Streaming Validation of JSON Documents Against Schemas
Alexis Le Glaunec, Angela W. Li, Konstantinos Mamouras
摘要
JSON is a popular data format for storing semi-structured data. We investigate the computational problem of JSON validation, which is the task of checking whether a JSON document adheres to a given schema. While there are several existing tools that support JSON validation, they implement offline algorithms that require loading the entire document in memory and creating the full parse tree before performing validation. This offline approach is constrained by the available system memory and is inappropriate when the data is presented as a stream. We propose an approach for performing streaming JSON validation that relies on a new class of pushdown automata that can process JSON documents in an online fashion. Our experimental results show that our approach uses substantially less memory and is faster than state-of-the-art tools.
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