Transformation of Continuous Aggregation Join Queries over Data Streams

Transformation of Continuous Aggregation Join Queries over Data Streams

We address continuously processing an aggregation join query over data streams. Queries of this type involve both join and aggregation operations, with windows specified on join input streams. To our knowledge, the existing researches address join query optimization and aggregation query optimization as separate problems. Our observation, however, is that by putting them within the same scope o...

Transformation of Continuous Aggregation Join Queries over Data

Multiple Continuous Queries Evaluation over Data Streams

Query processing for data streams should be continuous and rapid, which requires strict time constraint. In most previous researches, in order to guarantee this constraint, the evaluation order of join predicates in a continuous query is optimized by a greedy. However, the greedy strategy traces only the first promising plan, so that it often finds a sub-optimal plan. This paper proposes an imp...

Monitoring Continuous Band-Join Queries over Dynamic Data

A continuous query is a standing query over a dynamic data set whose query result needs to be constantly updated as new data arrive. We consider the problem of constructing a data structure on a set of continuous band-join queries over two data sets R and S, where each band-join query asks for reporting the set {(r, s) ∈ R×S | a ≤ r−s ≤ b} for some parameters a and b, so that given a data updat...

Dynamic Optimization and Migration of Continuous Queries Over Data Streams

Continuous queries process real-time streaming data and output results in streams for a wide range of applications. Due to the fluctuating stream characteristics, a streaming database system needs to dynamically adapt query execution. This dissertation proposes novel solutions to continuous query adaptation in three core areas, namely dynamic query optimization, dynamic plan migration and parti...