Checking integrity constraints - how it differs in centralized, distributed and parallel databases

An important aim of a database system is to guarantee database consistency, which means that the data contained in a database is both accurate and valid. Integrity constraints represent knowledge about data with which a database must be consistent. The process of checking constraints to ensure that update operations or transactions which alter the database will preserve its consistency has proved to be extremely difficult to implement, particularly in distributed and parallel databases. In distributed databases the aim of the constraint checking is to reduce the amount of data needing to be accessed, the number of sites involved and the amount of data transferred across the network. In parallel databases the focus is on the total execution time taken in checking the constraints. This paper highlights the differences between centralized, distributed and parallel databases with respect to constraint checking

A database management capability for Ada

The data requirements of mission critical defense systems have been increasing dramatically. Command and control, intelligence, logistics, and even weapons systems are being required to integrate, process, and share ever increasing volumes of information. To meet this need, systems are now being specified that incorporate data base management subsystems for handling storage and retrieval of information. It is expected that a large number of the next generation of mission critical systems will contain embedded data base management systems. Since the use of Ada has been mandated for most of these systems, it is important to address the issues of providing data base management capabilities that can be closely coupled with Ada. A comprehensive distributed data base management project has been investigated. The key deliverables of this project are three closely related prototype systems implemented in Ada. These three systems are discussed

Inconsistency-tolerant business rules in distributed information systems

The final publication is available at Springer via http://10.1007/978-3-642-41033-8_41Business rules enhance the integrity of information systems. However, their maintenance does not scale up easily to distributed systems with concurrent transactions. To a large extent, that is due to two problematic exigencies: the postulates of total and isolated business rule satisfaction. For overcoming these problems, we outline a measure-based inconsistency-tolerant approach to business rules maintenance.Supported by ERDF/FEDER and MEC grants TIN2009-14460-C03, TIN2010-17139, TIN2012-37719-C03-01.Decker, H.; Muñoz Escoí, FD. (2013). Inconsistency-tolerant business rules in distributed information systems. En On the Move to Meaningful Internet Systems: OTM 2013 Workshops. Springer Verlag (Germany). 8186:322-331. https://doi.org/10.1007/978-3-642-41033-8_41S3223318186Abiteboul, S., Hull, R., Vianu, V.: Foundations of Databases. 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Springer, Heidelberg (2011)Decker, H.: New measures for maintaining the quality of databases. In: Murgante, B., Gervasi, O., Misra, S., Nedjah, N., Rocha, A.M.A.C., Taniar, D., Apduhan, B.O. (eds.) ICCSA 2012, Part IV. LNCS, vol. 7336, pp. 170–185. Springer, Heidelberg (2012)Decker, H.: Controlling the Consistency of the Evolution of Database Systems. In: Proc. 24th ICSSEA, Paris (2012)Decker, H., Martinenghi, D.: Inconsistency-tolerant Integrity Checking. IEEE Transactions on Knowledge and Data Engineering 23(2), 218–234 (2011)Decker, H., Muñoz-Escoí, F.D.: Revisiting and Improving a Result on Integrity Preservation by Concurrent Transactions. In: Meersman, R., Dillon, T., Herrero, P. (eds.) OTM 2010 Workshops. LNCS, vol. 6428, pp. 297–306. Springer, Heidelberg (2010)Eswaran, K., Gray, J., Lorie, R., Traiger, I.: The Notions of Consistency and Predicate Locks in a Database System. CACM 19(11), 624–633 (1976)Gilbert, S., Lynch, N.: Brewer’s Conjecture and the feasibility of Consistent, Available, Partition-tolerant Web Services. ACM SIGACT News 33(2), 51–59 (2002)Ibrahim, H.: Checking Integrity Constraints - How it Differs in Centralized, Distributed and Parallel Databases. In: Proc. 17th DEXA Workshops, pp. 563–568. IEEE (2006)Lynch, N., Blaustein, B., Siegel, M.: Correctness Conditions for Highly Available Replicated Databases. In: Proc. 5th PODC, pp. 11–28. ACM Press (1986)Martinenghi, D., Christiansen, H.: Transaction Management with Integrity Checking. In: Andersen, K.V., Debenham, J., Wagner, R. (eds.) DEXA 2005. LNCS, vol. 3588, pp. 606–615. Springer, Heidelberg (2005)Christiansen, H., Decker, H.: Integrity checking and maintenance in relational and deductive databases and beyond. In: Ma, Z. (ed.) Intelligent Databases: Technologies and Applications, pp. 238–285. Idea Group (2006)Morgan, T.: Business Rules and Information Systems - Aligning IT with Business Goals. Addison-Wesley (2002)Muñoz-Escoí, F.D., Ruiz-Fuertes, M.I., Decker, H., Armendáriz-Íñigo, J.E., de Mendívil, J.R.G.: Extending Middleware Protocols for Database Replication with Integrity Support. In: Meersman, R., Tari, Z. (eds.) OTM 2008, Part I. LNCS, vol. 5331, pp. 607–624. Springer, Heidelberg (2008)Nicolas, J.-M.: Logic for improving integrity checking in relational data bases. Acta Informatica 18, 227–253 (1982)Novakovic, I., Deletic, V.: Structuring of Business Rules in Information System Design and Architecture. Facta Universitatis Nis, Ser. Elec. Energ. 22(3), 305–312 (2009)Pipino, L., Lee, Y., Yang, R.: Data Quality Assessment. CACM 45(4), 211–218 (2002)Stonebraker, M.: Errors in Database Systems, Eventual Consistency, and the CAP Theorem (2010), http://cacm.acm.org/blog/blog-cacm/83396-errors-in-database-systems-eventual-consistency-and-the-cap-theoremStonebraker, M.: In search of database consistency. CACM 53(10), 8–9 (2010)Stonebraker, M.: Technical perspective - One size fits all: an idea whose time has come and gone. Commun. ACM 51(12), 76 (2008)Taveter, K.: Business Rules’ Approach to the Modelling, Design and Implementation of Agent-Oriented Information Systems. In: Proc. CAiSE workshop AOIS, Heidelberg (1999)Vidyasankar, K.: Serializability. In: Liu, L., Özu, T. (eds.) Encyclopedia of Database Systems, pp. 2626–2632. Springer (2009)Weikum, G., Vossen, G.: Transactional Information Systems. Morgan Kaufmann (2002)Vogels, W.: Eventually Consistent. ACM Queue 6(6), 14–19 (2008)Pereira Ziwich, P., Procpio Duarte, E., Pessoa Albini, L.: Distributed Integrity Checking for Systems with Replicated Data. In: Proc. ICPADS, vol. 1, pp. 363–369. IEEE CSP (2005

