One large Elasticsearch lookup index, or several smaller ones? - elasticsearch

Question

I'm creating a lookup index that I'll use solely as a terms filter. So no searching/aggregating, only filtering and GETs.
I'm debating the structure of this lookup index, whether each document should contain all of the fields I want to filter for, or whether I should create an index per field.
For example, let's say each document pertains to a user. Each user has a list of games they've played, books they've read, and movies they've watched. When searching for game/book/movie recommendations, I'll use the term filter to filter out those items they've already interacted with.
I'm wondering if I should have a single lookup index with a document mapping like:
users_index
{
'game_ids': [],
'movie_ids' : [],
'book_ids': []
}
or one index per lookup value, like:
user_games_index
{
'game_ids': []
}
user_movies_index
{
'movie_ids': []
}
user_books_index
{
'book_ids': []
}
Pros for one index:
Each index comes with overhead, so the fewer the better
If I ever want to retrieve all of a user's info, it's all in one index
Pros for multiple indices:
According to the update api docs, updating a document means retrieving the whole thing first. I will be updating each document a lot, and those arrays can become rather large (think thousands of ids). Updating a book id will then retrieve all of the game ids, which takes up memory. If they were in separate indices, I could avoid that.
Just easier to maintain on my end of things
I should note that if I use multiple indices, it'll only be 4 or 5, with about 500k documents per index. Also, only 1 primary shard per index, no replicas, and I'm on a single m5.2xlarge EC2 instance (8 cores, 32G ram).
Are these stats so small that it won't really matter at this point, or should I favor one index or many?

Answer 1

How about a third option?
You have one index and each of your document in the index looks something like this:
{
"user_id" : "some_user",
"document_type" : "movie" or "game" or "book"
"document_id" : "id of movie, game or book"
}
Why? Since you say a user's games, movies or books will be updated often, this approach lets you easily add / delete individual movies, games or books for users.
You also can easily filter the books/movies/games for specific users.
All values are of type "keyword" and filtering should be fast.
PS: A "good" mapping for an ES index will try to minimize the numbers of updates on individual documents and rather work at the level of inserting / deleting documents as ES does this task very well compared to finding & updating documents.
Edit: I have added query examples to illustrate how you can filter out results with bool query.
Example:
I want all movies / games / books a user X has NOT interacted with.
GET _search
{
"query": {
"bool": {
"must_not":{
"term" : {
"user_id" : "user X"
}
}
}
}
}
I want only movies a user X has NOT interacted with.
GET _search
{
"query": {
"bool": {
"must_not":{
"term" : {
"user_id" : "user X"
}
},
"filter":{
"term" : {
"document_type" : "movie"
}
}
}
}
}