An Inflationary Fixed Point Operator in XQuery

We introduce a controlled form of recursion in XQuery, inflationary fixed points, familiar in the context of relational databases. This imposes restrictions on the expressible types of recursion, but we show that inflationary fixed points nevertheless are sufficiently versatile to capture a wide range of interesting use cases, including the semantics of Regular XPath and its core transitive closure construct. While the optimization of general user-defined recursive functions in XQuery appears elusive, we will describe how inflationary fixed points can be efficiently evaluated, provided that the recursive XQuery expressions exhibit a distributivity property. We show how distributivity can be assessed both, syntactically and algebraically, and provide experimental evidence that XQuery processors can substantially benefit during inflationary fixed point evaluation.Comment: 11 pages, 10 figures, 2 table

Implementation and Performance Evaluation of a Parallel Transitive Closure Algorithms on PRISMA/DB

This paper is one of the first to discuss actual implementation of and experimentation with parallel transitive closure operations on a full-fledged relational database system. It brings two research efforts together; the development of an efficient execution strategy for parallel computation of path problems, called Disconnection Set Approach, and the development and implementation of a parallel, main-memory DBMS, called PRISMA/DB. First, we report on the implementation of the disconnection set approach on PRISMA/DB, showing how the latter's design allowed us to easily extend the functionality of the system. Second, we investigate the disconnection set approach's parallel behavior and performance by means of extensive experimentation. It is shown that the parallel implementation of the disconnection set approach yields very good performance characteristics, and that (super)linear speedup w.r.t. a special implementation of semi-naive is achieved for regular, so-called linear fragmenta..

A survey of parallel execution strategies for transitive closure and logic programs

An important feature of database technology of the nineties is the use of parallelism for speeding up the execution of complex queries. This technology is being tested in several experimental database architectures and a few commercial systems for conventional select-project-join queries. In particular, hash-based fragmentation is used to distribute data to disks under the control of different processors in order to perform selections and joins in parallel. With the development of new query languages, and in particular with the definition of transitive closure queries and of more general logic programming queries, the new dimension of recursion has been added to query processing. Recursive queries are complex; at the same time, their regular structure is particularly suited for parallel execution, and parallelism may give a high efficiency gain. We survey the approaches to parallel execution of recursive queries that have been presented in the recent literature. We observe that research on parallel execution of recursive queries is separated into two distinct subareas, one focused on the transitive closure of Relational Algebra expressions, the other one focused on optimization of more general Datalog queries. Though the subareas seem radically different because of the approach and formalism used, they have many common features. This is not surprising, because most typical Datalog queries can be solved by means of the transitive closure of simple algebraic expressions. We first analyze the relationship between the transitive closure of expressions in Relational Algebra and Datalog programs. We then review sequential methods for evaluating transitive closure, distinguishing iterative and direct methods. We address the parallelization of these methods, by discussing various forms of parallelization. Data fragmentation plays an important role in obtaining parallel execution; we describe hash-based and semantic fragmentation. Finally, we consider Datalog queries, and present general methods for parallel rule execution; we recognize the similarities between these methods and the methods reviewed previously, when the former are applied to linear Datalog queries. We also provide a quantitative analysis that shows the impact of the initial data distribution on the performance of methods

Matching Dependencies with Arbitrary Attribute Values: Semantics, Query Answering and Integrity Constraints

Matching dependencies (MDs) were introduced to specify the identification or matching of certain attribute values in pairs of database tuples when some similarity conditions are satisfied. Their enforcement can be seen as a natural generalization of entity resolution. In what we call the "pure case" of MDs, any value from the underlying data domain can be used for the value in common that does the matching. We investigate the semantics and properties of data cleaning through the enforcement of matching dependencies for the pure case. We characterize the intended clean instances and also the "clean answers" to queries as those that are invariant under the cleaning process. The complexity of computing clean instances and clean answers to queries is investigated. Tractable and intractable cases depending on the MDs and queries are identified. Finally, we establish connections with database "repairs" under integrity constraints.Comment: 13 pages, double column, 2 figure

Hyperset Approach to Semi-structured Databases and the Experimental Implementation of the Query Language Delta

This thesis presents practical suggestions towards the implementation of the hyperset approach to semi-structured databases and the associated query language Delta. This work can be characterised as part of a top-down approach to semi-structured databases, from theory to practice. The main original part of this work consisted in implementation of the hyperset Delta query language to semi-structured databases, including worked example queries. In fact, the goal was to demonstrate the practical details of this approach and language. The required development of an extended, practical version of the language based on the existing theoretical version, and the corresponding operational semantics. Here we present detailed description of the most essential steps of the implementation. Another crucial problem for this approach was to demonstrate how to deal in reality with the concept of the equality relation between (hyper)sets, which is computationally realised by the bisimulation relation. In fact, this expensive procedure, especially in the case of distributed semi-structured data, required some additional theoretical considerations and practical suggestions for efficient implementation. To this end the 'local/global' strategy for computing the bisimulation relation over distributed semi-structured data was developed and its efficiency was experimentally confirmed.Comment: Technical Report (PhD thesis), University of Liverpool, Englan

R-SQL: An SQL Database System with Extended Recursion

The relational database language SQL:1999 standard supports recursion, but thisapproach is limited to the linear case. Moreover, mutual recursion is not supported,and negation cannot be combined with recursion. We designed the language R-SQLto overcome these limitations in [ANSS13], improving termination properties in re-cursive definitions. In addition we developed a proof of concept implementation ofan R-SQL system. In this paper we describe in detail an improved system enhanc-ing performance. It can be integrated into existing RDBMS’s, extending them withthe aforementioned benefits of R-SQL. The system processes an R-SQL databasedefinition obtaining its extension in tables of an RDBMS (such as PostgreSQL andDB2). It is implemented in SWI-Prolog and it produces a Python script that, uponexecution, computes the result of the R-SQL relations. We provide some perfor-mance results showing the efficiency gains w.r.t. the previous version. We alsoinclude a comparative analysis including some representative relational a deductive systems

R-SQL: An SQL Database System with Extended Recursion

The relational database language SQL:1999 standard supports recursion, but this approach is limited to the linear case. Moreover, mutual recursion is not supported, and negation cannot be combined with recursion. We designed the language R-SQL to overcome these limitations, improving termination properties in recursive definitions. In addition we developed a proof of concept implementation of an R-SQL system. In this paper we describe in detail an improved system enhancing performance. It can be integrated into existing RDBMS's, extending them with the  aforementioned benefits of R-SQL. The system processes an R-SQL database definition obtaining its extension in tables of an RDBMS (such as PostgreSQL and DB2). It is implemented in SWI-Prolog and it produces a Python script that, upon execution, computes the result of the R-SQL relations. We provide some performance results showing the efficiency gains w.r.t. the previous version. We also include a comparative analysis including some representative relational a deductive systems