aws personalize putevents does not update recommendations

Question

I'm trying to use AWS Personalize. After creating dataset and batch inference, I am updating the user-item-interactions with personalize.putEvents (using Javascript SDK, docs)

Snippet:

const awsOpts = { apiVersion, accessKeyId, secretAccessKey, region }
const pEvents = new AWS.PersonalizeEvents(awsOpts)
// ...
const params = {
trackingId, userId, sessionId,
eventList: [{ 
    eventId: (+sentAt) + "",
    sentAt, 
    eventType,
    properties: { itemId }
}]
}
pEvents.putEvents(params, (err, data) => err ? reject(err) : resolve(data))

The events seem to be registered. No errors. After that when I create another batch-inference, I would expect that the new user-items would not appear in the recommendations anymore. But the recommendations in the next batch-inference are unchanged. Am I doing something wrong or am I misunderstanding the putEvents-API-call?

Schema for reference:

{
 "type": "record",
 "name": "Interactions",
 "namespace": "com.amazonaws.personalize.schema",
 "fields": [
    {
        "name": "USER_ID",
        "type": "string"
    },
    {
        "name": "ITEM_ID",
        "type": "string"
    },
    {
        "name": "EVENT_TYPE",
        "type": "string"
    },
    {
        "name": "TIMESTAMP",
        "type": "long"
    }
 ],
 "version": "1.0"
}

One thing seems a bit strange: Cloud watch reports that the lambda was executed twice despite no errors nor timeout exceeded (timeout is set to 10s, and the lambda takes less than 2s). Also Retry attempts is set to 2.

Answer 1

@D.J.Duff (sadly I can't comment)

Are you sure the events added using PutEvent API are considered without retraining ? I have been through the AWS Personalize Doc looking for exactly that and it looked to me that you need to retrain to get those events included and for the runtime api to be able to consider them. Could you point to me where you saw that they are considered without having to retrain ? Thanks