We consider the problem of estimating set-expression cardinality in a distributed streaming environment where rapid update streams originating at remote sites are continually transmitted to a central processing system. At the core of our algorithmic solutions for answering set-expression cardinality queries are two novel techniques for lowering data communication costs without sacrificing answer precision. Our first technique exploits global knowledge of the distribution of certain frequently occurring stream elements to significantly reduce the transmission of element state information to the central site. Our second technical contribution involves a novel way of capturing the semantics of the input set expression in a boolean logic formula, and using models (of the formula) to determine whether an element state change at a remote site can affect the set expression result. Results of our experimental study with real-life as well as synthetic data sets indicate that our distributed set-expression cardinality estimation algorithms achieve substantial reductions in message traffic compared to naive approaches that provide the same accuracy guarantees.
The work is extended also by Das et al. REF to support estimation of set-expression cardinality in a distributed streaming environment.
Distributed Set-Expression Cardinality Estimation
VLDB
Computer Science