A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf
.
KTV-Tree: Interactive Top-K Aggregation on Dynamic Large Dataset in the Cloud
2015
2015 IEEE 35th International Conference on Distributed Computing Systems Workshops
This paper studies the problem of supporting interactive top-k aggregation query over dynamic data in the cloud. We propose KTV-TREE, a top-K Threshold-based materialized View TREE, which achieves the fast processing of top-k aggregation queries by efficiently materialized views. A segment treebased structure is adopted to organize the views in a hierarchical manner. A suite of protocols are proposed for incrementally maintaining the views. Experiments are performed for evaluating the
doi:10.1109/icdcsw.2015.32
dblp:conf/icdcsw/TangLTH15
fatcat:4selowu3grezle6a3salcedogy