Graphical Querying of Multidimensional Databases

Ravat, Franck; Teste, Olivier; Tournier, Ronan; Zurfluh, Gilles

doi:10.1007/978-3-540-75185-4_22

Cited by 20 publications

(12 citation statements)

References 22 publications

(27 reference statements)

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…However, the necessity to provide visual artefacts for OLAP is also well-known [26]. With regard to OLAP algebras, this necessity has also been extended to the query definition by means of graphical languages with which to query data warehouses [37] or the direct representation of queries by marking conceptual schemata [6].…”

Section: Related Workmentioning

confidence: 99%

Extending OCL for OLAP querying on conceptual multidimensional models of data warehouses

Pardillo

Mazón

Trujillo

2010

Information Sciences

View full text Add to dashboard Cite

Section: Related Workmentioning

confidence: 99%

Extending OCL for OLAP querying on conceptual multidimensional models of data warehouses

Pardillo

Mazón

Trujillo

2010

Information Sciences

View full text Add to dashboard Cite

“…Then, the OLAP operation was implemented using MapReduce framework. Ravat et al (2007) defined a conceptual model that represents data through a constellation of facts and dimensions and present a query algebra handling multidimensional data as well as multidimensional tables. These studies take advantage of special data structure to improve the OLAP performance while in HaoLap the multidimensional model is adopted to perform OLAP, so the formers have a certain usage limitation.…”

Section: Related Workmentioning

confidence: 99%

HaoLap: A Hadoop based OLAP system for big data

Song

Guo

Wang

et al. 2015

Journal of Systems and Software

View full text Add to dashboard Cite

In recent years, facing information explosion, industry and academia have adopted distributed file system and MapReduce programming model to address new challenges the big data has brought. Based on these technologies, this paper presents HaoLap (Hadoop based oLap), an OLAP (OnLine Analytical Processing) system for big data. Drawing on the experience of Multidimensional OLAP (MOLAP), HaoLap adopts the specified multidimensional model to map the dimensions and the measures; the dimension coding and traverse algorithm to achieve the roll up operation on dimension hierarchy; the partition and linearization algorithm to store dimensions and measures; the chunk selection algorithm to optimize OLAP performance; and MapReduce to execute OLAP. The paper illustrates the key techniques of HaoLap including system architecture, dimension definition, dimension coding and traversing, partition, data storage, OLAP and data loading algorithm. We evaluated HaoLap on a real application and compared it with Hive, HadoopDB, HBaseLattice, and Olap4Cloud. The experiment results show that HaoLap boost the efficiency of data loading, and has a great advantage in the OLAP performance of the data set size and query complexity, and meanwhile HaoLap also completely support dimension operations.

show abstract

“…The final IS 3 represents the star schema or constellation schema that the decision maker wishes to analyse (Ravat et al 2007).…”

Section: Step 4: Generation Data-mart Schemamentioning

confidence: 99%

Computer-Aided Data-Mart Design

Abdelhédi¹,

Pujolle²,

Teste³

et al. 2011

Proceedings of the 13th International Conference on Enterprise Information Systems

View full text Add to dashboard Cite

With decision support systems, decision-makers analyse data in data marts extracted from production bases. The data-mart schema design is generally performed by expert designers (administrator or computer specialist). With data-driven, requirement-driven or hybrid-driven approaches, this designer builds a data-mart defining facts (analysis subjects) and analysis axes. This process, based on data sources and decision-makers requirements, often turns out to be approximate and complex. We propose to design a data-mart schema by the decision-maker himself, following a hybrid-driven approach. Using an assistance process that visualises successively intermediate schemas built from data sources, the decision-maker gradually builds his multidimensional schema. He determines measures to be analysed, dimensions hierarchies within dimensions. A CASE tool based on this concept has been developed.

show abstract

Graphical Querying of Multidimensional Databases

Cited by 20 publications

References 22 publications

Extending OCL for OLAP querying on conceptual multidimensional models of data warehouses

Extending OCL for OLAP querying on conceptual multidimensional models of data warehouses

HaoLap: A Hadoop based OLAP system for big data

Computer-Aided Data-Mart Design

Contact Info

Product

Resources

About