Abstract
Data models are a central piece in information systems, being the relational data models very popular and extensively used. In Big Data, and due to the characteristics of the NoSQL databases, the data modeling task is seen in another perspective, as those databases are considered schema-free. Nevertheless, these databases also need data models that ensure the proper storage and querying of the data. Considering the vast amount of relational databases and the ever-increasing volume of data, the importance of data models in Big Data increases. In this work, a specific set of rules is proposed for the automatic transition between a traditional and a Big Data environment, considering two specific objectives: the identification of a columnar data model for HBase supporting operational needs and the identification of a tabular data model for Hive supporting analytical needs. The obtained results show the applicability of the proposed rules and their relevance for data modeling in Big Data environments.
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References
Chen, H., Chiang, R.H., Storey, V.C.: Business intelligence and analytics: from Big Data to Big Impact. MIS Q. 36, 1165–1188 (2012)
Durham, E.-E., Rosen, A., Harrison, R.W., et al.: A model architecture for Big Data applications using relational databases. In: 2014 IEEE International Conference on Big Data (Big Data), pp. 9–16. IEEE (2014)
Li, C.: Transforming relational database into HBase: a case study. In: 2010 IEEE International Conference on Software Engineering and Service Sciences (ICSESS), pp. 683–687. IEEE (2010)
Vajk, T., Feher, P., Fekete, K., Charaf, H.: Denormalizing data into schema-free databases. In: 2013 IEEE 4th International Conference on Cognitive Infocommunications (CogInfoCom), pp. 747–752. IEEE (2013)
Di Tria, F., Lefons, E., Tangorra, F.: Design process for Big Data warehouses. In: 2014 International Conference on Data Science and Advanced Analytics (DSAA), pp. 512–518. IEEE (2014)
HBase: Apache HBase (2016). https://hbase.apache.org
Khurana, A.: Introduction to HBase schema design. White Paper, Cloudera (2012)
Hive: Apache Hive (2016). https://hive.apache.org
Thusoo, A., Sarma, J.S., Jain, N., Shao, Z., Chakka, P., Zhang, N., Antony, S., Liu, H., Murthy, R.: Hive-a petabyte scale data warehouse using hadoop. In: 2010 IEEE 26th International Conference on Data Engineering (ICDE), pp. 996–1005. IEEE (2010)
Capriolo, E., Wampler, D., Rutherglen, J.: Programming Hive. O’Reilly & Associates, Sebastopol (2012)
Hewitt, E.: Cassandra: The Definitive Guide. O’Reilly, Beijing (2011)
Acknowledgments
This work has been supported by COMPETE: POCI-01-0145-FEDER-007043 and FCT, Fundação para a Ciência e Tecnologia, within the Projects UID/CEC/00319/2013 (ALGORITMI) and MITP-TB/CS/0026/2013 (SusCity).
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Santos, M.Y., Costa, C. (2016). Data Models in NoSQL Databases for Big Data Contexts. In: Tan, Y., Shi, Y. (eds) Data Mining and Big Data. DMBD 2016. Lecture Notes in Computer Science(), vol 9714. Springer, Cham. https://doi.org/10.1007/978-3-319-40973-3_48
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DOI: https://doi.org/10.1007/978-3-319-40973-3_48
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