the complexity of data exchange
Data exchange is the problem of transforming data structured under a source schema into data structured under a target schema in such a way that all constraints of a schema mapping are satisfied. At the heart of data exchange, lies a basic decision problem, called the existence-of-solutions problem: given a source instance, is there a target instance that satisfies the constraints of the schema mapping at hand? Earlier work showed that for schema mappings specified by embedded implicational dependencies, this problem is solvable in polynomial time, assuming that (1) the schema mapping is kept fixed and (2) the constraints of the schema mapping satisfy a certain structural condition, called weak acyclicity.We investigate the effect of these assumptions on the complexity of the existence-of-solutions problem, and show that each one is indispensable in deriving polynomial-time algorithms for this problem. Specifically, using machinery from universal algebra, we show that if the weak acyclicity assumption is relaxed even in a minimal way, then the existence-of-solutions problem becomes undecidable. We also show that if, in addition to the source instance, the schema mapping is part of the input, then the existence-of-solutions problem becomes EXPTIME-complete. Thus, there is a provable exponential gap between the data complexity and the combined complexity of data exchange. Finally, we study restricted classes of schema mappings and develop a comprehensive picture for the combined complexity of the existence-of-solutions problem for these restrictions. In particular, depending on the restriction considered, the combined complexity of this problem turns out to be either EXPTIME-complete or coNP-complete.
complexity data exchange schema mappings undecidability heterogenous databases database dependencies data translation