State-of-the-art on evolution and reactivity

This report starts by, in Chapter 1, outlining aspects of querying and updating resources on the Web and on the Semantic Web, including the development of query and update languages to be carried out within the Rewerse project. From this outline, it becomes clear that several existing research areas and topics are of interest for this work in Rewerse. In the remainder of this report we further present state of the art surveys in a selection of such areas and topics. More precisely: in Chapter 2 we give an overview of logics for reasoning about state change and updates; Chapter 3 is devoted to briefly describing existing update languages for the Web, and also for updating logic programs; in Chapter 4 event-condition-action rules, both in the context of active database systems and in the context of semistructured data, are surveyed; in Chapter 5 we give an overview of some relevant rule-based agents frameworks

Global Semantic Integrity Constraint Checking for a System of Databases

In today’s emerging information systems, it is natural to have data distributed across multiple sites. We define a System of Databases (SyDb) as a collection of autonomous and heterogeneous databases. R-SyDb (System of Relational Databases) is a restricted form of SyDb, referring to a collection of relational databases, which are independent. Similarly, X-SyDb (System of XML Databases) refers to a collection of XML databases. Global integrity constraints ensure integrity and consistency of data spanning multiple databases. In this dissertation, we present (i) Constraint Checker, a general framework of a mobile agent based approach for checking global constraints on R-SyDb, and (ii) XConstraint Checker, a general framework for checking global XML constraints on X-SyDb. Furthermore, we formalize multiple efficient algorithms for varying semantic integrity constraints involving both arithmetic and aggregate predicates. The algorithms take as input an update statement, list of all global semantic integrity constraints with arithmetic predicates or aggregate predicates and outputs sub-constraints to be executed on remote sites. The algorithms are efficient since (i) constraint check is carried out at compile time, i.e. before executing update statement; hence we save time and resources by avoiding rollbacks, and (ii) the implementation exploits parallelism. We have also implemented a prototype of systems and algorithms for both R-SyDb and X-SyDb. We also present performance evaluations of the system

Consistency in a Partitioned Network: A Survey

Recently, several strategies for transaction processing in partitioned distributed database systems with replicated data have been proposed. We survey these strategies in light of the competing goals of maintaining correctness and achieving high availability. Extensions and combinations are then discussed, and guidelines for the selection of a strategy for a particular application are presented

Distributed databases

Mòdul 3 del llibre Database Architecture. UOC, 20122022/202