I found information about how number of shards, number of fields in mapping, affect performance of Elasticsearch. But I could not find any information about how indexing or not indexing a field affect cluster performance. 

Imagine I have document like:

```
{
  "name":"John Doe", 
  "photoPath":"/var/www/public/images/i1/j/d/123456.jpg", 
  "passwordHash":"$12$3b$abc...354", 
  "bio":"..."
}

```

I need to put 10 to 100 such documents to the cluster each second. When I put such document in index I am pretty sure I'd need to fulltext search for name and fulltext search for bio. I will never search for photoPath and I will never need fulltext search for password hash. 

When I do my mapping I have several options:

* make all fields text and analyze them with simple analyzer (i.e. tokenize by any not-character) - in that case I will have terms like "i1", "3b" or "123456" in my index
* make name and bio text, make password hash keyword and make photoPath non-indexed

---

So my questions are:

* In what ways, if any, am I improving performance in case I use the second option with custom tailored field types?
* Am I correct in my assumption that having less fields indexed helps performance?
* Am I correct in my assumption that indexing fewer fields will improve indexing performance?
* Am I correct in my assumption that actual search will be faster if I index only what I need?