Ranking of Product on Big Data using Apache Spark

Smita M. Deshpande, Rakesh S. Shirsath


Recommendation system has been used by enormous users. It used commonly in recent years, and are used in a variable areas in many popular applications which comprise of movies, songs, bulletin, files, research courses, online shopping, social networking sites, and products recommendation. Gradually, the extent of consumers, products and facts has mature rapidly, the big data scrutiny problem for examination of recommender systems. Here we are evaluating most efficient recommendation system. Conventional recommender systems frequently suffer from deficiency of scalability, efficiency and real time recommendation problems while processing or analysing documents taking place at huge scale. To get rid from these problems, a recommendation system is implemented in Apache Hadoop and Spark including MapReduce paradigm for Bigdata. Proposed Framework can have considerable enhancement in performance associated to traditional tools.

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