Big Data Mining using Map Reduce: A Survey Paper
Journal Title: IOSR Journals (IOSR Journal of Computer Engineering) - Year 2014, Vol 16, Issue 6
Abstract
Abstract: Big data is large volume, heterogeneous, distributed data. Big data applications where datacollection has grown continuously, it is expensive to manage, capture or extract and process data using existingsoftware tools. For example Weather Forecasting, Electricity Demand Supply, social media and so on. Withincreasing size of data in data warehouse it is expensive to perform data analysis. Data cube commonlyabstracting and summarizing databases. It is way of structuring data in different n dimensions for analysis oversome measure of interest. For data processing Big data processing framework relay on cluster computers andparallel execution framework provided by Map-Reduce. Extending cube computation techniques to thisparadigm. MR-Cube is framework (based on mapreduce)used for cube materialization and mining over massivedatasets using holistic measure. MR-Cube efficiently computes cube with holistic measures over billion-tupledatasets
Authors and Affiliations
Shital Suryawanshi , Prof. V. S. Wadne
Keywords
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