2,212 research outputs found
Query processing of geometric objects with free form boundarie sin spatial databases
The increasing demand for the use of database systems as an integrating
factor in CAD/CAM applications has necessitated the development of database
systems with appropriate modelling and retrieval capabilities. One essential
problem is the treatment of geometric data which has led to the development of
spatial databases. Unfortunately, most proposals only deal with simple geometric
objects like multidimensional points and rectangles. On the other hand, there has
been a rapid development in the field of representing geometric objects with free
form curves or surfaces, initiated by engineering applications such as mechanical
engineering, aviation or astronautics. Therefore, we propose a concept for the realization
of spatial retrieval operations on geometric objects with free form
boundaries, such as B-spline or Bezier curves, which can easily be integrated in
a database management system. The key concept is the encapsulation of geometric
operations in a so-called query processor. First, this enables the definition of
an interface allowing the integration into the data model and the definition of the
query language of a database system for complex objects. Second, the approach
allows the use of an arbitrary representation of the geometric objects. After a
short description of the query processor, we propose some representations for free
form objects determined by B-spline or Bezier curves. The goal of efficient query
processing in a database environment is achieved using a combination of decomposition
techniques and spatial access methods. Finally, we present some experimental
results indicating that the performance of decomposition techniques is
clearly superior to traditional query processing strategies for geometric objects
with free form boundaries
Database Systems - Present and Future
The database systems have nowadays an increasingly important role in the knowledge-based society, in which computers have penetrated all fields of activity and the Internet tends to develop worldwide. In the current informatics context, the development of the applications with databases is the work of the specialists. Using databases, reach a database from various applications, and also some of related concepts, have become accessible to all categories of IT users. This paper aims to summarize the curricular area regarding the fundamental database systems issues, which are necessary in order to train specialists in economic informatics higher education. The database systems integrate and interfere with several informatics technologies and therefore are more difficult to understand and use. Thus, students should know already a set of minimum, mandatory concepts and their practical implementation: computer systems, programming techniques, programming languages, data structures. The article also presents the actual trends in the evolution of the database systems, in the context of economic informatics.database systems - DBS, database management systems â DBMS, database â DB, programming languages, data models, database design, relational database, object-oriented systems, distributed systems, advanced database systems
A Survey on Array Storage, Query Languages, and Systems
Since scientific investigation is one of the most important providers of
massive amounts of ordered data, there is a renewed interest in array data
processing in the context of Big Data. To the best of our knowledge, a unified
resource that summarizes and analyzes array processing research over its long
existence is currently missing. In this survey, we provide a guide for past,
present, and future research in array processing. The survey is organized along
three main topics. Array storage discusses all the aspects related to array
partitioning into chunks. The identification of a reduced set of array
operators to form the foundation for an array query language is analyzed across
multiple such proposals. Lastly, we survey real systems for array processing.
The result is a thorough survey on array data storage and processing that
should be consulted by anyone interested in this research topic, independent of
experience level. The survey is not complete though. We greatly appreciate
pointers towards any work we might have forgotten to mention.Comment: 44 page
A query processing system for very large spatial databases using a new map algebra
Dans cette thĂšse nous introduisons une approche de traitement de requĂȘtes pour des bases de donnĂ©e spatiales. Nous expliquons aussi les concepts principaux que nous avons dĂ©fini et dĂ©veloppĂ©: une algĂšbre spatiale et une approche Ă base de graphe utilisĂ©e dans l'optimisateur. L'algĂšbre spatiale est dĂ©fini pour exprimer les requĂȘtes et les rĂšgles de transformation pendant les diffĂ©rentes Ă©tapes de l'optimisation de requĂȘtes. Nous avons essayĂ© de dĂ©finir l'algĂšbre la plus complĂšte que possible pour couvrir une grande variĂ©tĂ© d'application. L'opĂ©rateur algĂ©brique reçoit et produit seulement des carte. Les fonctions reçoivent des cartes et produisent des scalaires ou des objets. L'optimisateur reçoit la requĂȘte en expression algĂ©brique et produit un QEP (Query Evaluation Plan) efficace dans deux Ă©tapes: gĂ©nĂ©ration de QEG (Query Evaluation Graph) et gĂ©nĂ©ration de QEP. Dans premiĂšre Ă©tape un graphe (QEG) Ă©quivalent de l'expression algĂ©brique est produit. Les rĂšgles de transformation sont utilisĂ©es pour transformer le graphe a un Ă©quivalent plus efficace. Dans deuxiĂšme Ă©tape un QEP est produit de QEG passĂ© de l'Ă©tape prĂ©cĂ©dente. Le QEP est un ensemble des opĂ©rations primitives consĂ©cutives qui produit les rĂ©sultats finals (la rĂ©ponse finale de la requĂȘte soumise au base de donnĂ©e). Nous avons implĂ©mentĂ© l'optimisateur, un gĂ©nĂ©rateur de requĂȘte spatiale alĂ©atoire, et une base de donnĂ©e simulĂ©e. La base de donnĂ©e spatiale simulĂ©e est un ensemble de fonctions pour simuler des opĂ©rations spatiales primitives. Les requĂȘtes alĂ©atoires sont soumis Ă l'optimisateur. Les QEPs gĂ©nĂ©rĂ©es sont soumis au simulateur de base de donnĂ©es spatiale. Les rĂ©sultats expĂ©rimentaux sont utilisĂ©s pour discuter les performances et les caractĂ©ristiques de l'optimisateur.Abstract: In this thesis we introduce a query processing approach for spatial databases and explain the main concepts we defined and developed: a spatial algebra and a graph based approach used in the optimizer. The spatial algebra was defined to express queries and transformation rules during different steps of the query optimization. To cover a vast variety of potential applications, we tried to define the algebra as complete as possible. The algebra looks at the spatial data as maps of spatial objects. The algebraic operators act on the maps and result in new maps. Aggregate functions can act on maps and objects and produce objects or basic values (characters, numbers, etc.). The optimizer receives the query in algebraic expression and produces one efficient QEP (Query Evaluation Plan) through two main consecutive blocks: QEG (Query Evaluation Graph) generation and QEP generation. In QEG generation we construct a graph equivalent of the algebraic expression and then apply graph transformation rules to produce one efficient QEG. In QEP generation we receive the efficient QEG and do predicate ordering and approximation and then generate the efficient QEP. The QEP is a set of consecutive phases that must be executed in the specified order. Each phase consist of one or more primitive operations. All primitive operations that are in the same phase can be executed in parallel. We implemented the optimizer, a randomly spatial query generator and a simulated spatial database. The query generator produces random queries for the purpose of testing the optimizer. The simulated spatial database is a set of functions to simulate primitive spatial operations. They return the cost of the corresponding primitive operation according to input parameters. We put randomly generated queries to the optimizer, got the generated QEPs and put them to the spatial database simulator. We used the experimental results to discuss on the optimizer characteristics and performance. The optimizer was designed for databases with a very large number of spatial objects nevertheless most of the concepts we used can be applied to all spatial information systems."--RĂ©sumĂ© abrĂ©gĂ© par UMI
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