OpenSearch/docs/reference/mapping/params/boost.asciidoc

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[[mapping-boost]]
=== `boost`
Individual fields can be _boosted_ automatically -- count more towards the relevance score
-- at query time, with the `boost` parameter as follows:
[source,console]
--------------------------------------------------
PUT my_index
{
"mappings": {
"properties": {
"title": {
"type": "text",
"boost": 2 <1>
},
"content": {
"type": "text"
}
}
}
}
--------------------------------------------------
<1> Matches on the `title` field will have twice the weight as those on the
`content` field, which has the default `boost` of `1.0`.
NOTE: The boost is applied only for term queries (prefix, range and fuzzy queries are not _boosted_).
You can achieve the same effect by using the boost parameter directly in the query, for instance the following query (with field time boost):
[source,console]
--------------------------------------------------
POST _search
{
"query": {
"match": {
"title": {
"query": "quick brown fox"
}
}
}
}
--------------------------------------------------
is equivalent to:
[source,console]
--------------------------------------------------
POST _search
{
"query": {
"match": {
"title": {
"query": "quick brown fox",
"boost": 2
}
}
}
}
--------------------------------------------------
deprecated[5.0.0, "Index time boost is deprecated. Instead, the field mapping boost is applied at query time. For indices created before 5.0.0, the boost will still be applied at index time."]
[WARNING]
.Why index time boosting is a bad idea
==================================================
We advise against using index time boosting for the following reasons:
* You cannot change index-time `boost` values without reindexing all of your
documents.
* Every query supports query-time boosting which achieves the same effect. The
difference is that you can tweak the `boost` value without having to reindex.
* Index-time boosts are stored as part of the <<norms,`norm`>>, which is only one
byte. This reduces the resolution of the field length normalization factor
which can lead to lower quality relevance calculations.
==================================================