A LightGBM-XGBoost quantile regression model predicts CI build memory needs, delivering 36 GB average savings per build with under-allocation below 0.3% in production.
Sap hana database: Data management for modern business applications.SIGMOD Record, 40:45–51, 12 2011
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Intelligent resource prediction for SAP HANA continuous integration build workloads
A LightGBM-XGBoost quantile regression model predicts CI build memory needs, delivering 36 GB average savings per build with under-allocation below 0.3% in production.