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EVALUATING RECURSIVE QUERIES IN distributed DATABASES

IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING 1993年第1期5卷 104-121页

作者： NEJDL, W CERI, S WIEDERHOLD, G STANFORD UNIV DEPT COMP SCISTANFORDCA 94305 POLITECN MILAN DIPARTIMENTO ELETTR & INFORMAZI-20133 MILANITALY VIENNA TECH UNIV A-1040 VIENNAAUSTRIA UNIV MODENA I-41100 MODENAITALY

In this paper, we study the execution of logic queries in a distributed database environment. We assume that each local database system can execute logic queries, and we design methods for the efficient execution or queries requiring data from multiple sites. Conventional optimization strategies which are well known in the field of distributed databases, such as the early evaluation of selection conditions and the clustering of processing to manipulate and exchange large sets of tuples, are redefined in view of the additional difficulties due to logic queries, in particular to recursive rules. In order to allow efficient processing of these logic queries we present several program transformation techniques which attempt to minimize distribution costs based on the idea of semi-joins and generalized semi-joins in conventional databases. Although local computation of semi-joins is not possible for the general case, we indicate classes of programs for which these transformations succeed in producing set-oriented computation. We describe processes evaluating the recursive program in a distributed network and develop an efficient method for testing the termination of the computation. Finally, we compare our approach with sequential as well as dataflow-oriented evaluation. Datalog is assumed as logic programming language and paradigm.

关键词： DEDUCTIVE DATABASES distributed DATABASES distributed query processing query OPTIMIZATION RECURSIVE query processing SEMI-JOIN

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Fault-tolerant resource allocation for query processing in grid environments

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INTERNATIONAL JOURNAL OF WEB AND GRID SERVICES 2015年第2期11卷 143-159页

作者： Cokuslu, Deniz Hameurlain, Abdelkader Erciyes, Kayhan Izmir Univ Software Engn Dept TR-35350 Izmir Turkey Univ Toulouse 3 IRIT F-31062 Toulouse France Izmir Univ Dept Comp Engn TR-35350 Izmir Turkey

In this paper, we propose a new algorithm for fault-tolerant resource allocation for query processing in grid environments. For this, we propose an initial resource allocation algorithm followed by a fault-tolerance protocol. The proposed fault-tolerance protocol is based on the passive replication of stateful operators in queries. We provide theoretical analyses of the proposed algorithms and consolidate our analyses with the simulations.

关键词： resource allocation fault-tolerance distributed query processing grid systems distributed databases

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Adaptive algorithms for join processing in distributed database systems

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distributed AND PARALLEL DATABASES 1997年第3期5卷 233-269页

作者： Scheuermann, P Chong, EI ORACLE CORP NEW ENGLAND R&D CTR NASHUA NH 03062 USA

distributed query processing algorithms usually perform data reduction by using a semijoin program, but the problem with these approaches is that they still require an explicit join of the reduced relations in the final phase. We introduce an efficient algorithm for join processing in distributed database systems that makes use of bipartite graphs in order to reduce data communication costs and local processing costs. The bipartite graphs represent the tuples that can be joined in two relations taking also into account the reduction state of the relations. This algorithm fully reduces the relations at each site. We then present an adaptive algorithm for response time optimization that takes into account the system configuration, i.e., the additional resources available and the data characteristics, in order to select the best strategy for response time minimization. We also report on the results of a set of experiments which show that our algorithms outperform a number of the recently proposed methods for total processing time and response time minimization.

关键词： distributed query processing join algorithms adaptive algorithms bipartite graphs

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ObjectGlobe: Ubiquitous query processing on the Internet

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VLDB JOURNAL 2001年第1期10卷 48-71页

作者： Braumandl, R Keidl, M Kemper, A Kossmann, D Kreutz, A Seltzsam, S Stocker, K Univ Passau Lehrstuhl Informat D-94030 Passau Germany Tech Univ Munich Inst Informat D-81667 Munich Germany

We present the design of ObjectGlobe, a distributed and open query processor for Internet data sources. Today, data is published on the Internet via Web servers which have, if at all, very localized query processing capabilities. The goal of the ObjectGlobe project is to establish an open marketplace in which data and query processing capabilities can be distributed and used by any kind of Internet application. Furthermore, ObjectGlobe integrates cycle providers (i.e., machines) which carry out query processing operators. The overall picture is to make it possible to execute a query with-in principle-unrelated query operators, cycle providers, and data sources. Such an infrastructure can serve as enabling technology for scalable e-commerce applications, e.g., B2B and B2C market places. to be able to integrate data and data processing operations of a large number of participants. One of the main challenges in the design of such an open system is to ensure privacy and security. We discuss the ObjectGlobe security requirements, show how basic components such as the optimizer and runtime system need to be extended, and present the results of performance experiments that assess the additional cost for secure distributed query processing. Another challenge is quality of service management so that users can constrain the costs and running times of their queries.

