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As the rate of data collection continues to grow rapidly, developingvisualization tools that scale to immense data sets is a serious andever-increasing challenge. Existing approaches generally seek to decouplestorage and visualization systems, performing just-in-time data reduction totransparently avoid overloading the visualizer. We present a new architecturein which the visualizer and data store are tightly coupled. Unlike systems thatread raw data from storage, the performance of our system scales linearly withthe size of the final visualization, essentially independent of the size of thedata. Thus, it scales to massive data sets while supporting interactiveperformance (sub-100 ms query latency). This enables a new class ofvisualization clients that automatically manage data, quickly and transparentlyrequesting data from the underlying database without requiring the user toexplicitly initiate queries. It lays a groundwork for supporting trulyinteractive exploration of big data and opens new directions for research onscalable information visualization systems.

Mr. Plotter: Unifying Data Reduction Techniques in Storage and Visualization Systems