Supporting Incremental Join Queries on Ranked Inputs

This paper investigates the problem of incremental joins of multiple ranked data sets when the join condition is a list of arbitrary user-defined predicates on the input tuples. This problem arises in many important applications dealing with ordered inputs and multiple ranked data sets, and requiring the top k solutions. We use multimedia applications as the motivating examples but the problem is equally applicable to traditional database applications involving optimal resource allocation, scheduling, decision making, ranking, etc. We propose an algorithm J that enables querying of ordered data sets by imposing arbitrary userdefined join predicates. The basic version of the algorithm does not use any random access but a J PA variation can exploit available indexes for efficient random access based on the join predicates. A special case includes the join scenario considered by Fagin [1] for joins based on identical keys, and in that case, our algorithms perform as efficiently as ...

• Type: Conference
• Year: 2001
• Where: VLDB
• Authors: Apostol Natsev, Yuan-Chi Chang, John R. Smith, Chung-Sheng Li, Jeffrey Scott Vitter
• Keywords: Data Sets, Join Predicates, Multiple Ranked Data, VLDB 2001