Abstract
Several modern applications (e.g., Internet of Things, online social networks), which exploit big data, require a complete history of all changes performed on these data and their schemas (or structures). However, although schema versioning has long been advocated to be the best solution for this issue, currently there are no available technical supports, provided by existing big data management systems (especially NoSQL DBMSs), for handling temporal evolution and versioning aspects of big data. In [14], for a disciplined and systematic approach to the temporal management of JSON-based big data in NoSQL databases, we have proposed the use of a framework, named τJSchema (temporal JSON Schema). It allows defining and validating temporal JSON documents that obey to a temporal JSON schema. A τJSchema schema is composed of a conventional (i.e., non-temporal) JSON schema annotated with a set of temporal logical and temporal physical characteristics. Moreover, since these two components could evolve over time to respond to new applications’ requirements, we have extended τJSchema, in [17], to support versioning of conventional JSON schemas. In this work, we complete the figure by extending our framework to also support versioning of temporal logical and physical characteristics. Indeed, we propose a technique for temporal characteristics versioning, and provide a complete set of low-level change operations for the maintenance of these characteristics; for each operation, we define its arguments and its operational semantics. Thus, with this extension, τJSchema will provide a full support of temporal versioning of JSON-based big data at both instance and schema levels.
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References
Chen, C.P., Zhang, C.Y.: Data-intensive applications, challenges, techniques and technologies: a survey on Big Data. Inf. Sci. 275, 314–347 (2014)
Information Resources Management Association: Big Data: Concepts, Methodologies, Tools, and Applications. IGI Global, Hershey, PA, USA (2016)
Cuzzocrea, A.: Temporal aspects of big data management: state-of-the-art analysis and future research directions. In: Proceedings of the 22nd International Symposium on Temporal Representation and Reasoning (TIME 2015), Kassel, Germany, pp. 180–185, 23–25 September 2015
Snodgrass, R.T. (ed.), Ahn, I., Ariav, G., et al.: The TSQL2 Temporal Query Language. Kluwer Academic Publishers, Norwell (1995)
Brahmia, Z., Grandi, F., Oliboni, B., Bouaziz, R.: Schema versioning. In: Khosrow-Pour, M. (ed.) Encyclopedia of Information Science and Technology, 3rd edn., pp. 7651–7661. IGI Global, Hershey (2015)
NoSQL Databases. http://www.nosql-database.org/
Tiwari, S.: Professional NoSQL. John Wiley & Sons, Inc., Indianapolis (2011)
Pokorný, J.: NoSQL databases: a step to database scalability in web environment. Int. J. Web Inf. Syst. 9(1), 69–82 (2013)
Sharma, S., Tim, U.S., Wong, J., et al.: A brief review on leading big data models. Data Sci. J. 13, 138–157 (2014)
Gudivada, V.N., Rao, D., Raghavan, V.V.: NoSQL systems for big data management. In: Proceedings of the 2014 IEEE World Congress on Services (SERVICES 2014), Anchorage, AK, USA, pp. 190–197, 27 June–2 July 2014
Sharma, S., Tim, U.S., Gadia, S.K., et al.: Classification and comparison of NoSQL big data models. Int. J. Big Data Intell. 2(3), 201–221 (2015)
Corbellini, A., Mateos, C., Zunino, A., et al.: Persisting big-data: The NoSQL landscape. Inf. Syst. 63, 1–23 (2017)
Davoudian, A., Chen, L., Liu, M.: A survey on NoSQL stores. ACM Comput. Surv. 51(2), 43 (2018). Article 40
Brahmia, S., Brahmia, Z., Grandi, F., Bouaziz, R.: τJSchema: a framework for managing temporal JSON-based NoSQL databases. In: Proceedings of the 27th International Conference on Database and Expert Systems Applications (DEXA 2016), Part II, Porto, Portugal, 5–8 September, pp. 167–181 (2016)
Internet Engineering Task Force: JSON Schema: core definition and terminology, Internet-Draft, 4 August 2013. https://tools.ietf.org/html/draft-zyp-json-schema-04
Internet Engineering Task Force: The JavaScript Object Notation (JSON) Data Interchange Format, Internet Standards Track document, March 2014
Brahmia, S., Brahmia, Z., Grandi, F., Bouaziz, R.: Temporal JSON schema versioning in the τJSchema framework. J. Digit. Inf. Manag. 15(4), 179–202 (2017)
Brahmia, S., Brahmia, Z., Grandi, F., Bouaziz, R.: Online Appendix of the Paper: Managing Temporal and Versioning Aspects of JSON-based Big Data via the τJSchema Framework, 12 p., 10 October 2018. http://www-db.disi.unibo.it/~fgrandi/papers/ICBDSDE2018paperAppendix.pdf
Florescu, D., Fourny, G.: JSONiq: the History of a query language. IEEE Internet Comput. 17(5), 86–90 (2013)
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Brahmia, S., Brahmia, Z., Grandi, F., Bouaziz, R. (2019). Managing Temporal and Versioning Aspects of JSON-Based Big Data via the τJSchema Framework. In: Farhaoui, Y., Moussaid, L. (eds) Big Data and Smart Digital Environment. ICBDSDE 2018. Studies in Big Data, vol 53. Springer, Cham. https://doi.org/10.1007/978-3-030-12048-1_5
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DOI: https://doi.org/10.1007/978-3-030-12048-1_5
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