Backport distance functions vectors #39330
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* Distance measures for dense and sparse vectors
Introduce painless functions of
cosineSimilarity and dotProduct distance
measures for dense and sparse vector fields.
```js
{
"query": {
"script_score": {
"query": {
"match_all": {}
},
"script": {
"source": "cosineSimilarity(params.queryVector, doc['my_dense_vector'].value)",
"params": {
"queryVector": [4, 3.4, -1.2]
}
}
}
}
}
```
```js
{
"query": {
"script_score": {
"query": {
"match_all": {}
},
"script": {
"source": "cosineSimilaritySparse(params.queryVector, doc['my_sparse_vector'].value)",
"params": {
"queryVector": {"2": -0.5, "10" : 111.3, "50": -13.0, "113": 14.8, "4545": -156.0}
}
}
}
}
}
```
Closes elastic#31615
Create index with only 1 shard to ensure an expected request failure Closes elastic#39218
mayya-sharipova
added
backport
:Search Relevance/Ranking
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|
Pinging @elastic/es-search |
mayya-sharipova
added a commit
to mayya-sharipova/elasticsearch
that referenced
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Jun 14, 2019
This reverts commit e802842.
mayya-sharipova
added a commit
that referenced
this pull request
Jun 14, 2019
jtibshirani
added
:Search Relevance/Vectors
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Distance functions for dense and sparse vectors
Backport for #37947, #39313