Composition and Inversion of Schema Mappings

In the recent years, a lot of attention has been paid to the development of solid foundations for the composition and inversion of schema mappings. In this paper, we review the proposals for the semantics of these crucial operators. For each of these proposals, we concentrate on the three following problems: the definition of the semantics of the operator, the language needed to express the operator, and the algorithmic issues associated to the problem of computing the operator. It should be pointed out that we primarily consider the formalization of schema mappings introduced in the work on data exchange. In particular, when studying the problem of computing the composition and inverse of a schema mapping, we will be mostly interested in computing these operators for mappings specified by source-to-target tuple-generating dependencies

Algebraic rewritings for optimizing regular path queries

AbstractRewriting queries using views is a powerful technique that has applications in query optimization, data integration, data warehousing, etc. Query rewriting in relational databases is by now rather well investigated. However, in the framework of semistructured data the problem of rewriting has received much less attention. In this paper we focus on extracting as much information as possible from algebraic rewritings for the purpose of optimizing regular path queries. The cases when we can find a complete exact rewriting of a query using a set a views are very “ideal”. However, there is always information available in the views, even if this information is only partial. We introduce “lower” and “possibility” partial rewritings and provide algorithms for computing them. These rewritings are algebraic in their nature, i.e. we use only the algebraic view definitions for computing the rewritings. We do not use any pairs (tuples) of objects for computing the rewritings. This fact makes them a main memory product, which can be used for reducing secondary memory and remote access. After the main memory algebraic computation of the rewritings there is a second phase, with secondary memory access, for deriving the pairs of objects in the query answer. We give two algorithms for utilizing the partial lower and partial possibility rewritings to decrease the number of secondary memory accesses

The Internet of Things as a Privacy-Aware Database Machine

Instead of using a computer cluster with homogeneous nodes and very fast high bandwidth connections, we want to present the vision to use the Internet of Things (IoT) as a database machine. This is among others a key factor for smart (assistive) systems in apartments (AAL, ambient assisted living), offices (AAW, ambient assisted working), Smart Cities as well as factories (IIoT, Industry 4.0). It is important to massively distribute the calculation of analysis results on sensor nodes and other low-resource appliances in the environment, not only for reasons of performance, but also for reasons of privacy and protection of corporate knowledge. Thus, functions crucial for assistive systems, such as situation, activity, and intention recognition, are to be automatically transformed not only in database queries, but also in local nodes of lower performance. From a database-specific perspective, analysis operations on large quantities of distributed sensor data, currently based on classical big-data techniques and executed on large, homogeneously equipped parallel computers have to be automatically transformed to billions of processors with energy and capacity restrictions. In this visionary paper, we will focus on the database-specific perspective and the fundamental research questions in the underlying database theory

Ronciling Differences

In this paper we study a problem motivated by the management of changes in databases. It turns out that several such change scenarios, e.g., the separately studied problems of view maintenance (propagation of data changes) and view adaptation (propagation of view definition changes) can be unified as instances of query reformulation using views provided that support for the relational difference operator exists in the context of query reformulation. Exact query reformulation using views in positive relational languages is well understood, and has a variety of applications in query optimization and data sharing. Unfortunately, most questions about queries become undecidable in the presence of difference (or negation), whether we use the foundational set semantics or the more practical bag semantics. We present a new way of managing this difficulty by defining a novel semantics, Z- relations, where tuples are annotated with positive or negative integers. Z-relations conveniently represent data, insertions, and deletions in a uniform way, and can apply deletions with the union operator (deletions are tuples with negative counts). We show that under Z-semantics relational algebra (R A) queries have a normal form consisting of a single difference of positive queries, and this leads to the decidability of their equivalence.We provide a sound and complete algorithm for reformulating R A queries, including queries with difference, over Z-relations. Additionally, we show how to support standard view maintenanc