Revert "Backport distance functions vectors (#39330)" (#43233)

This reverts commit e802842.

Author: mayya-sharipova

docs/painless/painless-api-reference/painless-api-reference-score/index.asciidoc

@@ -10,8 +10,6 @@ The following specialized API is available in the Score context.
 ==== Static Methods
 The following methods are directly callable without a class/instance qualifier. Note parameters denoted by a (*) are treated as read-only values.
 
-* double cosineSimilarity(List *, VectorScriptDocValues.DenseVectorScriptDocValues)
-* double cosineSimilaritySparse(Map *, VectorScriptDocValues.SparseVectorScriptDocValues)
 * double decayDateExp(String *, String *, String *, double *, JodaCompatibleZonedDateTime)
 * double decayDateGauss(String *, String *, String *, double *, JodaCompatibleZonedDateTime)
 * double decayDateLinear(String *, String *, String *, double *, JodaCompatibleZonedDateTime)
@@ -21,23 +19,9 @@ The following methods are directly callable without a class/instance qualifier.
 * double decayNumericExp(double *, double *, double *, double *, double)
 * double decayNumericGauss(double *, double *, double *, double *, double)
 * double decayNumericLinear(double *, double *, double *, double *, double)
-* double dotProduct(List, VectorScriptDocValues.DenseVectorScriptDocValues)
-* double dotProductSparse(Map *, VectorScriptDocValues.SparseVectorScriptDocValues)
 * double randomScore(int *)
 * double randomScore(int *, String *)
 * double saturation(double, double)
 * double sigmoid(double, double, double)
 
-==== Classes By Package
-The following classes are available grouped by their respective packages. Click on a class to view details about the available methods and fields.
-
-
-==== org.elasticsearch.index.query
-<<painless-api-reference-score-org-elasticsearch-index-query, Expand details for org.elasticsearch.index.query>>
-
-* <<painless-api-reference-score-VectorScriptDocValues, VectorScriptDocValues>>
-* <<painless-api-reference-score-VectorScriptDocValues-DenseVectorScriptDocValues, VectorScriptDocValues.DenseVectorScriptDocValues>>
-* <<painless-api-reference-score-VectorScriptDocValues-SparseVectorScriptDocValues, VectorScriptDocValues.SparseVectorScriptDocValues>>
-
-include::packages.asciidoc[]
 

docs/painless/painless-api-reference/painless-api-reference-score/packages.asciidoc

@@ -9,7 +9,7 @@ not exceed 1024. The number of dimensions can be
 different across documents. A `dense_vector` field is
 a single-valued field.
 
-These vectors can be used for <<vector-functions,document scoring>>.
+These vectors can be used for document scoring.
 For example, a document score can represent a distance between
 a given query vector and the indexed document vector.
 

docs/reference/mapping/types/dense-vector.asciidoc

@@ -9,7 +9,7 @@ not exceed 1024. The number of dimensions can be
 different across documents. A `sparse_vector` field is
 a single-valued field.
 
-These vectors can be used for <<vector-functions,document scoring>>.
+These vectors can be used for document scoring.
 For example, a document score can represent a distance between
 a given query vector and the indexed document vector.
 

docs/reference/mapping/types/sparse-vector.asciidoc

@@ -72,122 +72,6 @@ to be the most efficient by using the internal mechanisms.
 --------------------------------------------------
 // NOTCONSOLE
 
