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Internet is flooded with information every day. Easy access to large amount of information along with difficulty in judging the validity of so much content can lead to information overload . As a result, e-commerce applications and social media sites are increasingly challenged to attract new users and retain existing ones. Based on user interests and preferences, these systems recommend items that may be of interest or value to the customers/users. Recommendation systems help users deal with the information-overload by giving them recommendations of products, etc.They help businesses make more profits, i.e., selling more products. Recommendation systems  are a type of information filtering system that uses the preferences of a group of people to make recommendations to other people. Some of the well-known features of recommendation system are: product recommendation for online shopping, social matching, targeted content/advertising etc. 35% of...

The ability to bring consensus in a network of unreliable services is at the heart of any fault-tolerant distributed system. Apache ZooKeeper is a high-performance open-source server that provides a highly reliable distributed co-ordination and meets the production demands of the web-scale, mission critical applications. ZooKeeper is popular among multi-host, multi-process applications (C, Java bindings) running in data centers. This paper discusses how ZooKeeper is used to implement distributed consensus among the available services.   Every complex distributed application needs a service for maintaining configuration information, naming, providing distributed synchronization, and/or providing group services. Because of the complexity in implementing these solutions for distributed computing, the more natural preference is to use a tried, tested and reliable solution available in the market. ZooKeeper provides a simple interface to a centralized coordinating service. Th...