  Materialized view is used in large data centric applications to expedite
query processing. The efficiency of materialized view depends on degree of
result found against the queries over the existing materialized views.
Materialized views are constructed following different methodologies. Thus the
efficacy of the materialized views depends on the methodology based on which
these are formed. Construction of materialized views are often time consuming
and moreover after a certain time the performance of the materialized views
degrade when the nature of queries change. In this situation either new
materialized views could be constructed from scratch or the existing views
could be upgraded. Fresh construction of materialized views has higher time
complexity hence the modification of the existing views is a better
solution.Modification process of materialized view is classified under
materialized view maintenance scheme. Materialized view maintenance is a
continuous process and the system could be tuned to ensure a constant rate of
performance. If a materialized view construction process is not supported by
materialized view maintenance scheme that system would suffer from performance
degradation. In this paper a new materialized view maintenance scheme is
proposed using markovs analysis to ensure consistent performance. Markovs
analysis is chosen here to predict steady state probability over initial
probability.
