How to integrate search results with database - api

Question

Lets say I store story documents in Elasticsearch like
{
story_id: 1,
title: "Hello World",
content: "Foo. Bar."
likes: 2222
}
When the client (frontend) searches, they should have the option to like (or remove their like) any of the search results, but there should also be an indication of whether or not they liked each result already.
What is a good way to get this information to the client?
Perform a database query to get all the stories the user has liked and keep it in the client's local storage. When search results are retrieved, map the user's liked stories to the retrieved search results on the client. This would add the complexity of updating local storage as well as the API when a user likes a story. Also, the number of stories a user likes could get very large.
Keep a list of users that have liked a story within the document itself and when searching check if the user is in the list. This could blow up the search index size?
{ ...
likes: [ 'foo_user', 'bar_user', ... ]
}
In the API, after the search, perform a database query to determine which stories in the search response the user has already liked, and map this info to the search results before returning the API response. This could slow down searches because an additional database query is required, but maybe it is inconsequential?

Answer 1

For this use case, most common/mainstream approach would be your option 3.
You need to save every like as a record in datastore.
You need to index docs in Elasticsearch(ES) with most probably only the properties you will use for searching and aggregation purpose, not whole doc.
After use query/search from Frontend you lookup from ES the docs and take their ids.
Go to datastore like records and check if there are user like records for each of them.
Combine this info and return whole doc to frontend.
Additional Datastore lookup would not cost you much both in time and money I would say. It wouldn't effect user experience much either.
My only concern would be because for every query I need to check likes collection, this request is not CDN/cache friendly.