The invention relates to the technical field of graph
data processing, and provides a graph
data processing method based on
cache optimization, which comprises the following steps: constructing a
cache optimization representation of graph data, and distributing a bit vector GT-vector with a
fixed length of k for each vertex in a graph, each bit representing whether the vertex belongs to a pre-calculated maximum independent set; reserving
adjacency list representation of the graph data, and storing the
adjacency list representation as reference data in a memory; for an edge query request, reading GT-vectors of two vertexes from a
CPU cache, and executing bit and operation; if the bit and the result are non-zero, judging that the edge is non-edge and immediately returning a first Boolean result indicating that the edge does not exist; and if the bit and result is zero, querying the
adjacency list in the memory for
verification, and returning a second Boolean result indicating that the edge exists or does not exist. According to the method and the device, the
hybrid architecture combining the bit vector representation of
cache optimization and the adjacency
list is constructed, so that the magnitude order improvement of the graph
data processing performance is realized on the premise of ensuring that the query result is completely accurate.