The Experts below are selected from a list of 39 Experts worldwide ranked by ideXlab platform
Sonia Bergamaschi - One of the best experts on this subject based on the ideXlab platform.
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HPCS - SOPJ: A Scalable Online Provenance Join for Data Integration
2017 International Conference on High Performance Computing & Simulation (HPCS), 2017Co-Authors: Song Zhu, Giuseppe Fiameni, Giovanni Simonini, Sonia BergamaschiAbstract:Data integration is a technique used to combine different sources of data together to provide an unified view among them. MOMIS[1] is an open-source data integration framework developed by the DBGroup1. The goal of our work is to make MOMIS be able to scale-out as the input data sources increase without introducing noticeable performance penalty. In particular, we present a Full Outer Join method capable to efficiently integrate multiple sources at the same time by using data streams and provenance information. To evaluate the scalability of this innovative approach, we developed a Join engine employing a distributed data processing framework. Our solution is able to process input data sources in the form of continuous stream, execute the Join operation on-the-fly and produce outputs as soon as they are generated. In this way, the Join can return partial results before the input streams have been completely received or processed optimizing the entire execution. Encouraging results of adopting the proposed approach on real datasets closes the paper.
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Full Outer Join Optimization Techniques in Integration Information Systems
2006Co-Authors: Domenico Beneventano, Sonia Bergamaschi, Carlos Rodrigue, Nana MbinkeuAbstract:In Integration Information Systems data fusion, i.e. the merging of multiple tuples about the same real world object coming from different sources into a consistent and homogeneous set is often ignored [4]. The Full Outer Join operator is a good candidate in today’s integrating information systems, to perform data fusion [1, 5]. The problem is that Full Outer Join queries are very expensive, especially in a distributed environment as the one of mediator/integration systems. Database optimizers take Full advantage of associativity and commutativity properties of Join to implement efficient and powerful optimizations on Join queries; however, only limited optimization is performed on Full Outer Join [5]. This paper reports the description of work-in-progress about query optimization techniques for Full Outer Join queries developed in the context of the MOMIS/SEWASIE Integration System.
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Full Outer Join Optimization Techniques in Integration Information Systems
2006Co-Authors: Domenico Beneventano, Sonia Bergamaschi, Carlos Rodrigue, Nana MbinkeuAbstract:In Integration Information Systems data fusion, i.e. the merging of multiple tuples about the same real world object coming from different sources into a consistent and homogeneous set is often ignored [4]. The Full Outer Join operator is a good candidate in today’s integrating information systems, to perform data fusion [1, 5]. The problem is that Full Outer Join queries are very expensive, especially in a distributed environment as the one of mediator/integration systems. Database optimizers take Full advantage of associativity and commutativity properties of Join to implement efficient and powerful optimizations on Join queries; however, only limited optimization is performed on Full Outer Join [5]. This paper reports the description of work-in-progress about query optimization techniques for Full Outer Join queries developed in the context of the MOMIS/SEWASI
Nana Mbinkeu - One of the best experts on this subject based on the ideXlab platform.
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Full Outer Join Optimization Techniques in Integration Information Systems
2006Co-Authors: Domenico Beneventano, Sonia Bergamaschi, Carlos Rodrigue, Nana MbinkeuAbstract:In Integration Information Systems data fusion, i.e. the merging of multiple tuples about the same real world object coming from different sources into a consistent and homogeneous set is often ignored [4]. The Full Outer Join operator is a good candidate in today’s integrating information systems, to perform data fusion [1, 5]. The problem is that Full Outer Join queries are very expensive, especially in a distributed environment as the one of mediator/integration systems. Database optimizers take Full advantage of associativity and commutativity properties of Join to implement efficient and powerful optimizations on Join queries; however, only limited optimization is performed on Full Outer Join [5]. This paper reports the description of work-in-progress about query optimization techniques for Full Outer Join queries developed in the context of the MOMIS/SEWASIE Integration System.
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Full Outer Join Optimization Techniques in Integration Information Systems
2006Co-Authors: Domenico Beneventano, Sonia Bergamaschi, Carlos Rodrigue, Nana MbinkeuAbstract:In Integration Information Systems data fusion, i.e. the merging of multiple tuples about the same real world object coming from different sources into a consistent and homogeneous set is often ignored [4]. The Full Outer Join operator is a good candidate in today’s integrating information systems, to perform data fusion [1, 5]. The problem is that Full Outer Join queries are very expensive, especially in a distributed environment as the one of mediator/integration systems. Database optimizers take Full advantage of associativity and commutativity properties of Join to implement efficient and powerful optimizations on Join queries; however, only limited optimization is performed on Full Outer Join [5]. This paper reports the description of work-in-progress about query optimization techniques for Full Outer Join queries developed in the context of the MOMIS/SEWASI
Domenico Beneventano - One of the best experts on this subject based on the ideXlab platform.
