The invention discloses a local core point clustering algorithm based on parallel natural neighbors. The local core point clustering algorithm comprises the following steps of S1, carrying out KD-treeconstruction on data set by adopting a rapid sorting method; S2, obtaining neighborhood information of each data object by adopting a parallel natural neighborhood search algorithm; S3, obtaining a local core point by calculating the density of each data object; S4, calculating the distance between the local core points; S5, constructing a decision diagram, and realizing clustering of local corepoints; S6, distributing non-local core points, and achieving clustering of the data set. Through the algorithm, the distance between the local core points based on the shared neighbors is defined, and the efficiency of the clustering algorithm is improved.