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Extended Adaptive Join Operator with Bind-Bloom Join for Federated SPARQL Queries

INTERNATIONAL JOURNAL OF DATA WAREHOUSING AND MINING 2017年第3期13卷 47-72页

作者： Oguz, Damla Yin, Shaoyi Ergenc, Belgin Hameurlain, Abdelkader Dikenelli, Oguz Paul Sabatier Univ Inst Res Comp Sci Toulouse IRIT Toulouse France Izmir Inst Technol Dept Comp Engn Izmir Turkey Ege Univ Dept Comp Engn Izmir Turkey

The goal of query optimization in query federation over linked data is to minimize the response time and the completion time. Communication time has the highest impact on them both. Static query optimization can end up with inefficient execution plans due to unpredictable data arrival rates and missing statistics. This study is an extension of adaptive join operator which always begins with symmetric hash join to minimize the response time, and can change the join method to bind join to minimize the completion time. The authors extend adaptive join operator with bind-bloom join to further reduce the communication time and, consequently, to minimize the completion time. They compare the new operator with symmetric hash join, bind join, bind-bloom join, and adaptive join operator with respect to the response time and the completion time. Performance evaluation shows that the extended operator provides optimal response time and further reduces the completion time. Moreover, it has the adaptation ability to different data arrival rates.

关键词： Adaptive query Optimization Bloom Filter distributed query processing Join Methods Linked Data query Federation

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Fault-tolerant query processing in structured P2P-systems

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distributed AND PARALLEL DATABASES 2010年第1期28卷 33-66页

作者： Bestehorn, Markus von der Weth, Christian Buchmann, Erik Boehm, Klemens Karlsruhe Inst Technol Inst Program Struct & Data Org Karlsruhe Germany Nanyang Technol Univ Singapore Singapore

Recently, a number of query processors has been proposed for the evaluation of relational queries in structured P2P systems. However, as these approaches do not consider peer or link failures, they cannot be deployed without extensions for real-world applications. We show that typical failures in structured P2P systems can have an unpredictable impact on the correctness of the result. In particular stateful operators that store intermediate results on peers, e.g., the distributed hash join, must protect such results against failures. Although many replication schemes for P2P systems exist, they cannot replicate operator states while the query is processed. In this paper we propose an in-query replication scheme which replicates the state of an operator among the neighbors of the processing peer. Our analytical evaluation shows that the network overhead of the in-query replication is in O(1) regarding network size, i.e., our scheme is scalable. We have carried out an extensive experimental evaluation using simulations as well as a PlanetLab deployment. It confirms the effectiveness and the efficiency of the in-query replication scheme and shows the effectiveness of the routing extension in networks of varying reliability.

关键词： Peer-to-peer distributed query processing Fault-tolerant operators distributed Hash Table (DHT)

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querying distributed Spatial Datasets with Unknown Regions

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IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING 2014年第10期26卷 2534-2547页

作者： Zhu, Qijun Lee, Dik Lun Lee, Wang-Chien Hong Kong Univ Sci & Technol Dept Comp Sci & Engn Hong Kong Hong Kong Peoples R China Penn State Univ Dept Comp Sci & Engn University Pk PA 16802 USA

This paper studies the problem of querying Bounded Spatial Datasets (BSDs). A BSD contains i) objects with known locations, and ii) unknown regions, each of which bounds an unknown number of objects, within a coverage area. We consider applications where each BSD is hosted on a server or site connected to a communication network and the BSDs overlap in their coverage areas. The challenge is to query the distributed BSDs to retrieve all objects and to minimize the unknown regions which may contain objects satisfying the query, while minimizing the data transmission volume and number of interactions between the query client and the sites. We develop query processing algorithms for two important types of spatial queries, namely, range and k-nearest-neighbor (kNN) queries. We develop the site-based approach and the area-based approach for efficiently processing range and kNN queries on distributed BSDs. They aim to process only a subset of the sites to obtain the full answer for a query. Thus, optimal site selection and the corresponding site querying methods are important problems studied in this paper. In the area-based approach, we prove an optimal division and derive a practical heuristic to partition a query and select the best processing site for each partition, hence achieving even better efficiency than the site-based approach. Simulation results based on three real spatial datasets show that our proposed approaches significantly outperform the baseline that uses a centralized approach in terms of data transmission volume and the number of interactions between the query client and the distributed sites.

