Mostly just do the most naive data-flattening you can and see
how big the index is. You really have to generate the index then
run representative queries at it.
But naively flattening the data in this case approaches
15B documents, which is a problem, you're sharding over quite a
few shards etc.
We have about 15 million items. Each item has 10 attributes that we are
indexing at this time. We are planning on adding 15 more attributes in
future.
We have about 1 customers. Each of the items mentioned above can have
special pricing, etc for each of the customers. There are 6 attributes of
For 1-3, test and see. The problem I often see is that it is _assumed_ that
flattening the data will cost a lot in terms of index size and maintenance.
Test that assumption before going down the relational road.
You haven't talked about how many documents you have, how much data
would have to be r
