Analyzing data to find trends, correlations, and stable patterns is an important problem for many industrial applications. In this paper, we propose a new technique based on paral...
Kaidi Zhao, Bing Liu, Thomas M. Tirpak, Andreas Sc...
Graph-theoretic abstractions are extensively used to analyze massive data sets. Temporal data streams from socioeconomic interactions, social networking web sites, communication t...
Many parallel join algorithms have been proposed in the last several years. However, most of these algorithms require that the amount of data to be joined is known in advance in o...
Wide-area distribution raises significant performance problems for traditional query processing techniques as data access becomes less predictable due to link congestion, load imb...
Workloads that comb through vast amounts of data are gaining importance in the sciences. These workloads consist of "needle in a haystack" queries that are long running ...