关键词： distributed query processing spatial databases incomplete datasets data integration range queries kNN queries cost-efficient query processing

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Integrating and querying astronomical data on the e-GrOV data grid

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COMPUTER SYSTEMS SCIENCE AND ENGINEERING 2008年第2期23卷 107-119页

作者： Vargas-Solari, Genoveva Zechinelli-Martini, Jose-Luis Cuevas-Vicenttin, Victor Grenoble Informat Lab St Martin Dheres France Fundac Univ Amer Puebla Res Ctr Informat & Automat Technol Cholula Mexico

distributed query processing and heterogeneous data integration are two research areas that have received much attention over many years. These areas remain very relevant and continuously pose new challenges due to the numerous problems from various disciplines that can be solved by processing and analyzing large amounts of data. in this work we address in particular the problems faced by the fields of astronomy and astrophysics. The nature of these problems suggests the need of mechanisms that enable a wide range of distributed resources to cooperate in order to solve them. Currently, such environments composed of a large number of cooperating distributed resources are called Grids. This paper presents our approach and experiences on building a data integration and query processing system aimed at providing unified access to astronomical datasets through the e-GrOV data Grid, which represents a first step towards a Mexican Virtual Observatory.

关键词： query analysis Integrate virtual observatory disciplines distributed energy resources ASTRONOMY First Step data integration distributed query processing Heterogeneous data integration

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OPTIMIZING JOINS BETWEEN 2 FRAGMENTED RELATIONS ON A BROADCAST LOCAL-NETWORK

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INFORMATION SYSTEMS 1991年第2期16卷 185-198页

作者： AHN, JK MOON, SC KOREA INST SCI & TECHNOL DEPT COMP SCI SEOUL 130650 SOUTH KOREA

The problem of joining two fragmented relations on a broadcast network is dealt with. Multiple copies of a fragment are used to increase parallelism and reduce transmission cost. A bipartite graph model is used to represent the pairs of fragments from the two relations which need to be joined. We are interested in minimizing total transmission cost needed to compute a distributed join between two fragmented relations. This join problem is formulated as a linear integer program. Two heuristics are developed for the general two-way join problem. When the corresponding join graph is restricted to tree structure, an optimal algorithm can be developed. Computational experiments are performed to analyze the performances of these heuristics.

关键词： distributed query processing BROADCAST NETWORK FRAGMENTED DATABASE

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SNEE: a query processor for wireless sensor networks

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distributed AND PARALLEL DATABASES 2011年第1-2期29卷 31-85页

作者： Galpin, Ixent Brenninkmeijer, Christian Y. A. Gray, Alasdair J. G. Jabeen, Farhana Fernandes, Alvaro A. A. Paton, Norman W. Univ Manchester Sch Comp Sci Manchester M13 9PL Lancs England

A wireless sensor network (WSN) can be construed as an intelligent, largescale device for observing and measuring properties of the physical world. In recent years, the database research community has championed the view that if we construe a WSN as a database (i.e., if a significant aspect of its intelligent behavior is that it can execute declaratively-expressed queries), then one can achieve a significant reduction in the cost of engineering the software that implements a data collection program for the WSN while still achieving, through query optimization, very favorable cost:benefit ratios. This paper describes a query processing framework for WSNs that meets many desiderata associated with the view of WSN as databases. The framework is presented in the form of compiler/optimizer, called SNEE, for a continuous declarative query language over sensed data streams, called SNEEql. SNEEql can be shown to meet the expressiveness requirements of a large class of applications. SNEE can be shown to generate effective and efficient query evaluation plans. More specifically, the paper describes the following contributions: (1) a user-level syntax and physical algebra for SNEEql, an expressive continuous query language over WSNs;(2) example concrete algorithms for physical algebraic operators defined in such a way that the task of deriving memory, time and energy analytical cost-estimation models (CEMs) for them becomes straightforward by reduction to a structural traversal of the pseudocode;(3) CEMs for the concrete algorithms alluded to;(4) an architecture for the optimization of SNEEql queries, called SNEE, building on well-established distributed query processing components where possible, but making enhancements or refinements where necessary to accommodate the WSN context;(5) algorithms that instantiate the components in the SNEE architecture, thereby supporting integrated query planning that includes routing, placement and timing;and (6) an empirical performance eva

关键词： query optimization Wireless sensor networks distributed query processing query languages Continuous queries Cost estimation models

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SECURITY CONSTRAINT processing IN A MULTILEVEL SECURE distributed DATABASE-MANAGEMENT SYSTEM

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IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING 1995年第2期7卷 274-293页

作者： THURAISINGHAM, B FORD, W MITRE Corporation Bedford MA USA The MITRE Corporation McLean VA US Mitre Corp. Bedford MA USA

In a multilevel secure distributed database management system, users cleared at different security levels access and share a distributed database consisting of data at different sensitivity levels. An approach to assigning sensitivity levels, also called security levels, to data is one which utilizes constraints or classification rules. Security constraints provide an effective classification policy, They can be used to assign security levels to the data based on content, context, and time. In this paper we extend our previous work on security constraint processing in a centralized multilevel secure database management system by describing techniques for processing security constraints in a distributed environment during query, update, and database design operations.

