Using machine learning to optimize parallelism in big data applications
A Study of Cross-Validation and Bootstrap for Accuracy Estimation and Model Selection
Bubble-up: Increasing utilization in modern warehouse scale computers via sensible co-locations
MapReduce: Simplified Data Processing on Large Clusters
Resilient Distributed Datasets: A Fault-Tolerant Abstraction for In-Memory Cluster Computing
Paragon: QoS-aware scheduling for heterogeneous datacenters