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Study of Map Reduce Over Different Cube Computation Approaches: Survey Paper
Abstract
MapReduce is a programing poser and an related effort for processing and generating super aggregation sets. Users determine a map operate that processes a key/value place to make a set of medium key/value pairs, and a Reduce function work that merges all middle values associated with the very mediate key. Efficient extract of aggregations very significant role in Data wearhouse Store systems. Multidimensionalaccumulation psychotherapy applications data crosswise much dimensions designer for anomalies or unusual patterns. The SQL mass functions and the GROUP BY operator are utilised for accumulation. But Data psychotherapy applications requirement the N-dimensional generality of these operators. Data cube is introduced which is a way of structuring information in N-dimensions so as to spread analysis over few measure. Datawearhouse implementation for the essential part of data cube computation. The precomputation of all or endeavor of a data cube can greatly restrict the salutation quantify and deepen the executing of online analytical processing. Various strategies to Cube Materlization, there are various methods for cube computation and specific computation algorithms, namely Star Cubing, BUC, Multiway array aggregation, parallel algorithms, the computation of shell fragments and. But these techniques some rule so new MapReduce based approach is used.
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References
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