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ANAPSID: an adaptive query processing engine for SPARQL endpoints
- In ISWC2011
, 2011
"... Abstract. Following the design rules of Linked Data, the number of available SPARQL endpoints that support remote query processing is quickly growing; however, because of the lack of adaptivity, query executions may frequently be unsuccessful. First, fixed plans identified following the traditional ..."
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Abstract. Following the design rules of Linked Data, the number of available SPARQL endpoints that support remote query processing is quickly growing; however, because of the lack of adaptivity, query executions may frequently be unsuccessful. First, fixed plans identified following the traditional optimize-then-execute paradigm, may timeout as a consequence of endpoint availability. Sec-ond, because blocking operators are usually implemented, endpoint query en-gines are not able to incrementally produce results, and may become blocked if data sources stop sending data. We present ANAPSID, an adaptive query engine for SPARQL endpoints that adapts query execution schedulers to data availabil-ity and run-time conditions. ANAPSID provides physical SPARQL operators that detect when a source becomes blocked or data traffic is bursty, and opportunis-tically, the operators produce results as quickly as data arrives from the sources. Additionally, ANAPSID operators implement main memory replacement policies to move previously computed matches to secondary memory avoiding duplicates. We compared ANAPSID performance with respect to RDF stores and endpoints, and observed that ANAPSID speeds up execution time, in some cases, in more than one order of magnitude. 1
SemLAV: Local-As-View Mediation for SPARQL Queries
"... Abstract. The Local-As-View (LAV) integration approach aims at query-ing heterogeneous data in dynamic environments. In LAV, data sources are described as views over a global schema which is used to pose queries. Query processing requires to generate and execute query rewritings, but for SPARQL quer ..."
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Abstract. The Local-As-View (LAV) integration approach aims at query-ing heterogeneous data in dynamic environments. In LAV, data sources are described as views over a global schema which is used to pose queries. Query processing requires to generate and execute query rewritings, but for SPARQL queries, the LAV query rewritings may not be generated or executed in a reasonable time. In this paper, we present SemLAV, an alternative technique to pro-cess SPARQL queries over a LAV integration system without generating rewritings. SemLAV executes the query against a partial instance of the global schema which is built on-the-fly with data from the relevant views. The paper presents an experimental study for SemLAV, and compares its performance with traditional LAV-based query processing techniques. The results suggest that SemLAV scales up to SPARQL queries even over a large number of views, while it significantly outperforms traditional so-lutions.
GUN: An Efficient Execution Strategy for Querying the Web of Data
"... Abstract. Local-As-View (LAV) mediators provide a uniform interface to a federation of heterogeneous data sources to attempt the execution of queries against the federation. LAV mediators rely on query rewriters to translate mediator queries into equivalent queries on the federated data sources. The ..."
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Abstract. Local-As-View (LAV) mediators provide a uniform interface to a federation of heterogeneous data sources to attempt the execution of queries against the federation. LAV mediators rely on query rewriters to translate mediator queries into equivalent queries on the federated data sources. The query rewriting problem in LAV mediators has shown to be NP-complete, and there may be an exponential number of rewritings, making unfeasible the execution or even generation of all the rewritings for some queries. The complexity of this problem can be particularly impacted when queries and data sources are described using SPARQL conjunctive queries, for which millions of rewritings could be generated. We aim at providing an efficient solution to the problem of executing LAV SPARQL query rewritings while the gathered answer is as complete as possible. We formulate the Result-Maximal k-Execution problem (Re-MakE) as the problem of maximizing the query results obtained from the execution of only k rewritings. Additionally, a novel query execution strategy called GUN is proposed to solve the ReMakE problem. Our ex-perimental evaluation demonstrates that GUN outperforms traditional techniques in terms of answer completeness and execution time. 1
STEREO: a SaT-based tool for an optimal solution of the sERvice selEctiOn problem
"... Abstract. We present STEREO, a system that offers an expressive formalism and implements techniques firmly grounded on logic to solve the Service Selection Problem (SSP). STEREO adopts the Local-As-View approach (LAV) to represent services ’ functionality as views on ontology concepts, while user re ..."
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Abstract. We present STEREO, a system that offers an expressive formalism and implements techniques firmly grounded on logic to solve the Service Selection Problem (SSP). STEREO adopts the Local-As-View approach (LAV) to represent services ’ functionality as views on ontology concepts, while user requests are expressed as conjunctive queries on these concepts. Additionally, users can describe their preferences, which are used to rank the solutions. We discuss the LAV formulation of SSP; then, we illustrate the encoding of SSP as a logical theory whose models are in correspondence with the problem solutions, and in presence of preferences, the best models are in correspondence with the best-ranked solutions. We demonstrate STEREO and the properties of modern SAT solvers that provide an efficient and scalable solution to SSP. 1
Adaptive Semantic Data Management Techniques for Linked Data-Graduate Course Description
, 2011
"... In the context of the Cloud of Linked Data, a large number of huge RDF linked datasets have become available, and this number keeps growing. Simultaneously, scalable and efficient RDF engines that follow the traditional optimize-then-execute paradigm have been developed to locally access RDF data, a ..."
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In the context of the Cloud of Linked Data, a large number of huge RDF linked datasets have become available, and this number keeps growing. Simultaneously, scalable and efficient RDF engines that follow the traditional optimize-then-execute paradigm have been developed to locally access RDF data, and SPARQL endpoints have been implemented for remote query processing. However, given the size of existing datasets, lack of statistics to describe available sources, and unpredictable conditions of remote queries, existing solutions are still insufficient. First, the most efficient RDF engines rely their query processing algorithms on physical access and storage structures that are locally stored; however, because of the size of existing linked datasets, loading the data and their links is not always feasible. Second, remote linked data query processing can be extremely costly because of the lack of query planning; also, current techniques are not adaptable to unpredictable data transfers or data availability, thus, executions can be unsuccessful. To overcome these limitations, query physical operators and execution engines need to be able to access remote data and adapt query execution schedulers to data availability. In this graduate course we present the basis of adaptive query processing frameworks defined in the database area, and their applicability in the Linked data context. This course targets graduate students who want to know limitations of existing RDF engines, adaptive query processing techniques and how traditional RDF data management approaches can be extended to remotely access linked data and be well-suitable to runtime conditions.
Axel Polleres & Huajun ChenPosters & Demonstrations Track – Organization Program Chairs
, 2010
"... On behalf of the program committee for ISWC2010 Posters & Demonstrations Track, it is our great pleasure to present these proceedings, which form a collection of abstracts describing the presented posters and demos presented at the conference. The posters and demonstrations track of ISWC 2010 co ..."
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On behalf of the program committee for ISWC2010 Posters & Demonstrations Track, it is our great pleasure to present these proceedings, which form a collection of abstracts describing the presented posters and demos presented at the conference. The posters and demonstrations track of ISWC 2010 continues the established tradition of providing an interaction and connection opportunity for researchers and practitioners to present and demonstrate their new and innovative work-in-progress. The track gives conference attendees a way to learn about novel on-going research projects that might not yet be complete, but whose preliminary results are already interesting. The track also provides presenters with an excellent opportunity to obtain feedback from their peers in an informal setting from knowledgeable sources. New in this year, we also encouraged authors of accepted full research or in-use papers to present a practical demonstration or poster with additional results. In total, there were initially 90 submissions, of which we accept 28 regular demos, 6 demos accompanying full papers, as well as 19 posters.
