Abstract: Data resources stored in different units and departments in cloud environment are cross-domain,heterogeneous and complex.As a unified data model for cross-origin and heterogeneous data sources,data service can publish data sources in the form of services,and generate data composition view by composing several data services according to users’ data requirements.Since the data sources are autonomous,it becomes a key issue to update data composition view in real time with minimal cost.This paper proposes a data composition view positioning update approach based on incremental logs.The latest data changes of data sources are captured according to incremental logs,and then the attributes and tuples in data composition view are indexed.The index numbers of different tuples can be calculated with positioning attributes.The corresponding tuple update operations can be performed according to data changes’ type.A log-based update data acquisition algorithm and a data composition view positioning update algorithm are presented.The proposed approach has been evaluated in a cross-origin heterogeneous elevator data service system by using datasets from multiple departments.When the proportion of the number of changed tuples is much smaller than the total number of tuples,the update efficiency of positioning update approach is much higher than existing methods.When the number of attributes of the data composition view is larger,the update efficiency of the positioning update approach is much higher than existing methods.

Key words: Data composition view, Data service, Incremental logs, Positioning update, Real time