-[[vector-functions]]
-===== Functions for vector fields
-
-experimental[]
-
-These functions are used for
-for <<dense-vector,`dense_vector`>>  and
-<<sparse-vector,`sparse_vector`>> fields.
-
-NOTE: During vector functions' calculation, all matched documents are
-linearly scanned. Thus, expect the query time grow linearly 
-with the number of matched documents. For this reason, we recommend
-to limit the number of matched documents with a `query` parameter.
-
-For dense_vector fields, `cosineSimilarity` calculates the measure of
-cosine similarity between a given query vector and document vectors.
-
-[source,js]
---------------------------------------------------
-{
-  "query": {
-    "script_score": {
-      "query": {
-        "match_all": {}
-      },
-      "script": {
-        "source": "cosineSimilarity(params.queryVector, doc['my_dense_vector'])",
-        "params": {
-          "queryVector": [4, 3.4, -0.2]  <1>
-        }
-      }
-    }
-  }
-}
---------------------------------------------------
-// NOTCONSOLE
-<1> To take advantage of the script optimizations, provide a query vector as a script parameter.
-
-Similarly, for sparse_vector fields, `cosineSimilaritySparse` calculates cosine similarity
-between a given query vector and document vectors.
-
-[source,js]
---------------------------------------------------
-{
-  "query": {
-    "script_score": {
-      "query": {
-        "match_all": {}
-      },
-      "script": {
-        "source": "cosineSimilaritySparse(params.queryVector, doc['my_sparse_vector'])",
-        "params": {
-          "queryVector": {"2": 0.5, "10" : 111.3, "50": -1.3, "113": 14.8, "4545": 156.0}
-        }
-      }
-    }
-  }
-}
---------------------------------------------------
-// NOTCONSOLE
-
-For dense_vector fields, `dotProduct` calculates the measure of
-dot product between a given query vector and document vectors.
-
-[source,js]
---------------------------------------------------
-{
-  "query": {
-    "script_score": {
-      "query": {
-        "match_all": {}
-      },
-      "script": {
-        "source": "dotProduct(params.queryVector, doc['my_dense_vector'])",
-        "params": {
-          "queryVector": [4, 3.4, -0.2]
-        }
-      }
-    }
-  }
-}
---------------------------------------------------
-// NOTCONSOLE
-
-Similarly, for sparse_vector fields, `dotProductSparse` calculates dot product
-between a given query vector and document vectors.
-
-[source,js]
---------------------------------------------------
-{
-  "query": {
-    "script_score": {
-      "query": {
-        "match_all": {}
-      },
-      "script": {
-        "source": "dotProductSparse(params.queryVector, doc['my_sparse_vector'])",
-        "params": {
-          "queryVector": {"2": 0.5, "10" : 111.3, "50": -1.3, "113": 14.8, "4545": 156.0}
-        }
-      }
-    }
-  }
-}
---------------------------------------------------
-// NOTCONSOLE
-
-NOTE: If a document doesn't have a value for a vector field on which
-a vector function is executed, 0 is returned as a result
-for this document.
-
-NOTE: If a document's dense vector field has a number of dimensions
-different from the query's vector, 0 is used for missing dimensions
-in the calculations of vector functions.
-
-
 [[random-score-function]]
 ===== Random score function
 `random_score` function generates scores that are uniformly distributed

docs/reference/query-dsl/script-score-query.asciidoc

@@ -17,6 +17,6 @@
     - match: { classes.6.methods.0.parameters.0 : java.lang.CharSequence }
     - match: { classes.6.methods.0.parameters.1 : int }
     - match: { classes.6.methods.0.parameters.2 : int }
-    - match: { imported_methods.0.name: dotProduct }
-    - match: { class_bindings.0.name: cosineSimilarity }
+    - match: { imported_methods.0.name: saturation }
+    - match: { class_bindings.0.name: decayDateExp }
     - match: { instance_bindings: [] }

modules/lang-painless/src/test/resources/rest-api-spec/test/painless/71_context_api.yml

@@ -20,9 +20,4 @@
 esplugin {
     description 'Adds advanced field mappers'
     classname 'org.elasticsearch.index.mapper.MapperExtrasPlugin'
-    extendedPlugins = ['lang-painless']
-}
-
-dependencies {
-    compileOnly project(':modules:lang-painless')
 }

modules/mapper-extras/build.gradle

@@ -30,7 +30,6 @@
 import org.elasticsearch.common.xcontent.XContentParser.Token;
 import org.elasticsearch.index.fielddata.IndexFieldData;
 import org.elasticsearch.index.query.QueryShardContext;
-import org.elasticsearch.index.query.VectorDVIndexFieldData;
 import org.elasticsearch.search.DocValueFormat;
 
 import java.io.IOException;
@@ -120,7 +119,8 @@ public Query existsQuery(QueryShardContext context) {
 
         @Override
         public IndexFieldData.Builder fielddataBuilder(String fullyQualifiedIndexName) {
-            return new VectorDVIndexFieldData.Builder(true);
+            throw new UnsupportedOperationException(
+                "Field [" + name() + "] of type [" + typeName() + "] doesn't support sorting, scripting or aggregating");
         }
 
         @Override

modules/mapper-extras/src/main/java/org/elasticsearch/index/mapper/DenseVectorFieldMapper.java

@@ -30,7 +30,6 @@
 import org.elasticsearch.common.xcontent.XContentParser.Token;
 import org.elasticsearch.index.fielddata.IndexFieldData;
 import org.elasticsearch.index.query.QueryShardContext;
-import org.elasticsearch.index.query.VectorDVIndexFieldData;
 import org.elasticsearch.search.DocValueFormat;
 
 import java.io.IOException;
@@ -120,7 +119,8 @@ public Query existsQuery(QueryShardContext context) {
 
         @Override
         public IndexFieldData.Builder fielddataBuilder(String fullyQualifiedIndexName) {
-            return new VectorDVIndexFieldData.Builder(false);
+            throw new UnsupportedOperationException(
+                "Field [" + name() + "] of type [" + typeName() + "] doesn't support sorting, scripting or aggregating");
         }
 
         @Override