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W ith the cloud app lica tion requ iring less runn ing tim e and h igher performance as w e ll as m em ory prices con­ tinu ing to decline, the technology o f memory-based d is tribu ted com puting fram e w o rk , such as S park, has received un­ precedented a tten tion and is w id e ly applied. W e designed and im plemented paralle lized D B S C A N a lgo rith m based on Spark, w h ich can m in im ize the shu ffle frequency and the data am ount in shuffle. In o rder to optimize the algorithm para­ lle liza tion stra tegy, we found the bo ttleneck o f a lgo rith m performance th rough the analysis and described the D A G o f para lle l D B S C A N a lgo rith m based on Spark. F in a lly ,we compared the performance o f para lle l D B S C A N a lgo rith m w ith the D B S C A N a lg o rith m , and analyzed the influence o f d iffe re n t parameters on c lustering results. E xperim enta l results show th a t, compared w ith D B S C A N a lg o rith m ,th e runn ing tim e o f para lle l D B S C A N a lg o rith m based on Spark decrea­ ses 37. 2% and the speedup reaches 1. 6 respective ly on a data set containing three m illio n lines w ith o u t obvious loss o f cluste ring accuracy.

基于Spark的并行DBSCAN算法的设计与实现 (Design and Implementation of Parallel DBSCAN Algorithm Based on Spark).