XWeB: The XML Warehouse Benchmark

Mahboubi, Hadj; Darmont, Jérôme

doi:10.1007/978-3-642-18206-8_14

Cited by 6 publications

(5 citation statements)

References 20 publications

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“…To compare QBS to Pedersen, we use the XWeB benchmark [15], which remodels the TPC-H [31] relational database as a star XML schema. XWeB initially generates documents scaling in size from 50,000 to 250,000 facts.…”

Section: Methodsmentioning

confidence: 99%

A Novel Query-Based Approach for Addressing Summarizability Issues in XOLAP

Hachicha,

Kit,

Darmont

2013

Preprint

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The business intelligence and decision-support systems used in many application domains casually rely on data warehouses, which are decision-oriented data repositories modeled as multidimensional (MD) structures. MD structures help navigate data through hierarchical levels of detail. In many real-world situations, hierarchies in MD models are complex, which causes data aggregation issues, collectively known as the summarizability problem. This problem leads to incorrect analyses and critically affects decision making. To enforce summarizability, existing approaches alter either MD models or data, and must be applied a priori, on a case-by-case basis, by an expert. To alter neither models nor data, a few query-time approaches have been proposed recently, but they only detect summarizability issues without solving them. Thus, we propose in this paper a novel approach that automatically detects and processes summarizability issues at query time, without requiring any particular expertise from the user. Moreover, while most existing approaches are based on the relational model, our approach focus on an XML MD model, since XML data is customarily used to represent business data and its format better copes with complex hierarchies than the relational model. Finally, our experiments show that our method is likely to scale better than a reference approach for addressing the summarizability problem in the MD context.

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Section: Methodsmentioning

confidence: 99%

A Novel Query-Based Approach for Addressing Summarizability Issues in XOLAP

Hachicha,

Kit,

Darmont

2013

Preprint

Self Cite

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“…For instance, TPC-H was used to benchmark Hadoop and Pig (Moussa, 2012) and SSB for testing the efficiency of view materialization in the cloud (Perriot et al, 2014). Niche benchmarks also rely a lot on TPC-H. XWeB (Mahboubi & Darmont, 2010) proposes a unified reference model for XML warehouses and its associate XQuery decision-support workload. RTDW-bench (Jedrzejczak et al, 2012) is designed for testing the ability of a real-time data warehouse to handle a transaction stream without delay, given an arrival rate.…”

Section: Decision-support Benchmarksmentioning

confidence: 99%

Data-Centric Benchmarking

Darmont

2018

Encyclopedia of Information Science and Technology, Fourth Edition

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In data management, both system designers and users casually resort to performance evaluation. Performance evaluation by experimentation on a real system is generally referred to as benchmarking. The aim of this chapter is to present an overview of the major past and present state-of-the-art data-centric benchmarks. This review includes the TPC standard benchmarks, but also alternative or more specialized benchmarks. Surveyed benchmarks are categorized into three families: transaction benchmarks aimed at On-Line Transaction Processing (OLTP), decision-support benchmarks aimed at On-Line Analysis Processing (OLAP) and big data benchmarks. Issues, tradeoffs and future trends in data-centric benchmarking are also discussed.

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“…XML is an emerging standard for data representation and exchange semistructured complex data on the World Wide Web. XMLbased DWFs (Levy et al, 1996;Golfarelli et al, 2001;Rusu et al, 2004;Mahboubi & Darmont, 2011) usually involve web data and the main focus lies on the integration of complex data. Mostly these frameworks consist of XMLdocuments as input files, XML-ODS as preparing zone, and XML Cubes as multidimensional structure.…”

Section: Related Workmentioning

confidence: 99%

The data warehouse virtualization framework for operational business intelligence

Farooq

2012

Expert Systems

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In order to explore the most current information and react faster to changing business conditions, organizations consider real‐time data warehousing a powerful technique to achieve operational business intelligence (BI). We propose in this paper a novel real‐time data warehouse (RTDW) framework based on the virtualization concept. Our approach introduces a conceptual modelling technique, known as ring modelling, for real‐time data management and multidimensional analysis. This technique produces a flexible semi‐structured data model that accommodates unknown business process data and relationships as they evolve, handles schema changes and aggregate‐management efficiently, and scales well with the large size of increasing data volumes. With the help of a telecommunication business example, We evaluated our proposed approach in an extensive experimental study where we compared our approach Ring Model with existing structured multidimensional conceptual models (MCMs), i.e. relational OLAP and multidimensional OLAP, and with semi‐structured MCM, i.e. XML Cubes, in terms of scalability, data storage estimations, data updates loading time, and query response times. Our performance results show that encouraging speedups are achieved.

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XWeB: The XML Warehouse Benchmark

Cited by 6 publications

References 20 publications

A Novel Query-Based Approach for Addressing Summarizability Issues in XOLAP

A Novel Query-Based Approach for Addressing Summarizability Issues in XOLAP

Data-Centric Benchmarking

The data warehouse virtualization framework for operational business intelligence

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