Abstract not available

Semantic query optimization is an important issue in many contexts of databases including information integration, view maintenance and data warehousing and can substantially improve performance, especially in today's database systems which contain gigabytes of data. A crucial issue in semantic query optimization is query containment. Several papers have dealt with the problem of conjunctive query containment. In particular, some of the literature admits SQL like query languages with aggregate operations such as sum/count. Moreover, since real SQL requires a richer semantics than set semantics, there has been work on bag-semantics for SQL, essentially by introducing an interpreted column. One important technique for reasoning about query containment in the context of bag semantics is to translate the queries to alternatives using aggregate functions and assuming set semantics. Furthermore, in SQL, order by is the operator by which the results are sorted based on certain attributes and, clearly, ordering is an important issue in query optimization. As such, there has been work done in support of ordering based on the application of the domain. However, a final step is required in order to introduce a rich semantics in support. In this work, we integrate set and bag semantics to be able to reason about real SQL queries. We demonstrate an ordered bag semantics for SQL using a relational algebra with aggregates. We define a set algebra with various expressions of interest, then define syntax and semantics for bag algebra, and finally extend these definitions to ordered bags. This is done by adding a pair of additional interpreted columns to computed relations in which the first column is used in the standard fashion to capture duplicate tuples in query results, and the second adds an ordering priority to the output. We show that the relational algebra with aggregates can be used to compute these interpreted columns with sufficient flexibility to work as a semantics for standard SQL queries, which are allowed to include order by and duplicate preserving select clauses. The reduction of a workable ordered bag semantics for SQL to the relational algebra with aggregates - as we have developed it - can enable existing query containment theory to be applied in practical query containment.

Semantic query optimization is an important issue in many contexts of databases including information integration, view maintenance and data warehousing and can substantially improve performance, especially in today's database systems which contain gigabytes of data. A crucial issue in semantic query optimization is query containment. Several papers have dealt with the problem of conjunctive query containment. In particular, some of the literature admits SQL like query languages with aggregate operations such as sum/count. Moreover, since real SQL requires a richer semantics than set semantics, there has been work on bag-semantics for SQL, essentially by introducing an interpreted column. One important technique for reasoning about query containment in the context of bag semantics is to translate the queries to alternatives using aggregate functions and assuming set semantics. Furthermore, in SQL, order by is the operator by which the results are sorted based on certain attributes and, clearly, ordering is an important issue in query optimization. As such, there has been work done in support of ordering based on the application of the domain. However, a final step is required in order to introduce a rich semantics in support. In this work, we integrate set and bag semantics to be able to reason about real SQL queries. We demonstrate an ordered bag semantics for SQL using a relational algebra with aggregates. We define a set algebra with various expressions of interest, then define syntax and semantics for bag algebra, and finally extend these definitions to ordered bags. This is done by adding a pair of additional interpreted columns to computed relations in which the first column is used in the standard fashion to capture duplicate tuples in query results, and the second adds an ordering priority to the output. We show that the relational algebra with aggregates can be used to compute these interpreted columns with sufficient flexibility to work as a semantics for standard SQL queries, which are allowed to include order by and duplicate preserving select clauses. The reduction of a workable ordered bag semantics for SQL to the relational algebra with aggregates - as we have developed it - can enable existing query containment theory to be applied in practical query containment.

The Resource Description Framework (RDF) is the logical data model of the Semantic Web. RDF encodes information as a directed graph using a set of labeled edges known formally as resource-property-value statements or, in common usage, as RDF triples or simply triples. Values recorded in RDF triple form are either Universal Resource Identifiers (URIs) or literals. The use of URIs allows links between distributed data sources, which enables a logical model of data as a graph spanning the Internet. SPARQL is a standard SQL-like query language on RDF triples. This report describes the translation of SPARQL queries to equivalent SQL queries operating on a relational representation of RDF triples, and the physical optimization of that representation using the IBM DB2 relational database management system. Performance was evaluated using the Berlin SPARQL Benchmark. The results show that the implementation can perform well on certain queries, but more work is required to improved overall performance and scalability. / text

abstract / toc / Computer Science and Information Systems / Doctoral / Doctor of Philosophy

The primary goal of this dissertation is to present an outline of the culture history of the site of La Milpa and its immediate sustaining area through the elaboration and elucidation of a ceramic chronology and typology. However, an equally important aspect of this dissertation is a thorough critique of the type-variety/mode (T-V) system of classification upon which Maya ceramic analysis has been based over the last forty years. The analysis presented here was completed using a relational database (Microsoft Access). By using this database program, it became clear that it is necessary to rethink the basis and use of the type-variety system and how (or whether) it can be adapted as a tool for use in database driven analysis.

Žilvino Brobliausko magistro studijų baigiamajame darbe atliekamas daugiašalio reliacinių duomenų bazių saugumo modelio teorinis tyrimas: suformuluojami pagrindiniai reikalavimai, keliami tokio tipo modeliui; pasiūlomas modelis, leidžiantis vykdyti paiešką ir taikyti sumos, bei vidurkio agregatines funkcijas neiššifruojant skaitinių duomenų RDBVS pusėje; nurodomi pateikto modelio privalumai ir trūkumai. Pateikiama demonstracinė programa, realizuojanti pasiūlytą modelį. / The multilateral security model of relational databases is analyzed in master thesis of Žilvinas Brobliauskas. The results of research includes: the formulated requirements for multilateral security model of relational databases, proposed model, which allows range queries and aggregation functions over encrypted data without decrypting them at RDBMS level, and determined advantages and disadvantages of it. The program which realizes proposed model is given as proof of concept.

The relational model has dominated the database field because of its reduced application development time and non-procedural data manipulation features. It has significant problems, however, including weak integrity constraints. This paper discusses the need for object oriented techniques to improve on these flaws. Three existing DBMS will be discussed: IRIS, ORION, and OZ. / Department of Computer Science

The purpose of this study is to explore that mathematics provides a convenient formalism for studying classical database management system problems. There are two main parts in this study, devoted respectively to using mathematical theory of relations and using logical theory to study database management systems. In the first part we focus on relational model and relational algebra. The second part deals with the application of mathematical logic to database management systems, where logic may be used both as a inference system and as a representation language. The features and logical mechanisms of Prolog programming language have been studied. A sample logical database model is developed and tested, using the logic programming language Prolog. / Department of Computer Science

In this study, the inability to in a future meet the electricity demand and the urge to change the consumption behavior considered. In a smart grid context there are several possible ways to do this. Means include ways to increase the consumer’s awareness, add energy storages or build smarter homes which can control the appliances. To be able to implement these, indications on how the future consumption will be could be useful. Therefore we look further into how a framework for short-term consumption predictions can be created using electricity consumption data in relation to external factors. To do this a literature study is made to see what kind of methods that are relevant and which qualities is interesting to look at in order to choose a good prediction method. Case Based Reasoning seemed to be able to be suitable method. This method was examined further and built using relational databases. After this the method was tested and evaluated using datasets and evaluation methods CV, MBE and MAPE, which have previously been used in the domain of consumption prediction. The result was compared to the results of the winning methods in the ASHRAE competition. The CBR method was expected to perform better than what it did, and still not as good as the winning methods from the ASHRAE competition. The result showed that the CBR method can be used as a predictor and has potential to make good energy consumption predictions. and there is room for improvement in future studies.