The invention discloses an efficient distributed large-scale dynamic graph k-kernel maintenance method and belongs to the field of graphic information retrieval. The method includes a static k-kernel maintenance sub-method, an edge-insertion k-kernel maintenance sub-method and an edge-deletion k-kernel maintenance sub-method; according to the static k-kernel maintenance sub-method, information of neighbor vertexes of each vertex is fully utilized, and each vertex can maintain own kernel number quickly by accessing the information of the neighbor vertexes; meanwhile, according to the edge-insertion k-kernel maintenance sub-method and the edge-deletion k-kernel maintenance sub-method, traversing is started from the vertex of the inserted or deleted edge during the computation process to find a minimal vertex task queue set possibly to be updated, and same operation is executed on each vertex in the vertex task queue. Through the method, dynamic graph data vibration can be updated in real time, expansion is facilitated to perform distributed computation, and large-scale graph data difficult to compute with single computer can be processed.