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Full Outer Join Optimization Techniques in Integration Information Systems
2006Co-Authors: Domenico Beneventano, Sonia Bergamaschi, Carlos Rodrigue, Nana MbinkeuAbstract:In Integration Information Systems data fusion, i.e. the merging of multiple tuples about the same real world object coming from different sources into a consistent and homogeneous set is often ignored [4]. The Full Outer Join operator is a good candidate in today’s integrating information systems, to perform data fusion [1, 5]. The problem is that Full Outer Join queries are very expensive, especially in a distributed environment as the one of mediator/integration systems. Database optimizers take Full advantage of associativity and commutativity properties of Join to implement efficient and powerful optimizations on Join queries; however, only limited optimization is performed on Full Outer Join [5]. This paper reports the description of work-in-progress about query optimization techniques for Full Outer Join queries developed in the context of the MOMIS/SEWASIE Integration System.
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Full Outer Join Optimization Techniques in Integration Information Systems
2006Co-Authors: Domenico Beneventano, Sonia Bergamaschi, Carlos Rodrigue, Nana MbinkeuAbstract:In Integration Information Systems data fusion, i.e. the merging of multiple tuples about the same real world object coming from different sources into a consistent and homogeneous set is often ignored [4]. The Full Outer Join operator is a good candidate in today’s integrating information systems, to perform data fusion [1, 5]. The problem is that Full Outer Join queries are very expensive, especially in a distributed environment as the one of mediator/integration systems. Database optimizers take Full advantage of associativity and commutativity properties of Join to implement efficient and powerful optimizations on Join queries; however, only limited optimization is performed on Full Outer Join [5]. This paper reports the description of work-in-progress about query optimization techniques for Full Outer Join queries developed in the context of the MOMIS/SEWASI
Carlos Rodrigue - One of the best experts on this subject based on the ideXlab platform.
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Full Outer Join Optimization Techniques in Integration Information Systems
2006Co-Authors: Domenico Beneventano, Sonia Bergamaschi, Carlos Rodrigue, Nana MbinkeuAbstract:In Integration Information Systems data fusion, i.e. the merging of multiple tuples about the same real world object coming from different sources into a consistent and homogeneous set is often ignored [4]. The Full Outer Join operator is a good candidate in today’s integrating information systems, to perform data fusion [1, 5]. The problem is that Full Outer Join queries are very expensive, especially in a distributed environment as the one of mediator/integration systems. Database optimizers take Full advantage of associativity and commutativity properties of Join to implement efficient and powerful optimizations on Join queries; however, only limited optimization is performed on Full Outer Join [5]. This paper reports the description of work-in-progress about query optimization techniques for Full Outer Join queries developed in the context of the MOMIS/SEWASIE Integration System.
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Full Outer Join Optimization Techniques in Integration Information Systems
2006Co-Authors: Domenico Beneventano, Sonia Bergamaschi, Carlos Rodrigue, Nana MbinkeuAbstract:In Integration Information Systems data fusion, i.e. the merging of multiple tuples about the same real world object coming from different sources into a consistent and homogeneous set is often ignored [4]. The Full Outer Join operator is a good candidate in today’s integrating information systems, to perform data fusion [1, 5]. The problem is that Full Outer Join queries are very expensive, especially in a distributed environment as the one of mediator/integration systems. Database optimizers take Full advantage of associativity and commutativity properties of Join to implement efficient and powerful optimizations on Join queries; however, only limited optimization is performed on Full Outer Join [5]. This paper reports the description of work-in-progress about query optimization techniques for Full Outer Join queries developed in the context of the MOMIS/SEWASI
Dunren Che - One of the best experts on this subject based on the ideXlab platform.
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DEXA (2) - Join selectivity re-estimation for repetitive queries in databases
Lecture Notes in Computer Science, 2011Co-Authors: Wen-chi Hou, Cheng Luo, Qiang Zhu, Dunren CheAbstract:Repetitive queries refer to those queries that are likely to be executed repeatedly in the future. Examples of repetitive queries include those that are used to generate periodic reports, perform routine maintenance, summarize data for analysis, etc. They can constitute a large part of daily activities of the database system and deserve more optimization efforts. In this paper, we propose to collect information about Joins of a repetitive query, called the trace, during execution. We intend to use this information to re-estimate selectivities of Joins in all possible execution orders. We discuss the information needed to be kept for the Joins and design an operator, called the extended Full Outer Join, to gather such information. We show the sufficiency of the traces in computing the exact selectivities of Joins in all plans of the query. With the exact selectivities of Joins available, the query optimizer can utilize them to find truly the best Join order for the query in its search space, guaranteeing "optimal" execution of the query in the future.
