Computing measures for tweeter data cubes mining of cube group over data sets are impossible for many analyses in the tweeter.We have to compute the data set taken from tweeter user. You have to create a cube creation and then measure dimension setting using the roll up function.In the real world various challenges in the cube materlization and mining on web data sets. Map shuffle Reduce can be efficient extract cube and aggregate function on attribtes of tweeter.MR-Cube can be extract from efficient and effective PC cubes of holistic measures over large-tuple aggregation sets.In the existing techniques can not measure the holistic scale to the large tuples.
DOI: 10.17762/ijritcc2321-8169.150614
