Giachetta, Roberto

Máriás, Zsigmond

Giachetta Roberto

Máriás Zsigmond

University of Szeged

Performance Evaluation of Storing Inhomogeneous Descriptive Dataof Digital MapsRoberto Giachetta and Zsigmond MáriásIn contemporary Geographical Information Systems (GIS) the large variety of digital mapsources requires the handling and storing of various descriptive data in a single storage facility.When even the number and type of attributes can vary map by map, the storage of such inho-mogeneous data in a single database is difficult, as querying is an essential task and requiresfast retrieval of data based on any present attribute. Examples of such databases can be foundunder the domain of the Institute of Geodesy, Cartography and Remote Sensing.This paper presents a performance analysis study regarding the storage of descriptive dataof digital map in database systems. Map description data can vary from simple numbers andtext to complex data structures, like coordinates and timelines. Even with creating different cat-egories for maps, it cannot be guaranteed that all items in the category have the same types ofattributes stored. In traditional relational databases, tables must have a predefined structure ac-cording to the database schema, therefore simply providing columns for each descriptive datathis kind of flexibility cannot be met, and data must be grouped and stored in given columns.Therefore fast querying features of relational databases (including indexing) cannot be used,which results in significant performance loss. The authors have studied several solutions ad-dressing this problem.The first solution is the usage of a semi-structured document-oriented database systemcalled MongoDB, which defines database items as documents that can contain any kind andany number of attributes (even other documents) regardless of any predefined structure. Theseitems are indexed according to their attribute types and values. These documents can be storedin collections, and there is no restriction on the structure of documents within a collection,therefore no restriction is needed on descriptive data.The second solution is based on the creating an object-oriented environment inside a rela-tional data model (based on our previous studies) and storing digital maps as objects in thedatabase. This structure relies on creating inheritance taxonomy within the database and pro-viding facilities to create classes and objects that can be altered in run-time. We have two ap-proaches for this solution. In the first one, attributes’ descriptions and classes are described inseparate tables with a third table providing the link between a class and its attributes. Objectsare stored in one table, and different types of attribute data are stored in different tables. Thismodel has the advantage of being very flexible, when changing class structures with no need toredefine any database schema, however, queries must fetch object data using different tables,and inheritance structure is hard to reconstruct. Several improvements have been introducedfor these problems (denormalization, inherited field storage, attribute table contraction). In thesecond approach class and attribute schemas are stored in the same way, but a separate tableis created for each class to store the instances. Therefore creating, altering or even droppingtables is needed when changing schemas, but querying will be much faster.In this study, the authors compare the original rational database solutions with these threeapproaches by implementing and testing with massive inhomogeneous and altering descrip-tive data. The article will conclude by presenting which method is best with digital map dataat different search/insert/update command ratios. Since this problem is not only typical in thefield of GIS, the solution can be applied generally to any domain using inhomogeneous data,like e-commerce systems and document warehouses.Keywords: geographical information systems, large-scale spatial data storage, document-orienteddatabases, object-oriented databases, performace analysis.33AcknowledgementsThe research is supported by the TÁMOP-4.2.1/B-09/1/KMR-2010-003 project.References[1] Csornai, G., László, et al., The Integrated Utilization of Satellite Images in Hungary: Op-erational Applications from Crop Monitoring to Ragweed Control, Proceedings of the 26thSymposium of EARSeL, Millpress, Rotterdam, The Netherlands, 2007.[2] Chodorow, C., Introduction to MongoDB, Free and Open Source Software Developers’ EuropeanMeeting (FOSDEM), Brussels, Belgium, 2010.[3] Giachetta, R., Elek., I., Developing an Advanced Document Based Map Server, 8th Interna-tional Conference on Applied Informatics (ICAI), Eger, Hungary, 2010.[4] Máriás, Zs., Design and Performance Analysis of Hierarchical Large-scale InhomogeneousDatabases, 8th International Conference on Applied Informatics (ICAI), Eger, Hungary, 2010.[5] Nadkarni, P. M., et al., Organization of Heterogeneous Scientific Data Using the EAV/CRRepresentation The Journal of the American Medical Informatics Association (JAMIA), vol. 6,issue 6, 1999.34

Performance evaluation of storing inhomogeneous descriptive data of digital maps : [abstract]

http://acta.bibl.u-szeged.hu/59960/1/cscs_2010_033-034.pdf

Performance evaluation of storing inhomogeneous descriptive data of digital maps

Abstract

Similar works

Full text

Available Versions

University of Szeged