How can an existing large data model be loaded with the Realtime API?

Question

I have a realtime data model with a lot of data in it. When I try to load it using the API call my onLoaded function does not get called. Similarly my error handling function does not get called even though one of the underlying API calls (https://drive.google.com/otservice/gs?id=...&access_token=...) receives a 409 response from the server.

My attempts to load smaller data models works fine. I am confident that I am using the API correctly since I started my code from the example provided on the Realtime API Quickstart page.

Google Drive has the concept of requesting a partial response using the fields parameter to reduce the amount of data returned. I can not see similar functionality for the realtime API. Does it exist?

Is there a way to download the realtime data model as a generic file so I can pre-populate my application with data until the Realtime API is completely loaded?

Answer 1

Data models greater than around 10 megs are not currently supported. It sounds like you might be running into this limit.

You should think about how you can reduce the amount of data you are storing. E.g., store large items like images outside of the Realtime model, or (based on what you said you were doing in your previous question) do some smoothing to reduce the number of points stored as it increases.

You can export the data model right now in the Javascript API: https://developers.google.com/drive/realtime/reference/gapi.drive.realtime.Document#gapi.drive.realtime.Document.prototype.exportDocument

But in order to do that, you have to load the document first.