I would like to test l2norm by this:
POST /_scripts/painless/_execute
{
"script": {
"source": "l2norm(params.v1, params.v2)",
"params": {
"v1": [1.0, 1.0],
"v2": [1.0, 1.0]
}
}
}
However, it throws exception,
{
"error" : {
"root_cause" : [
{
"type" : "script_exception",
"reason" : "compile error",
"script_stack" : [
"l2norm(params.v1, params. ...",
"^---- HERE"
],
"script" : "l2norm(params.v1, params.v2)",
"lang" : "painless",
"position" : {
"offset" : 0,
"start" : 0,
"end" : 25
}
}
],
"type" : "script_exception",
"reason" : "compile error",
"script_stack" : [
"l2norm(params.v1, params. ...",
"^---- HERE"
],
"script" : "l2norm(params.v1, params.v2)",
"lang" : "painless",
"position" : {
"offset" : 0,
"start" : 0,
"end" : 25
},
"caused_by" : {
"type" : "illegal_argument_exception",
"reason" : "Unknown call [l2norm] with [2] arguments."
}
},
"status" : 400
}
The reason I would like to test that is because I noticed for a dense_vector having l2_norm, knnSearch result score is different from that using script l2norm.
PUT product-index
{
"mappings": {
"properties": {
"product-vector": {
"type": "dense_vector",
"dims": 5,
"index": true,
"similarity": "l2_norm"
},
"price": {
"type": "long"
}
}
}
}
POST product-index/_bulk?refresh=true
{ "index": { "_id": "1" } }
{ "product-vector": [230.0, 300.33, -34.8988, 15.555, -200.0], "price": 1599 }
{ "index": { "_id": "2" } }
{ "product-vector": [-0.5, 100.0, -13.0, 14.8, -156.0], "price": 799 }
{ "index": { "_id": "3" } }
{ "product-vector": [0.5, 111.3, -13.0, 14.8, -156.0], "price": 1099 }
POST product-index/_knn_search
{
"_source": false,
"fields": [
"serverId",
"id",
"createTime",
"groupId",
"userId",
"appId"
],
"knn": {
"field": "product-vector",
"query_vector": [-0.5, 90.0, -10, 14.8, -156.0],
"k": 10,
"num_candidates": 100
}
}
POST product-index/_search
{
"query": {
"script_score": {
"query" : {
"bool" : {
"filter" : {
"range" : {
"price" : {
"gte": 1000
}
}
}
}
},
"script": {
"source": "l2norm(params.queryVector, 'product-vector')",
"params": {
"queryVector": [-0.5, 90.0, -10, 14.8, -156.0]
}
}
}
}
}
In above code, _search using l2_norm script has max_score : 316.10992, while _knn_search has max_score : 0.009090909. I would like dig into what causes this difference, since they both are l2_norm.