关键词： distributed query processing query optimization open systems cycle-, function- and data provider security privacy quality of service

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Federating queries in SPARQL 1.1: Syntax, semantics and evaluation

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JOURNAL OF WEB SEMANTICS 2013年第1期18卷 1-17页

作者： Buil-Aranda, Carlos Arenas, Marcelo Corcho, Oscar Polleres, Axel UPM Fac Informat Ontol Engn Grp Madrid Spain PUC Dept Comp Sci Santiago Chile Siemens AG Osterreich A-1210 Vienna Austria

Given the sustained growth that we are experiencing in the number of SPARQL endpoints available, the need to be able to send federated SPARQL queries across these has also grown. To address this use case, the W3C SPARQL working group is defining a federation extension for SPARQL 1.1 which allows for combining graph patterns that can be evaluated over several endpoints within a single query. In this paper, we describe the syntax of that extension and formalize its semantics. Additionally, we describe how a query evaluation system can be implemented for that federation extension, describing some static optimization techniques and reusing a query engine used for data-intensive science, so as to deal with large amounts of intermediate and final results. Finally we carry out a series of experiments that show that our optimizations speed up the federated query evaluation process. (c) 2012 Elsevier B.V. All rights reserved.

关键词： SPARQL 1.1 distributed data management distributed query processing RDF

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Parallel and scalable processing of spatio-temporal RDF queries using Spark

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GEOINFORMATICA 2021年第4期25卷 623-653页

作者： Nikitopoulos, Panagiotis Vlachou, Akrivi Doulkeridis, Christos Vouros, George A. Univ Piraeus Sch Informat & Commun Technol Dept Digital Syst Piraeus Greece

The ever-increasing size of data emanating from mobile devices and sensors, dictates the use of distributed systems for storing and querying these data. Typically, such data sources provide some spatio-temporal information, alongside other useful data. The RDF data model can be used to interlink and exchange data originating from heterogeneous sources in a uniform manner. For example, consider the case where vessels report their spatio-temporal position, on a regular basis, by using various surveillance systems. In this scenario, a user might be interested to know which vessels were moving in a specific area for a given temporal range. In this paper, we address the problem of efficiently storing and querying spatio-temporal RDF data in parallel. We specifically study the case of SPARQL queries with spatio-temporal constraints, by proposing the DiStRDF system, which is comprised of a Storage and a processing Layer. The DiStRDF Storage Layer is responsible for efficiently storing large amount of historical spatio-temporal RDF data of moving objects. On top of it, we devise our DiStRDF processing Layer, which parses a SPARQL query and produces corresponding logical and physical execution plans. We use Spark, a well-known distributed in-memory processing framework, as the underlying processing engine. Our experimental evaluation, on real data from both aviation and maritime domains, demonstrates the efficiency of our DiStRDF system, when using various spatio-temporal range constraints.

关键词： distributed query processing distributed spatio-temporal queries SPARQL queries

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StreamFilter: a framework for distributed processing of range queries over streaming data with fine-grained access control

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CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS 2024年第7期27卷 9221-9241页

作者： Safaee, Shahab Mirabi, Meghdad Safaei, Ali Asghar Islamic Azad Univ Fac Engn Dept Comp Engn South Tehran Branch Tehran Iran Tech Univ Darmstadt Fac Comp Sci Darmstadt Germany Tarbiat Modares Univ Fac Med Sci Dept Med Informat Tehran Iran

Access control is a fundamental component of any data management system, ensuring the prevention of unauthorized data access. Within the realm of data streams, it plays a crucial role in query processing by facilitating authorized access to them. This paper introduces the StreamFilter framework, which focuses on securely processing queries with range filters over streaming data. Leveraging the Role-Based Access Control model, the StreamFilter framework enables the specification of fine-grained access policies at various levels of granularity, such as tuples and attributes, through the utilization of a bit string structure. To enhance the search operation during data stream query processing, the framework employs a distributed indexing method, constructing a set of smaller B + Tree indices rather than a single large B + Tree index. Furthermore, it seamlessly integrates access authorization evaluation with query processing, efficiently filtering unauthorized parts from the query results. The experimental results demonstrate an approximately 50% increase in efficiency for processing queries with range filters compared to the post-filtering strategy. This improvement is observed across all types of data distribution, including uniform, skew, and hyper skew.

