Incremental computations over strongly distributed databases

Abstract

SUMMARYThis contribution deals with systematic exploitation of logical reduction techniques to big distributed data handling. The particular applications are views and parallel updates over large-scale distributed databases as well as handling of queries over different generations of databases. Logical reduction techniques come in two favors. The first one: the syntactically defined translation schemes, which describe transformations of database schemes. They give rise to two induced maps, translations and transductions. Transductions describe the induced transformation of database instances and the translations describe the induced transformations of queries. The second one: Feferman-Vaught reductions, which are applied in situations of distributed databases. The reduction describes how the queries over a distributed database can be computed from queries over the components and queries over the index set. Combination and development of these techniques allow us to introduce the notion of strongly distributed databases. For such databases, we extend and generalize the known propagation techniques. The method allows unification of the distributed and parallel computation and communication as well as significant reduction of the communication load. The proposed general approach may be easily adopted to other distributed objects and their integration into large-scale systems.

Distributed computing track at SYNASC 2014

“…For this special issue, we have selected three top papers to be published as extended versions. The papers are from distinct areas with focus on theoretical aspects related to semantics for a DNA‐inspired language with applicability in parallel and distributed computing , queries on distributed databases , and model checking on MapReduce . As such, it covers a broad spectrum ranging from concurrent languages and distributed databases to cloud applications.…”

“…“Incremental computations over strongly distributed databases” deals with the systematic exploitation of logical reduction techniques to big distributed data handling. The particular applications are views and parallel updates over large‐scale distributed databases as well as handling of queries over different generations of databases.…”