PowerBuilder / Cognite API v1 / Create entity matcher model
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integer li_rc
oleobject loo_Http
integer li_Success
oleobject loo_Json
oleobject loo_Resp
// This example assumes the Chilkat API to have been previously unlocked.
// See Global Unlock Sample for sample code.
loo_Http = create oleobject
// Use "Chilkat_9_5_0.Http" for versions of Chilkat < 10.0.0
li_rc = loo_Http.ConnectToNewObject("Chilkat.Http")
if li_rc < 0 then
destroy loo_Http
MessageBox("Error","Connecting to COM object failed")
return
end if
// Use this online tool to generate code from sample JSON: Generate Code to Create JSON
// The following JSON is sent in the request body.
// {
// "sources": [
// {},
// {}
// ],
// "targets": [
// {},
// {}
// ],
// "trueMatches": [
// [
// ],
// [
// ]
// ],
// "externalId": "in irure amet",
// "name": "minim",
// "description": "aliqua ipsum culpa eiusmod",
// "featureType": "simple",
// "matchFields": [
// {
// "source": "name",
// "target": "name"
// }
// ],
// "classifier": "randomforest",
// "ignoreMissingFields": false
// }
loo_Json = create oleobject
// Use "Chilkat_9_5_0.JsonObject" for versions of Chilkat < 10.0.0
li_rc = loo_Json.ConnectToNewObject("Chilkat.JsonObject")
loo_Json.UpdateNewArray("trueMatches[0].")
loo_Json.UpdateNewArray("trueMatches[1].")
loo_Json.UpdateString("externalId","in irure amet")
loo_Json.UpdateString("name","minim")
loo_Json.UpdateString("description","aliqua ipsum culpa eiusmod")
loo_Json.UpdateString("featureType","simple")
loo_Json.UpdateString("matchFields[0].source","name")
loo_Json.UpdateString("matchFields[0].target","name")
loo_Json.UpdateString("classifier","randomforest")
loo_Json.UpdateBool("ignoreMissingFields",0)
loo_Http.SetRequestHeader("content-type","application/json")
loo_Http.SetRequestHeader("api-key","{{api-key}}")
loo_Resp = loo_Http.PostJson3("https://domain.com/api/v1/projects/{{project}}/context/entitymatching","application/json",loo_Json)
if loo_Http.LastMethodSuccess = 0 then
Write-Debug loo_Http.LastErrorText
destroy loo_Http
destroy loo_Json
return
end if
Write-Debug string(loo_Resp.StatusCode)
Write-Debug loo_Resp.BodyStr
destroy loo_Resp
destroy loo_Http
destroy loo_Json
Curl Command
curl -X POST
-H "api-key: {{api-key}}"
-H "content-type: application/json"
-d '{
"sources": [
{},
{}
],
"targets": [
{},
{}
],
"trueMatches": [
[],
[]
],
"externalId": "in irure amet",
"name": "minim",
"description": "aliqua ipsum culpa eiusmod",
"featureType": "simple",
"matchFields": [
{
"source": "name",
"target": "name"
}
],
"classifier": "randomforest",
"ignoreMissingFields": false
}'
https://domain.com/api/v1/projects/{{project}}/context/entitymatching
Postman Collection Item JSON
{
"id": "entityMatchingCreate",
"name": "Create entity matcher model",
"request": {
"url": {
"host": "{{baseUrl}}",
"path": [
"api",
"v1",
"projects",
"{{project}}",
"context",
"entitymatching"
],
"query": [
],
"variable": [
]
},
"method": "POST",
"header": [
{
"key": "api-key",
"value": "{{api-key}}",
"description": "An admin can create API keys in the Cognite console."
},
{
"key": "content-type",
"value": "application/json"
}
],
"description": "Note: All users on this CDF subscription with assets read-all and entitymatching read-all and write-all capabilities in the project, are able to access the data sent to this endpoint. Train a model that predicts matches between entities (for example, time series names to asset names). This is also known as fuzzy joining. If there are no trueMatches (labeled data), you train a static (unsupervised) model, otherwise a machine learned (supervised) model is trained.",
"body": {
"mode": "raw",
"raw": "{\n \"sources\": [\n {},\n {}\n ],\n \"targets\": [\n {},\n {}\n ],\n \"trueMatches\": [\n [],\n []\n ],\n \"externalId\": \"in irure amet\",\n \"name\": \"minim\",\n \"description\": \"aliqua ipsum culpa eiusmod\",\n \"featureType\": \"simple\",\n \"matchFields\": [\n {\n \"source\": \"name\",\n \"target\": \"name\"\n }\n ],\n \"classifier\": \"randomforest\",\n \"ignoreMissingFields\": false\n}"
}
}
}