Dynamic Complexity of Parity Exists Queries

Given a graph whose nodes may be coloured red, the parity of the number of red nodes can easily be maintained with first-order update rules in the dynamic complexity framework DynFO of Patnaik and Immerman. Can this be generalised to other or even all queries that are definable in first-order logic extended by parity quantifiers? We consider the query that asks whether the number of nodes that have an edge to a red node is odd. Already this simple query of quantifier structure parity-exists is a major roadblock for dynamically capturing extensions of first-order logic. We show that this query cannot be maintained with quantifier-free first-order update rules, and that variants induce a hierarchy for such update rules with respect to the arity of the maintained auxiliary relations. Towards maintaining the query with full first-order update rules, it is shown that degree-restricted variants can be maintained

Dynamic Graph Queries

Graph databases in many applications - semantic web, transport or biological networks among others - are not only large, but also frequently modified. Evaluating graph queries in this dynamic context is a challenging task, as those queries often combine first-order and navigational features. Motivated by recent results on maintaining dynamic reachability, we study the dynamic evaluation of traditional query languages for graphs in the descriptive complexity framework. Our focus is on maintaining regular path queries, and extensions thereof, by first-order formulas. In particular we are interested in path queries defined by non-regular languages and in extended conjunctive regular path queries (which allow to compare labels of paths based on word relations). Further we study the closely related problems of maintaining distances in graphs and reachability in product graphs. In this preliminary study we obtain upper bounds for those problems in restricted settings, such as undirected and acyclic graphs, or under insertions only, and negative results regarding quantifier-free update formulas. In addition we point out interesting directions for further research

Static Analysis for Logic-based Dynamic Programs

The goal of dynamic programs as introduced by Patnaik and Immerman (1994) is to maintain the result of a fixed query for an input database which is subject to tuple insertions and deletions. To this end such programs store an auxiliary database whose relations are updated via first-order formulas upon modifications of the input database. One of those auxiliary relations is supposed to store the answer to the query. Several static analysis problems can be associated to such dynamic programs. Is the answer relation of a given dynamic program always empty? Does a program actually maintain a query? That is, is the answer given of the program the same when an input database was reached by two different modification sequences? Even more, is the content of auxiliary relations independent of the modification sequence that lead to an input database? We study the algorithmic properties of those and similar static analysis problems. Since all these problems can easily be seen to be undecidable for full first-order programs, we examine the exact borderline for decidability for restricted programs. Our focus is on restricting the arity of the input databases as well as the auxiliary databases, and to restrict the use of quantifiers

Dynamic Complexity of Regular Languages: Big Changes, Small Work

Whether a changing string is member of a certain regular language can be maintained in the DynFO framework of Patnaik and Immerman: after changing the symbol at one position of the string, a first-order update formula can express - using additionally stored information - whether the resulting string is in the regular language. We extend this and further known results by considering changes of many positions at once. We also investigate to which degree the obtained update formulas imply work-efficient parallel dynamic algorithms

Givens QR Decomposition over Relational Databases

This paper introduces Figaro, an algorithm for computing the upper-triangular matrix in the QR decomposition of the matrix defined by the natural join over a relational database. The QR decomposition lies at the core of many linear algebra techniques and their machine learning applications, including: the matrix inverse; the least squares; the singular value decomposition; eigenvalue problems; and the principal component analysis. Figaro's main novelty is that it pushes the QR decomposition past the join. This leads to several desirable properties. For acyclic joins, it takes time linear in the database size and independent of the join size. Its execution is equivalent to the application of a sequence of Givens rotations proportional to the join size. Its number of rounding errors relative to the classical QR decomposition algorithms is on par with the input size relative to the join size. In experiments with real-world and synthetic databases, Figaro outperforms both in runtime performance and accuracy the LAPACK libraries openblas and Intel MKL by a factor proportional to the gap between the join output and input sizes

Dynamic Complexity under Definable Changes

This paper studies dynamic complexity under definable change operations in the DynFO framework by Patnaik and Immerman. It is shown that for changes definable by parameter-free first-order formulas, all (uniform) AC1 queries can be maintained by first-order dynamic programs. Furthermore, many maintenance results for single-tuple changes are extended to more powerful change operations: (1) The reachability query for undirected graphs is first-order maintainable under single tuple changes and first-order defined insertions, likewise the reachability query for directed acyclic graphs under quantifier-free insertions. (2) Context-free languages are first-order maintainable under EFO-defined changes. These results are complemented by several inexpressibility results, for example, that the reachability query cannot be maintained by quantifier-free programs under definable, quantifier-free deletions

A Strategy for Dynamic Programs: Start over and Muddle through

In the setting of DynFO, dynamic programs update the stored result of a query whenever the underlying data changes. This update is expressed in terms of first-order logic. We introduce a strategy for constructing dynamic programs that utilises periodic computation of auxiliary data from scratch and the ability to maintain a query for a limited number of change steps. We show that if some program can maintain a query for log n change steps after an AC$^1$-computable initialisation, it can be maintained by a first-order dynamic program as well, i.e., in DynFO. As an application, it is shown that decision and optimisation problems defined by monadic second-order (MSO) formulas are in DynFO, if only change sequences that produce graphs of bounded treewidth are allowed. To establish this result, a Feferman-Vaught-type composition theorem for MSO is established that might be useful in its own right

Givens rotations for QR decomposition, SVD and PCA over database joins

This article introduces FiGaRo, an algorithm for computing the upper-triangular matrix in the QR decomposition of the matrix defined by the natural join over relational data. FiGaRo ’s main novelty is that it pushes the QR decomposition past the join. This leads to several desirable properties. For acyclic joins, it takes time linear in the database size and independent of the join size. Its execution is equivalent to the application of a sequence of Givens rotations proportional to the join size. Its number of rounding errors relative to the classical QR decomposition algorithms is on par with the database size relative to the join output size. The QR decomposition lies at the core of many linear algebra computations including the singular value decomposition (SVD) and the principal component analysis (PCA). We show how FiGaRo can be used to compute the orthogonal matrix in the QR decomposition, the SVD and the PCA of the join output without the need to materialize the join output. A suite of experiments validate that FiGaRo can outperform both in runtime performance and numerical accuracy the LAPACK library Intel MKL by a factor proportional to the gap between the sizes of the join output and input

Dynamic Complexity Meets Parameterised Algorithms

Dynamic Complexity studies the maintainability of queries with logical formulas in a setting where the underlying structure or database changes over time. Most often, these formulas are from first-order logic, giving rise to the dynamic complexity class DynFO. This paper investigates extensions of DynFO in the spirit of parameterised algorithms. In this setting structures come with a parameter k and the extensions allow additional "space" of size f(k) (in the form of an additional structure of this size) or additional time f(k) (in the form of iterations of formulas) or both. The resulting classes are compared with their non-dynamic counterparts and other classes. The main part of the paper explores the applicability of methods for parameterised algorithms to this setting through case studies for various well-known parameterised problems