Implicit JSON Schema Versioning Driven by Big Data Evolution in the τJSchema Framework

In JSON-based NoSQL data stores, Big Data instance documents and their JSON schemas must evolve over time to reflect changes in the real world. When a JSON instance document, valid with respect to a JSON schema, is updated giving rise to a new document no longer valid with respect to the schema, the update is usually rejected also resulting in user frustration. In such a case, the JSON schema has to be explicitly changed by an administrator in order to become compliant with the new Big Data format before the update can be effected by the user. The different approach we propose in this work is to privilege the user actions and accept in a transparent way any update he/she wants to apply to the instance documents: violation of the validity of an updated instance document with respect to its JSON schema is automatically detected and schema changes necessary to produce a new schema version compliant with the new Big Data format are automatically applied by the system, producing a new JSON schema version. Hence, in this work, we deal with implicit JSON schema versioning driven by updates to JSON-based Big Data instance documents. Our proposed solution consists in an extension of the tauJSchema (Temporal JSON Schema) framework we previously introduced to create and validate temporal JSON documents and to allow classical temporal JSON schema versioning, to also support implicit JSON schema versioning.