关键词： MULTILEVEL SECURE distributed DATABASE MANAGEMENT SYSTEM SECURITY CONSTRAINTS INFERENCE PROBLEM SECURITY POLICY distributed query processing distributed UPDATE processing MULTILEVEL distributed DATABASE DESIGN

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A Service-Oriented distributed Semantic Mediator: Integrating Multiscale Biomedical Information

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IEEE TRANSACTIONS ON INFORMATION TECHNOLOGY IN BIOMEDICINE 2012年第6期16卷 1296-1303页

作者： Mora, Oscar Engelbrecht, Gerhard Bisbal, Jesus Prous Inst Biomed Res Barcelona 08028 Spain Univ Pompeu Fabra Barcelona 08002 Spain

Biomedical research continuously generates large amounts of heterogeneous and multimodal data spread over multiple data sources. These data, if appropriately shared and exploited, could dramatically improve the research practice itself, and ultimately the quality of health care delivered. This paper presents distributed Semantic MEDiator (DISMED), an open source semantic mediator that provides a unified view of a federated environment of multiscale biomedical data sources. DISMED is a Web-based software application to query and retrieve information distributed over a set of registered data sources, using semantic technologies. It also offers a user-friendly interface specifically designed to simplify the usage of these technologies by nonexpert users. Although the architecture of the software mediator is generic and domain independent, in the context of this paper, DISMED has been evaluated for managing biomedical environments and facilitating research with respect to the handling of scientific data distributed in multiple heterogeneous data sources. As part of this contribution, a quantitative evaluation framework has been developed. It consist of a benchmarking scenario and the definition of five realistic use-cases. This framework, created entirely with public datasets, has been used to compare the performance of DISMED against other available mediators. It is also available to the scientific community in order to evaluate progress in the domain of semantic mediation, in a systematic and comparable manner. The results show an average improvement in the execution time by DISMED of 55% compared to the second best alternative in four out of the five use-cases of the experimental evaluation.

关键词： Biomedical information data integration distributed query processing RDF semantic Web software mediator SPARQL

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Grid query optimizer to improve query processing in grids

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FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE 2008年第5期24卷 342-353页

作者： Liu, Shuo Karimi, Hassan A. Ohio Dominican Univ Div Math Comp & Nat Sci Columbus OH 43219 USA Univ Pittsburgh Sch Informat Sci Geoinformat Lab Pittsburgh PA 15213 USA

The emergence of computational grids, as global computing infrastructures, calls for development of new and advanced database techniques. While there exist algorithms and tools that facilitate database operations in grids, currently query optimization techniques are scant. In this paper, a query optimization technique, Grid query Optimizer (GQO), that improves overall response time for grid-based query processing is presented. GQO features a resource selection strategy and a generic parallelism processing algorithm to balance optimization cost and query execution. GQO is tested using a simulated grid environment and compared with two other optimization techniques. Experiment results show that GQO provides better-than-average performance and is especially suitable for queries with large search spaces. (c) 2007 Elsevier B.V. All rights reserved.

关键词： query optimization grid computing distributed query processing database systems

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Adaptive workload allocation in query processing in autonomous heterogeneous environments

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distributed AND PARALLEL DATABASES 2009年第3期25卷 125-164页

作者： Gounaris, Anastasios Smith, Jim Paton, Norman W. Sakellariou, Rizos Fernandes, Alvaro A. A. Watson, Paul Aristotle Univ Thessaloniki Dept Informat Thessaloniki 54124 Greece Univ Newcastle Tyne Sch Comp Sci Newcastle Upon Tyne NE1 7RU Tyne & Wear England Univ Manchester Sch Comp Sci Manchester M13 9PL Lancs England

The increasing prevalence of networked storage and computational resources, along with middleware for managing resource access and sharing, raises the prospect that queries can be run over resources obtained on demand, rather than on dedicated infrastructures. However, the movement of query processing into non-dedicated environments means that it is necessary to take account of the partial information and unstable conditions that characterise autonomous, shared, distributed settings. Thus, query processing on grid platforms needs to be adaptive, revising evaluation strategies at query runtime in response to the evolving environment, such as changes to machine load and availability. To address this challenge, adaptive techniques are described that: (i) balance load across plan partitions supporting intra-operator parallelism;(ii) remove bottlenecks in pipelined plans supporting inter-operator parallelism;and (iii) combine the two aforementioned techniques. The approach has been empirically evaluated in a grid-enabled adaptive query processor.

关键词： Adaptive query processing Dynamic resource allocation Load balancing distributed query processing query optimization Grid computing

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