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Self-tuning of the relationships among rules' components in active databases systems

IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING 2004年第3期16卷 375-379页

作者： Botzer, D Etzion, O IBM Res Lab Haifa IL-31905 Haifa Israel

Active databases systems are systems that detect events and trigger actions as a result of this detection. Active capabilities are provided by a set of rules, such that each rule consists of three components (event, condition, and action). A major performance issue in active databases is the issue of relationships among rule components. Current implementations of triggers do not allow flexibility in the selection of transaction policies (partition of rules to transactions);the intertransaction timing policies of rules' components, the intratransaction policies of commit and abort dependencies, and synchronization issues. While these decisions have a substantial impact on the application performance, they are not provided as design primitives;one of the reasons for that is that it is very difficult to manually tune these decisions. In some research prototypes of active databases, these relationships are encapsulated into a set of coupling modes. Each coupling mode represents a combination of decisions about the partition of rule components to transactions, the relative timing within a transaction, and the interrelationships among these transactions. This paper describes a self-tuning model that operates on a general active database. The optimization model strives to minimize a programmable goal function that reflects the system designer's preferences and the system behavior and the applications' semantics through constraint definitions. The tuning model strives to optimize the mutual relationships among the system rules' components.

关键词： active databases advanced transaction models databases optimization tuning

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Comparative study of relational and graph databases 15

Comparative study of relational and graph databases

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IEEE 15th International Scientific Conference on Informatics (INFORMATICS)

作者： Lazarska, Malgorzata Siedlecka-Lamch, Olga Czestochowa Tech Univ Inst Comp & Informat Sci Czestochowa Poland

ISBN: (纸本)9781728131795

We live in a time of incredible technological development. In a fraction of a second, millions of information are generated and processed all over the world. The need to develop new models of databases is related to the dynamic and the amount of data stored. Using database schemes which are rigid and do not quickly adapt to changes occurring in the real world is ineffective and sometimes simply impossible. The solution of all these problems could be, among others, graph databases. In this talk, we present a detailed comparison of relational and graph databases, compiling the stages of design, implementation and testing. At each stage, we keep the same data in both databases, checking how easily they can be modelled in each logical model, then imported, and finally made queries and modifications on them.

关键词： graph databases database modelling databases optimization

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Simultaneous Approximation of Several Non-uniformly Distributed Values within Histogram Buckets 5

Simultaneous Approximation of Several Non-uniformly Distribu...

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5th International Conference on Data Management Technologies and Applications (DATA)

作者： Labbadi, Wissem Akaichi, Jalel Tunis Univ ISG Bouchoucha Bardo Tunisia King Khaled Univ Coll Comp Sci Abha Saudi Arabia

ISBN: (纸本)9789897581939

The problem of estimating median and other quantiles without storing observations was first proposed, in the field of simulation modeling to improve the studying of the performance of modeled systems rather than relying only on the mean and standard deviation alone. This problem is then extended to histogram plotting which raises the problem of estimating many quantiles of the same variable. However, the calculation of several values simultaneously is a computationally complex task since it requires several passes through the data. We propose in this paper an extension of the state-of-the-art Values Approximation algorithm (Labbadi and Akichi, 2014) to estimate simultaneously several values within a histogram bucket. The extended algorithm significantly reduces the computation of the estimation since the original algorithm estimates only a single value. The experimental results show that the extended algorithm provides good estimates especially when data have non-equal spreads.

关键词： databases optimization Data Quality Management Histograms Construction Simultaneous Estimation Non-uniform Distribution Quantiles Computation Estimation Error

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Comparative study of relational and graph databases

Comparative study of relational and graph databases

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IEEE International Scientific Conference on Informatics

作者： Malgorzata Lazarska Olga Siedlecka-Lamch Institute of Computer and Information Sciences Czestochowa University of Technology Czestochowa Poland

ISBN: (数字)9781728131801

ISBN: (纸本)9781728131818

We live in a time of incredible technological development. In a fraction of a second, millions of information are generated and processed all over the world. The need to develop new models of databases is related to the dynamic and the amount of data stored. Using database schemes which are rigid and do not quickly adapt to changes occurring in the real world is ineffective and sometimes simply impossible. The solution of all these problems could be, among others, graph *** this talk, we present a detailed comparison of relational and graph databases, compiling the stages of design, implementation and testing. At each stage, we keep the same data in both databases, checking how easily they can be modelled in each logical model, then imported, and finally made queries and modifications on them.

关键词： graph databases database modelling databases optimization

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