Abstract: Due to the high communication overhead caused by the complex query across nodes in the distributed information network model (INM) database management system, a dynamic data partition and query processing algorithm is proposed. Based on the relationship characteristics of INM model and the historical relationship information, it obtains the initial relevance between data, then mines the potential relevance between data based on the historical query information and dynamically adjusts the data with strong correlation to the same processing node, so as to reduce the number of cross-nodes traversals in complex query. The extensive experiments on synthetic dataset WatDiv are carried out. The experimental results show that the query time of this algorithm is reduced by 35%~55% compared with the consistent hash algorithm in the period by ensuring the load balance of the number of objects and the proportion of relationship pairs between nodes, and the time fluctuation of the same query in multiple periods is controlled within 5%~10%, which ensures the stability of complex queries.

Key words: information network model, dynamic data partition, relevance, load balancing, distributed system