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Implicit JSON Schema Versioning Triggered by Temporal Updates to JSON-Based Big Data in the τJSchema Framework

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Proceedings of the 5th International Conference on Big Data and Internet of Things (BDIoT 2021)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 489))

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Abstract

Schema versioning of JSON-based Big Data is driven either explicitly by schema changes or implicitly by updates. In the τJSchema framework, we have previously investigated implicit JSON Schema versioning, by dealing with implicit schema changes driven by updates of JSON-based conventional Big Data. Since τJSchema supports not only conventional but also temporal JSON-based Big Data, in this paper, we complete our investigation by focusing on the temporal side of implicit schema versioning in τJSchema. To this end, we propose an approach for handling implicit schema changes triggered by temporal updates of JSON-based Big Data. More precisely, when a user specifies a temporal JSON update operation that modifies a snapshot JSON component assigning a valid-time timestamp to its new value, the execution of such an operation requires the JSON component to become temporal, which is for all intents a schema change. Thus, a new version of the τJSchema temporal characteristics document is generated, with the addition of a new valid-time characteristic. New versions of the temporal JSON schema and of the temporal JSON document are also accordingly created.

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Correspondence to Zouhaier Brahmia .

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Brahmia, Z., Brahmia, S., Grandi, F., Bouaziz, R. (2022). Implicit JSON Schema Versioning Triggered by Temporal Updates to JSON-Based Big Data in the τJSchema Framework. In: Lazaar, M., Duvallet, C., Touhafi, A., Al Achhab, M. (eds) Proceedings of the 5th International Conference on Big Data and Internet of Things. BDIoT 2021. Lecture Notes in Networks and Systems, vol 489. Springer, Cham. https://doi.org/10.1007/978-3-031-07969-6_3

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