Abstract
The management, analysis and sharing of big data usually involves interacting with multiple heterogeneous remote and local resources. Performing data-intensive operations in this environment is typically a non-automated and arduous task that often requires deep knowledge of the underlying technical details by non-experts. MapReduce box (MRbox) is an open-source experimental application that aims to lower the barrier of technical expertise needed to use powerful big data analytics tools and platforms. MRbox extends the Dropbox interaction paradigm, providing a unifying view of the data shared across multiple heterogeneous infrastructures, as if they were local. It also enables users to schedule and execute analytics on remote computational resources by just interacting with local files and folders. MRbox currently supports Hadoop and ownCloud/B2DROP services and MapReduce jobs can be scheduled and executed. We hope to further expand MRbox so that it unifies more types of resources, and to explore ways for users to interact with complex infrastructures more simply and intuitively.