Microsoft FHIR Server serialize searchindices this way in cosmosdb. How to model it in AWS DynamoDB? { "id": "9240cda7-bbb7-4ad4-aa9f-971750a3dc71", "searchIndices": [ { "p": "_id", "c": "9240cda7-bbb7-4ad4-aa9f-971750a3dc71" }, { "p": "_lastUpdated", "st": "2018-08-22T23:37:56.1289012+00:00", "et": "2018-08-22T23:37:56.1289012+00:00" }, { "p": "patient", "r": "Patient/example" }, { "p": "performer", "r": "Practitioner/example" }, { "p": "related", "r_0": "Observation/example-genetics-1", "s_1": "http://hl7.org/fhir/observation-relationshiptypes", "c_1": "derived-from" }, { "p": "related-target", "r": "Observation/example-genetics-1" }, { "p": "related-type", "s": "http://hl7.org/fhir/observation-relationshiptypes", "c": "derived-from" }, { "p": "status", "s": "http://hl7.

How do you extract multiple fields at different levels of nesting json resources? jsonpath, jq, jmespath or chatgpt? In FHIR, bundle resource in json format usually have multiple level of details nested in json. It’s quite different from other use cases. My first thought is using jsonpath as it is quite similar to FHIRPath. There are several limitations of jsonpath which make it infeasible. It doesn’t support to the use case, even though JsonPath supports deep scan and Bracket-notated child or children.