SwiftTuna: Incrementally Exploring Large-scale Multidimensional Data

The advance in distributed computing technologies opens up new possibilities of data exploration even for datasets with a few billion entries. In this paper, we present SwiftTuna, an interactive system that brings in modern cluster computing technologies (i.e., inmemory computing) to InfoVis, allowing rapid and incremental exploration of large-scale multidimensional data without building precomputed data structures (e.g., data cubes). Our performance evaluation demonstrates that SwiftTuna enables data exploration of a real-world dataset with four billion records while preserving the latency between incremental responses within a few seconds.