论文标题
LMFAO：用于集体聚合的引擎
LMFAO: An Engine for Batches of Group-By Aggregates
论文作者
论文摘要
LMFAO是一种内存优化和执行引擎，用于大批组合的集体汇总。这样的数据库工作负载捕获了各种数据科学应用程序的数据密集型计算。 我们展示了三种流行模型的LMFAO：带有批处梯度下降的山脊线性回归，带购物车的决策树以及与RK均值的聚类。
LMFAO is an in-memory optimization and execution engine for large batches of group-by aggregates over joins. Such database workloads capture the data-intensive computation of a variety of data science applications. We demonstrate LMFAO for three popular models: ridge linear regression with batch gradient descent, decision trees with CART, and clustering with Rk-means.
