数据库内连通元分析
In-database connected component analysis
摘要：
我们描述了一个大数据实用的，SQL实现的算法，有效地确定连接组件的图形数据存储在大规模并行处理（MPP）关系数据库。所描述的算法是一个线性空间，随机算法，总是终止于正确的答案，但受到随机的运行时间，这样对于任何$ε>0$和任何输入图$G=\langle V, E \rangle$的算法终止后，$\mathop{\text{O}}(\log |V|)$ SQL查询的概率至少为$1-ε$，我们经验证明，在实践中转化为一个准线性运行时间。
英文摘要：
We describe a Big Data-practical, SQL-implementable algorithm for efficiently determining connected components for graph data stored in a Massively Parallel Processing (MPP) relational database. The algorithm described is a linear-space, randomised algorithm, always terminating with the correct answer but subject to a stochastic running time, such that for any $ε>0$ and any input graph $G=\langle V, E \rangle$ the algorithm terminates after $\mathop{\text{O}}(\log |V|)$ SQL queries with probability of at least $1-ε$, which we show empirically to translate to a quasi-linear runtime in practice.
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