  We present PS-DBSCAN, a communication efficient parallel DBSCAN algorithm
that combines the disjoint-set data structure and Parameter Server framework in
Platform of AI (PAI). Since data points within the same cluster may be
distributed over different workers which result in several disjoint-sets,
merging them incurs large communication costs. In our algorithm, we employ a
fast global union approach to union the disjoint-sets to alleviate the
communication burden. Experiments over the datasets of different scales
demonstrate that PS-DBSCAN outperforms the PDSDBSCAN with 2-10 times speedup on
communication efficiency.
  We have released our PS-DBSCAN in an algorithm platform called Platform of AI
(PAI - https://pai.base.shuju.aliyun.com/) in Alibaba Cloud. We have also
demonstrated how to use the method in PAI.
