# Providing weight to individual fields
**URL:** https://discuss.elastic.co/t/providing-weight-to-individual-fields/63081
**Category:** Elasticsearch
**Created:** [October 14, 2016, 8:44pm UTC](https://discuss.elastic.co/t/providing-weight-to-individual-fields/63081 "2016-10-14T20:44:12Z")
**Posts on this page:** 5
**Page:** 1
### Author:  [@Josh\_Harrison](https://discuss.elastic.co/u/Josh_Harrison)
#### Post date: [October 14, 2016, 8:44pm UTC](https://discuss.elastic.co/t/providing-weight-to-individual-fields/63081/1 "2016-10-14T20:44:12Z")
I have a nested document structure like
`{"mystaff":[{"name":"bob", "value":0.375}, {"name":"fred", "value":0.8537}]}`
Is it possible to use the value associated with bob or fred as a weight value in a query when determining the "best" document? That is, if I have both
`{"_index":"staff", "_type":"performance", "_id":1,"_source":{"mystaff":[{"name":"bob", "value":0.375}, {"name":"fred", "value":0.8537}]}}`
`{"_index":"staff", "_type":"performance", "_id":2,"_source":{"mystaff":[{"name":"bob", "value":0.99743}, {"name":"fred", "value":0.5583}]}}`
I'd like to be able to search for "bob" and get back /staff/performance/2 as a higher scoring record than /staff/performance/1, based on the value Bob has at mystaff.value.
Note this is an extremely simplified example - I ultimately want to build something akin to a list of performance for events for many hundreds of "staff" per "performance event", then be able to issue a seperate weighted query where I care more about how Kerry and Sue did than Bob and Fred, but I don't care how Jerry did or if he even participated. I know that'll end up being a large bool query with "should" and "must" clauses, along with weighting of individual terms, but this seems like the core approach to something like that.
That is to say, I want to query the events where overall Kerry and Sue did really well, Bob and Fred doing well is a bonus but not hugely impactful, and Jerry may or may not have participated in the event.
Edit: Is this where [https://www.elastic.co/guide/en/elasticsearch/reference/2.4/query-dsl-function-score-query.html](https://www.elastic.co/guide/en/elasticsearch/reference/2.4/query-dsl-function-score-query.html) would come into play?
---
### Author:  [@warkolm](https://discuss.elastic.co/u/warkolm)
#### Post date: [October 15, 2016, 10:55pm UTC](https://discuss.elastic.co/t/providing-weight-to-individual-fields/63081/2 "2016-10-15T22:55:09Z")
[https://www.elastic.co/guide/en/elasticsearch/reference/2.4/query-dsl-query-string-query.html#\_boosting](https://www.elastic.co/guide/en/elasticsearch/reference/2.4/query-dsl-query-string-query.html#_boosting) might be more what you want.
---
### Author:  [@Josh\_Harrison](https://discuss.elastic.co/u/Josh_Harrison)
#### Post date: [October 26, 2016, 8:50pm UTC](https://discuss.elastic.co/t/providing-weight-to-individual-fields/63081/3 "2016-10-26T20:50:36Z")
I think I'd need something beyond just boosted - as far as I can tell, that's saying "when I am doing my query, I care more about tokens X and Y than I do Z".
The first part of what I need to do is, if I query "fred" without any specific boosting, get back values in order of document id 1, then document id 2 (because "fred" has a value of 0.8537 in doc 1, and 0.5583 in doc 2). Similarly, I want to be able to search for "bob" without any specific boosting to get back document 2, then document 1 (doc 1, bob has a value of 0.375, doc 2 bob has a value of 0.99743).
Then on top of that, I want to apply query side boosting - I want to put together a query like (I know not doing a nested query right, at the moment this is just an example) {"query":{"bool":{"should":[{"term":{"mystaff.name":"bob^0.89"}},{"term":{"mystaff.name":"fred^0.67"}}]}}}
Would this end up looking like using a bunch of decay functions in boolean statements like:
> ```
> {
> "query": {
> "bool": {
> "should": [
> {
> "function_score": {
> "functions": [
> {
> "gauss": {
> "mystaff.value": {
> "origin": 0,
> "scale": 1
> }
> }
> }
> ],
> "score_mode": "multiply",
> "query": {
> "match": {
> "term": {
> "mystaff.name": "fred^0.67"
> }
> }
> }
> }
> },
> {
> "function_score": {
> "functions": [
> {
> "gauss": {
> "mystaff.value": {
> "origin": 0,
> "scale": 1
> }
> }
> }
> ],
> "query": {
> "match": {
> "term": {
> "mystaff.name": "bob^0.89"
> }
> }
> }
> }
> }
> ]
> }
> }
> }
>
> ```
---
### Author:  [@Josh\_Harrison](https://discuss.elastic.co/u/Josh_Harrison)
#### Post date: [October 27, 2016, 11:00pm UTC](https://discuss.elastic.co/t/providing-weight-to-individual-fields/63081/4 "2016-10-27T23:00:22Z")
I was able to do this with something very similar to the query above - I ended up needing two nested queries, containing a bool query, with a "should" clause containing a bunch of gauss function scores pointing to the individual weight in each nested record, with an origin of 1 and a scale of 1 (so the further away from 1 the value was, the lower it was weighted, if I understand correctly). Each function\_score has a "boost" parameter corresponding to the value of the searched weight.
Essentially this, given my previous example records:
> ```
> {
> "query": {
> "nested": {
> "score_mode": "sum",
> "path": "mystaff",
> "query": {
> "bool": {
> "should": [
> {
> "function_score": {
> "query": {
> "match": {
> "mystaff.name": "bob"
> }
> },
> "functions": [
> {
> "gauss": {
> "mystaff.value": {
> "origin": 1,
> "scale": 1
> }
> }
> }
> ],
> "boost": 0.89,
> "score_mode": "multiply"
> }
> },
> {
> "function_score": {
> "query": {
> "match": {
> "mystaff.name": "fred"
> }
> },
> "functions": [
> {
> "gauss": {
> "mystaff.value": {
> "origin": 1,
> "scale": 1
> }
> }
> }
> ],
> "boost": 0.67,
> "score_mode": "multiply"
> }
> }
> ]
> }
> }
> }
> }
> }
>
> ```
---
### Author:  [@system](https://discuss.elastic.co/u/system)
#### Post date: [July 5, 2017, 10:08pm UTC](https://discuss.elastic.co/t/providing-weight-to-individual-fields/63081/5 "2017-07-05T22:08:55Z")