关键词： Access control B plus tree index distributed query processing Map-reduce programming model Range query Streaming data

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Tuple source relational model: A source-aware data model for multidatabases

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DATA & KNOWLEDGE ENGINEERING 1999年第1期29卷 83-114页

作者： Lim, EP Chiang, RHL Cao, YY Nanyang Technol Univ Sch Accountancy & Business Informat Management Res Ctr Singapore 639798 Singapore Nanyang Technol Univ Sch Appl Sci Ctr Adv Informat Syst Singapore 639798 Singapore

In some integration projects, complete integration of database instances may not be necessary. It may also be too costly and impossible to do so due to poor local data quality and insufficient instance-level knowledge. In this research, we study how multidatabases with global schemas should be represented and manipulated when the data instances from the local databases do not require to be fully integrated. We propose the tuple source (TS) relational model to represent multidatabases under such an integration requirement. This model extends the classical relational model by augmenting every relation with a source attribute to identify the local database that the tuples come from. The source attribute can also be used to specify the right context to interpret global data instances. To manipulate TS relations, we have developed a set of tuple source relational algebraic operations and an extended SQL query language known as TS-SQL. With TS relational model, flexible multidatabase queries that involve instances from different local databases can be formulated easily. In this paper, we also reported our distributed query processing and optimization strategies and their implementation. (C) 1999 Elsevier Science B.V. All rights reserved.

关键词： database integration multidatabases relational data model distributed query processing

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querying business processes with BP-QL

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INFORMATION SYSTEMS 2008年第6期33卷 477-507页

作者： Beeri, Catriel Eyal, Anat Kamenkovich, Simon Milo, Tova Tel Aviv Univ Sch Comp Sci IL-69978 Tel Aviv Israel Hebrew Univ Jerusalem Sch Engn & Comp Sci Jerusalem Israel

We present in this paper BP-QL, a novel query language for querying business processes. The BP-QL language is based on an intuitive model of business processes, an abstraction of the emerging BPEL (business process execution language) standard. It allows users to query business processes visually, in a manner very analogous to how such processes are typically specified, and can be employed in a distributed setting, where process components may be provided by distinct providers. We describe here the query language as well as its underlying formal model. We consider the properties of the various language components and explain how they influenced the language design. In particular we distinguish features that can be efficiently supported, and those that incur a prohibitively high cost, or cannot be computed at all. We also present our implementation which complies with real life standards for business process specifications, XML, and Web set-vices, and is used in the BP-QL system. (C) 2008 Elsevier B.V. All rights reserved.

关键词： business processes query languages XML BPEL distributed query processing

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Combinatorial optimization of distributed queries

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IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING 1995年第6期7卷 915-927页

作者： Groselj, B Malluhi, QM UNIV SW LOUISIANA CTR ADV COMP STUDIESLAFAYETTELA 70504

In relational distributed databases a query cost consists of a local cost and a transmission cost. query optimization is a combinatorial optimization problem, As the query size grows, the optimization methods based on exhaustive search become too expensive, We propose the following strategy for solving large distributed query optimization problems in relational database systems: 1) represent each query-processing schedule by a labeled directed graph, 2) reduce the number of different schedules by pruning away invalid or high-cost solutions, and 3) find a suboptimal schedule by combinatorial optimization, We investigate several combinatorial optimization techniques: random search, single start, multistart, simulated annealing, and a combination of random search and local simulated annealing. The utility of combinatorial optimization is demonstrated in the problem of finding the (sub)optimal semijoin schedule that fully reduces all relations of a tree query, The combination of random search and local simulated annealing was superior to other tested methods.

关键词： combinatorial optimization distributed query processing multistart random search relational database semi-join simulated annealing single start tree query

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