The embodiment of the invention provides a graph data processing method, which comprises the following steps of: S1, obtaining graph data containing a plurality of vertexes, sorting the vertexes according to the descending order of the vertexes, and taking a sorting serial number as a first resorting ID; S2, sequentially distributing the vertexes of the graph data to each distributed computing node in a distributed computing node cluster in a polling manner according to the first reordering ID and preset granularity; S3, traversing the obtained partial graph data by the computational nodes byusing a hybrid BFS algorithm, and obtaining a local next-layer active vertex set by each computational node after each layer is traversed; S4, after each layer is traversed, performing loop communication between adjacent computing nodes to transmit a local next-layer active vertex set, and determining the compression mode of the local next-layer active vertex set to be transmitted this time beforethe local next-layer active vertex set is transmitted after partial-layer traversal. According to the invention, vertex IDs are subjected to reordering, data compression and loop communication through the out-degree of the vertexes, and the communication efficiency is improved.