \hline \(t_{0}\) & Naive Bayes & Estimator & Classification & 2,939,059 & 18 & 4 & 198.94 \\ \(t_{1}\) & FPGrowth & Estimator & Association Rules & 494,156 & 180 & 180 & 417.01 \\ \(t_{2}\) & Naive Bayes & Estimator & Classification & 5,000,000 & 27 & 0 & 321.86 \\ \(t_{3}\) & K-Means & Estimator & Clustering & 1,000,000 & 104 & 0 & 247.96 \\ \(t_{4}\) & Decision Tree & Estimator & Classification & 4,000,000 & 53 & 0 & 505.45 \\ \(t_{5}\) & Decision Tree & Estimator & Classification & 4,000,000 & 27 & 0 & 257.49 \\ \(t_{6}\) & Decision Tree & Estimator & Classification & 5,000,000 & 129 & 0 & 1542.58 \\ \(t_{7}\) & K-Means & Estimator & Clustering & 2,000,000 & 53 & 0 & 252.73 \\ \(t_{8}\) & Naive Bayes & Estimator & Classification & 2,000,000 & 104 & 0 & 495.90 \\ \(t_{9}\) & Naive Bayes & Estimator & Classification & 1,000,000 & 129 & 0 & 307.57 \\ \(t_{10}\) & SVM & Estimator & Classification & 2,000,000 & 53 & 0 & 252.72 \\ \(t_{11}\) & K-Means & Estimator & Clustering & 2,049,280 & 9 & 2 & 122.03 \\ \(t_{12}\) & GMM & Estimator & Clustering & 2,458,285 & 28 & 0 & 145.01 \\ \(t_{13}\) & K-Means & Estimator & Clustering & 9169 & 5812 & 1 & 101.89 \\ \(t_{14}\) & SVM & Estimator & Classification & 2,000,000 & 27 & 0 & 128.75 \\ \(t_{15}\) & K-Means & Estimator & Clustering & 3,000,000 & 104 & 0 & 743.87 \\ \(t_{16}\) & SVM & Estimator & Classification & 3,000,000 & 53 & 0 & 379.09 \\ \(t_{17}\) & SVM & Estimator & Classification & 14,410 & 1921 & 0 & 127.38 \\ \(t_{18}\) & K-Means & Estimator & Clustering & 5,000,000 & 53 & 0 & 631.81 \\ \(t_{19}\) & K-Means & Estimator & Clustering & 5,000,000 & 104 & 0 & 1239.78 \\ \(t_{20}\) & K-Means & Estimator & Clustering & 2,000,000 & 78 & 0 & 371.93 \\ \(t_{21}\) & SVM & Estimator & Classification & 3,000,000 & 104 & 0 & 743.87 \\ \(t_{22}\) & K-Means & Estimator & Clustering & 2,939,059 & 18 & 4 & 198.94 \\ \(t_{23}\) & SVM & Estimator & Classification & 19,213 & 1442 & 0 & 123.28 \\ \(t_{24}\) & Decision Tree & Estimator & Classification & 3,000,000 & 129 & 0 & 922.69 \\ \(t_{25}\) & K-Means & Estimator & Clustering & 1,959,372 & 26 & 4 & 189.55 \\ \(t_{26}\) & Decision Tree & Estimator & Classification & 4,898,431 & 18 & 4 & 331.57 \\ \(t_{27}\) & Naive Bayes & Estimator & Classification & 4,898,431 & 18 & 4 & 331.57 \\ \(t_{28}\) & K-Means & Estimator & Clustering & 2,939,059 & 34 & 4 & 334.91 \\ \(t_{29}\) & K-Means & Estimator & Clustering & 4,898,431 & 18 & 4 & 331.57 \\ \(t_{30}\) & K-Means & Estimator & Clustering & 1,966,628 & 42 & 0 & 170.49 \\ \(t_{31}\) & Naive Bayes & Estimator & Classification & 1,959,372 & 18 & 4 & 132.62 \\ \(t_{32}\) & K-Means & Estimator & Clustering & 3,000,000 & 78 & 0 & 557.91 \\ \(t_{33}\) & Decision Tree & Estimator & Classification & 3,000,000 & 53 & 0 & 379.09 \\ \(t_{34}\) & Decision Tree & Estimator & Classification & 14,410 & 2401 & 0 & 159.71 \\ \(t_{35}\) & K-Means & Estimator & Clustering & 2,939,059 & 42 & 4 & 386.53 \\ \(t_{36}\) & Decision Tree & Estimator & Classification & 2,939,059 & 34 & 4 & 334.91 \\ \(t_{37}\) & Decision Tree & Estimator & Classification & 4,000,000 & 129 & 0 & 1230.24 \\ \(t_{38}\) & Naive Bayes & Estimator & Classification & 1,000,000 & 53 & 0 & 126.36 \\ \(t_{39}\) & GMM & Estimator & Clustering & 1,000,000 & 53 & 0 & 126.36 \\ \(t_{40}\) & Decision Tree & Estimator & Classification & 2,939,059 & 18 & 4 & 198.94 \\ \(t_{41}\) & K-Means & Estimator & Clustering & 4,898,431 & 18 & 4 & 331.57 \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Task and dataset descriptions (Workflow 1). \begin{table}
\begin{tabular}{c c c c c} \hline \hline  & **RMSE** & **MAE** & **Adjusted \(R^{2}\)** & **Pearson Correlation** \\ \hline Storage Memory & 246.63 & 95.6 & 0.96 & 0.98 \\ Execution & 4.7 & 1.6 & 0.99 & 0.99 \\ Memory & Duration & 20,354.38 & 7,877.72 & 0.80 & 0.91 \\ \hline \hline \end{tabular}
\end{table}