How can ElasticSearch be used to implement social search?

Question

I’m trying to create a business search with social features using ElasticSearch. I have a business directory, and users can interact with those businesses in different ways: b

Answer 1

There's another set of solutions that have the upside of being extremely fast (i.e. taking advantage of what ES is best at), but looks terrible to anyone who knows even the first thing about designing data storage/retrieval systems.

If your 'business' index is smaller than your 'user' index (i.e. 10,000 biz, 1,000,000 users)

1. Create 2 indexes: User and Business.
2. Business index should have an 'array' field that holds the ids of every user who has ever "interacted" with it (i.e. "users: 1,4,23,26,127,8678")
3. User index should have a nested array field with business IDs and reviews, checkins, etc in a nested object with meta information (i.e. "business_id:1233,rating: 7.5,checkins:21")

When you search for a business, do a quick string query or filter query with the User's friend ids (OR of course) against the Business index. The tf-idf should automatically filter businesses that have been interacted with the most by your your friends to the top. If you need more info, just hit the User index to get the meta data for each of your friends (rating, checkins, etc). This should be lightening fast and super efficient, because ES is absolutely fantastic at matching arrays as individual terms. That's what its for yo!

If your 'business' index is signifigantly larger than your 'user' index, reverse the pattern...putting an indexed array of business_ids a user has interacted with on the user index.