Building a Data Store with the Dynamic Structure
https://doi.org/10.18255/1818-1015-2016-2-93-118
Abstract
This article presents the analysis of approaches to data warehouse construction based on relational and NoSQL solutions and lists the limitations of the relational approach to data mining. The contradiction between data presentation in the real subject domain and the model of data presentation in the relational and NoSQL approaches is revealed. The revealed contradiction is related to the temporality of the values of individual data attributes, the variability of the composition of these attributes, and structure of connections between them. A new logical model of the data warehouse with dynamic structure is proposed. The model is based on the concept of the object as a container for properties storage. Each property of the object includes the property name and two property values without reference and with reference, that are relevant at a given time. The reference property value points to an object whose name is interpreted as the value of the property at a given time. A formal description of the model with allocation of the necessary functionality to manipulate objects and their properties (selectors, predicates, constructors) is given and the necessary control structures are introduced. Substantiation of the proposed model, called an OP-model is given on the basis of compliance with the logical ER data model. It is proved that any ER data model can be implemented in the OP-model. At the same time, the advantages of the OP-model are indicated, they are associated with the possibility of changing connections between entities due to changes in the reference value at a particular time. The potential for scalability of data warehouse due to the unique identification of each object is noted.
About the Author
Yu. N. Artamonov
Federal state budgetary scientific institution «Gosmetodcentr», Lyusinovskaya str., 51, Moscow, 117997 Russia
Russian Federation
Russian Federation
PhD
References
1. Барсегян А. А., Технологии анализа данных: Data Mining, Visual Mining, Text Mining, OLAP, БХВ-Петербург, СПб, 2007; [Barsegjan A. A., Tehnologii analiza dannyh: Data Mining, Visual Mining, Text Mining, OLAP, BHV-Peterburg, SPb, 2007, 384 pp., (in Russian).]
2. Дейт К.Дж., Введение в системы баз данных, Вильямс, М., 2001, 1072 с.; [Dejt K.Dzh., Vvedenie v sistemy baz dannyh, Viljams, M., 2001, (in Russian).]
3. Мартин Дж., Организация баз данных в вычислительных системах, Мир, М., 1980, 665 с.; [Martin J., Computer data-base organization, IBM Systems Research Institute, New Jersey, 1977, 665 pp., (in Russian).]
4. Коннолли Т., Базы данных: проектирование, реализация и сопровождение: Теория и практика, Вильямc, М., 2003, 1440 с.; [Konnolli T., Bazy dannyh: proektirovanie, realizacija i soprovozhdenie: Teorija i praktika, Viljams, M., 2003, 1440 pp., (in Russian).]
5. List Of NoSQL Databases, http://nosql-database.org/.
6. Marcos Kawazoe Aguilera, Carole Delporte-Gallet, Hugues Fauconnier, and Sam Toueg, “Communication-efficient leader election and consensus with limited link synchrony”, The Proceedings of the International Symposium on Principles of Distributed Computing (PODC), 2004, 328–337.
7. Herlihy M. Shavit N., “The topological structure of asynchronous computability”, Journal of the ACM, 46:6 (1999), 858–923.
8. Haifeng Y. Amin V., “The costs and limits of availability for replicated services”, ACM Transactions on Computer Systems, 24:1 (2006), 70–113.
9. Brian F. Cooper, Raghu Ramakrishnan, Utkarsh Srivastava, Adam Silberstein, Philip Bohannon, Hans-Arno Jacobsen, Nick Puz, Daniel Weaver, Ramana Yerneni, “Pnuts: Yahoo!’s hosted data serving platform”, PVLDB, 1:2 (2008), 1277–1288.
10. Swati Ahirrao Rajesh Ingle, “Scalable transactions in cloud data stores”, Journal of Cloud Computing: Advances, Systems and Applications, 4:21 (2015), 1–14.
11. In-memory data structure store Redis, http://redis.io/.
12. MongoDB Professional with Cloud Manager, https://www.mongodb.org/.
13. A Database for the Web CouchDB, http://couchdb.apache.org/.
14. Писаренко Д.С., Рублев В.С., “Объектная СУБД Динамическая информационная модель DIM и ее основные концепции”, Моделирование и анализ информационных систем, 16:1 (2009), 62–91; [Pisarenko D.S., Rublev V.S., “Object DBMS DIM and its main concepts”, Modeling and Analysis of Information Systems, 16:1 (2009), 62–91, (in Russian).]
15. Рублев В.С., “Язык объектных запросов динамической информационной модели DIM”, Моделирование и анализ информационных систем, 17:3 (2010), 144–161; [Rublev V.S., “The object query language of the dynamic information model DIM”, Modeling and Analysis of Information Systems, 17:3 (2010), 144–161, (in Russian).]
16. Рублев В.С., “Отношение истории и динамика схем баз данных СУБД DIM”, Моделирование и анализ информационных систем, 19:2 (2012), 97–108; [Roublev V.S., “Evolution of DBMS DIM Database Schemes”, Modeling and Analysis of Information Systems, 19:2 (2012), 97–108, (in Russian).]
17. Антонов Д.В., Рублев В.С., “Эффективность доступа к данным в СУБД DIM”, Моделирование и анализ информационных систем, 22:2 (2015), 158–175; [Antonov D.V., Roublev V.S., “Access Efficiency to Data in DIM DBMS”, Modeling and Analysis of Information Systems, 22:2 (2015), 158–175, (in Russian).]
18. Петров А.Н., Рублев В.С., “Полнота динамики значений свойств данных в СУБД DIM”, Моделирование и анализ информационных систем, 22:2 (2015), 259–277. [Petrov A.N., Roublev V.S., “Completeness of the Dynamics of the Attributes Values of Data in the Database DIM”, Modeling and Analysis of Information Systems, 22:2 (2015), 259–277, (in Russian)].
19. Roublev V.S., “Static completeness of the dynamic information model”, Automatic control and computer sciences, 49:3 (2015), 167–176.
20. A Comprehensive Data Integration and Business Analytics Platform, http://www.pentaho.com/.
21. Data Mining Software in Java, http://www.cs.waikato.ac.nz/ml/weka/.
22. Doug H., Let Over Lambda, 2010, 384 pp.
23. Alexandros B., “An Efficient Database Storage Structure for Large Dynamic Objects”, Proceedings, IEEE Data Engineering Conference, Phoenix, Arizona, 1992, 301–308.
24. Полтавцев А.А., “Динамические структуры в реляционных базах данных”, Программные продукты и системы, 2:110 (2015), 95–97; [Poltavtsev A.A., “Dynamic structures in relation databases”, Software & Systems, 2:110 (2015), 95–97, (in Russian).]
25. Цикритзис Д., Лоховски Ф., Модели данных, Финансы и статистика, М., 1985, 168 с.; [Tsikritzis D., Lokhovski F., Modeli dannykh, Finansy i statistika, M., 1985, 168 pp., (in Russian).]
26. Калиниченко Л.А., Методы и средства интеграции неоднородных баз данных, Наука, М., 1983, 424 с.; [Kalinichenko L.A., Metody i sredstva integratsii neodnorodnykh baz dannykh, Nauka, M., 1983, 424 pp., (in Russian).]
Review
For citations:
Artamonov Yu.N. Building a Data Store with the Dynamic Structure. Modeling and Analysis of Information Systems. 2016;23(2):93-118. (In Russ.) https://doi.org/10.18255/1818-1015-2016-2-93-118
Views:
1169
Email this article 