Abstract: | A streaming graph is a graph formed by a sequence of incoming edges with time stamps. Unlike the static graphs, the streaming graph is highly dynamic and time-related. Streaming graphs in the real world, which are of the high volume and velocity, can be challenging to the classic graph data structures: data of internet traffic, social network communication, and financial transections, etc. The traditional graph storage models like the adjacency matrix and the adjacency list are no longer sufficient for the large amount data and high frequency updates. And most the streaming graph structures are only supports the specific graph algorithms. Here a new data structure is presented to meet the challenge: a double orthogonal list in hash table (Dolha) as a high speed and high memory efficiency graph structure. Dolha has constant time cost for single edge processing, and near-linear space cost. Moreover, time cost for neighborhood queries in Dolha is linear, which enables it to support most algorithms of graphs without extra cost. A persistent structure based on Dolha is also presented, to handle the sliding window update and time related queries. |