A distributed MapReduce system built on Hazelcast that processes millions of parking tickets from NYC and Chicago in parallel. The architecture leverages a client-server model with custom mappers, reducers, and collators to execute analytical queries—ranging from revenue aggregation by agency to time-series trend analysis—across a horizontally scalable cluster.

Built for the Distributed object-oriented programming course at Buenos Aires Institute of Technology (ITBA).