Adaptive Stream Filters for Entity-based Queries with Non-Value Tolerance

We study the problem of applying adaptive filters for approximate query processing in a distributed stream environment. We propose filter bound assignment protocols with the objective of reducing communication cost. Most previous works focus on value-based queries (e.g., average) with numerical error tolerance. In this paper, we cover entity-based queries (e.g., a nearest neighbor query returns object names rather than a single value). In particular, we study non-value-based tolerance (e.g., the answer to the nearest-neighbor query should rank third or above). We investigate different non-value-based error tolerance definitions and discuss how they are applied to two classes of entity-based queries: non-rankbased and rank-based queries. Extensive experiments show that our protocols achieve significant savings in both communication overhead and server computation.

• Type: Conference
• Year: 2005
• Where: VLDB
• Authors: Reynold Cheng, Ben Kao, Sunil Prabhakar, Alan Kwan, Yi-Cheng Tu
• Keywords: Database, Entity-based Queries, Error Tolerance, Numerical Error Tolerance, VLDB 2005