Querying Road Traffic Data from a Document Store

We present a novel system called Extrac for querying a large database of road traffic information. Such traffic data are collected from an ITS (Intelligent transportation systems) center of Busan and represents speed values of all road segments of Busan for every 5 minutes. Extrac stores the collected traffic data into a NoSQL document database and supports a traffic congestion queries. It adopts a suite of new approaches for (a) transformation of traffic data into pattern summaries based on a MapReduce framework, and (b) efficient congestion query processing which utilizes single value decomposition (SVD) of transformed matrices. We demonstrate the Extract systems using real traffic data of Busan metropolitan city.