View materialization is being practiced over several years in large data centric applications like database, data warehouse, data mining etc. for faster query processing. Initially the materialized views are formed based on some methodologies, however the performance (hit-miss ratio) of the materialized views may degrade after certain time if the incoming query pattern changes. This situation could be handled efficiently by employing a view maintenance scheme which works dynamically during query execution at run time. As these materialized views involves huge amount of data, consideration of time and space complexity during the maintenance process plays an important role. In this paper authors adopt an incremental view maintenance policy based on attribute affinity to update the materialized views at run time without using extra space and minimizing the data transfer between the secondary memory and primary memory (where the active materialized views reside). This in turn reduces time complexity and supports incremental maintenance eliminating the requirement of full replacement of existing materialized views. © 2014 IEEE.