Maintaining temporal consistency of discrete objects in soft real-time database systems

A real-time database system contains base data items which record and model a physical, real-world environment. For better decision support, base data items are summarized and correlated to derive views. These base data and views are accessed by application transactions to generate the ultimate actions taken by the system. As the environment changes, updates are applied to base data, which subsequently trigger view recomputations. There are thus three types of activities: Base data update, view recomputation, and transaction execution. In a real-time database system, two timing constraints need to be enforced. We require that transactions meet their deadlines (transaction timeliness) and read fresh data (data timeliness). In this paper, we define the concept of absolute and relative temporal consistency from the perspective of transactions for discrete data objects. We address the important issue of transaction scheduling among the three types of activities such that the two timing requirements can be met. We also discuss how a real-time database system should be designed to enforce different levels of temporal consistency.published_or_final_versio

Temporal and Contextual Dependencies in Relational Data Modeling

Although a solid theoretical foundation of relational data modeling has existed for decades, critical reassessment from temporal requirements’ perspective reveals shortcomings in its integrity constraints. We identify the need for this work by discussing how existing relational databases fail to ensure correctness of data when the data to be stored is time sensitive. The analysis presented in this work becomes particularly important in present times where, because of relational databases’ inadequacy to cater to all the requirements, new forms of database systems such as temporal databases, active databases, real time databases, and NoSQL (non-relational) databases have been introduced. In relational databases, temporal requirements have been dealt with either at application level using scripts or through manual assistance, but no attempts have been made to address them at design level. These requirements are the ones that need changing metadata as the time progresses, which remains unsupported by Relational Database Management System (RDBMS) to date. Starting with shortcomings of data, entity, and referential integrity in relational data modeling, we propose a new form of integrity that works at a more detailed level of granularity. We also present several important concepts including temporal dependency, contextual dependency, and cell level integrity. We then introduce cellular-constraints to implement the proposed integrity and dependencies, and also how they can be incorporated into the relational data model to enable RDBMS to handle temporal requirements in future. Overall, we provide a formal description to address the temporal requirements’ problem in relational data model, and design a framework for solving this problem. We have supplemented our proposition using examples, experiments and results

Updates and View Maintenance in Soft Real-Time Database

A database system contains base data items which record and model a physical, real world environment. For better decision support, base data items are summarized and correlated to derive views. These base data and views are accessed by application transactions to generate the ultimate actions taken by the system. As the environmentchanges, updates are applied to the base data, which subsequently trigger view recomputations. There are thus three types of activities: base data update, view recomputation, and transaction execution

Updates and view maintenance in soft real-time database systems

A database system contains base data items which record and model a physical, real world environment. For better decision support, base data items are summarized and correlated to derive views. These base data and views are accessed by application transactions to generate the ultimate actions taken by the system. As the environment changes, updates are applied to the base data, which subsequently trigger view recomputations. There are thus three types of activities: base data update, view recomputation, and transaction execution. In a real-time system, two timing constraints need to be enforced. We require transactions meet their deadlines (transaction timeliness) and read fresh data (data timeliness). In this paper we define the concept of absolute and relative temporal consistency from the perspective of transactions. We address the important issue of transaction scheduling among the three types of activities such that the two timing requirements can be met. We also discuss how a real-time database system should be designed to enforce different levels of temporal consistency.link_to_subscribed_fulltex

Actualización y mantenimiento de vistas en bases de datos multidimensionales = Updates and view maintenance in multidimensional databases

Usually, OLAP(On Line Analytical Processing) systems provide data visualization through a multidimensional data model according to which a data fact is viewed as a mapping from a point in a space of dimensions into one or more spaces of measures. Moreover, dimensions are organized in levels which conform a hierarchy, providing a way of defining different levels of data aggregation, a central issue in data analysis. In a relational implementation of OLAP(usually called ROLAP), we can think of facts as being stored in fact tables, while each dimension is described in a dimension table. The industry solutions were built under the assumption that data in fact tables reflect the dynamic aspect of the data warehouse, while data in dimension tables represent static information. However, if we think of the data warehouse as a materialized view of data located in multiple sources, it is usual to find situations in which the structure of these sources changes, a new source is added, or an old one dropped. Any of these changes may require updates to the structure of some dimensions. Further, as multidimensional views are designed according to requirements from end users, a redefinition of the initial requirements may cause a dimension update. In this thesis we argue that accounting for dimension updates is necessary in an OLAP tool in order to avoid constantly rebuilding dimensions from scratch. Thus, we first characterize these updates and study the view maintenance problem when they occur. We developed algorithms which, taking advantage of the nature of the dimension updates, in some cases outperform well-known view maintenance algorithms. We then propose an extension to the MDX language(a standard query language for OLAP) and describe the implementation of TSOLAP, a multidimensional repository which supports dimension updates and view maintenance, developed following the OLE DB for OLAP standard. We discuss the experimental results of tests performed over a real-life case study, a medical center in Buenos Aires. In the second part of the thesis we embed our proposal in the temporal database framework, introducing the Temporal Multidimensional Data Model, and a temporal query language for OLAP which we called TOLAP. TOLAP allows expressing complex OLAP queries in an elegant and declarative fashion. We discuss issues like syntax, semantics, safety and expressive power. We also present an implementation including a graphic environment for temporal OLAP. Finally, we show how the temporal approach can be applied to the case study mentioned above.Fil:Vaisman, Alejandro Ariel. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina