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SIGMOD
2005
ACM
162views Database» more  SIGMOD 2005»
14 years 11 months ago
Fast and Approximate Stream Mining of Quantiles and Frequencies Using Graphics Processors
We present algorithms for fast quantile and frequency estimation in large data streams using graphics processor units (GPUs). We exploit the high computational power and memory ba...
Naga K. Govindaraju, Nikunj Raghuvanshi, Dinesh Ma...
SIGMOD
2005
ACM
150views Database» more  SIGMOD 2005»
14 years 11 months ago
BRAID: Stream Mining through Group Lag Correlations
The goal is to monitor multiple numerical streams, and determine which pairs are correlated with lags, as well as the value of each such lag. Lag correlations (and anticorrelation...
Yasushi Sakurai, Spiros Papadimitriou, Christos Fa...
SIGMOD
2002
ACM
91views Database» more  SIGMOD 2002»
14 years 11 months ago
A scalable hash ripple join algorithm
Recently, Haas and Hellerstein proposed the hash ripple join algorithm in the context of online aggregation. Although the algorithm rapidly gives a good estimate for many join-agg...
Gang Luo, Curt J. Ellmann, Peter J. Haas, Jeffrey ...
PODS
2002
ACM
138views Database» more  PODS 2002»
14 years 11 months ago
Fast Algorithms For Hierarchical Range Histogram Construction
Data Warehousing and OLAPapplications typically view data as having multiple logical dimensions e.g., product, location with natural hierarchies de ned on each dimension. OLAP que...
Sudipto Guha, Nick Koudas, Divesh Srivastava
PODS
2003
ACM
143views Database» more  PODS 2003»
14 years 11 months ago
Maintaining variance and k-medians over data stream windows
The sliding window model is useful for discounting stale data in data stream applications. In this model, data elements arrive continually and only the most recent N elements are ...
Brian Babcock, Mayur Datar, Rajeev Motwani, Liadan...