Remove deprecated vector functions.

docs/reference/migration/migrate_8_0/search.asciidoc

@@ -34,4 +34,12 @@ The `nested_filter` and `nested_path` options, deprecated in 6.x, have been remo
 
 {es} will no longer prefer using shards in the same location (with the same awareness attribute values) to process
 `_search` and `_get` requests. Adaptive replica selection (activated by default in this version) will route requests
-more efficiently using the service time of prior inter-node communications.
+more efficiently using the service time of prior inter-node communications.
+
+[float]
+==== Update to vector function signatures
+The vector functions of the form `function(query, doc['field'])` were
+deprecated in 7.6, and are now removed in 8.x. The form
+`function(query, 'field')` should be used instead. For example,
+`cosineSimilarity(query, doc['field'])` is replaced by
+`cosineSimilarity(query, 'field')`.

x-pack/plugin/src/test/resources/rest-api-spec/test/vectors/10_dense_vector_basic.yml

@@ -1,6 +1,6 @@
 setup:
   - skip:
-      features: [headers, warnings]
+      features: headers
       version: " - 7.2.99"
       reason: "dense_vector functions were added from 7.3"
 
@@ -99,26 +99,3 @@ setup:
   - match: {hits.hits.2._id: "1"}
   - gte: {hits.hits.2._score: 0.78}
   - lte: {hits.hits.2._score: 0.791}
-
----
-"Deprecated function signature":
-  - do:
-      headers:
-        Content-Type: application/json
-      warnings:
-        - The vector functions of the form function(query, doc['field']) are deprecated, and the form function(query, 'field') should be used instead. For example, cosineSimilarity(query, doc['field']) is replaced by cosineSimilarity(query, 'field').
-      search:
-        rest_total_hits_as_int: true
-        body:
-          query:
-            script_score:
-              query: {match_all: {} }
-              script:
-                source: "cosineSimilarity(params.query_vector, doc['my_dense_vector'])"
-                params:
-                  query_vector: [0.5, 111.3, -13.0, 14.8, -156.0]
-
-  - match: {hits.total: 3}
-  - match: {hits.hits.0._id: "3"}
-  - match: {hits.hits.1._id: "2"}
-  - match: {hits.hits.2._id: "1"}

x-pack/plugin/src/test/resources/rest-api-spec/test/vectors/30_sparse_vector_basic.yml

@@ -104,27 +104,3 @@ setup:
 - match: {hits.hits.2._id: "1"}
 - gte: {hits.hits.2._score: 0.78}
 - lte: {hits.hits.2._score: 0.791}
-
----
-"Deprecated function signature":
-  - do:
-      headers:
-        Content-Type: application/json
-      warnings:
-        - The [sparse_vector] field type is deprecated and will be removed in 8.0.
-        - The vector functions of the form function(query, doc['field']) are deprecated, and the form function(query, 'field') should be used instead. For example, cosineSimilarity(query, doc['field']) is replaced by cosineSimilarity(query, 'field').
-      search:
-        rest_total_hits_as_int: true
-        body:
-          query:
-            script_score:
-              query: {match_all: {} }
-              script:
-                source: "cosineSimilaritySparse(params.query_vector, doc['my_sparse_vector'])"
-                params:
-                  query_vector: {"2": -0.5, "10" : 111.3, "50": -13.0, "113": 14.8, "4545": -156.0}
-
-  - match: {hits.total: 3}
-  - match: {hits.hits.0._id: "3"}
-  - match: {hits.hits.1._id: "2"}
-  - match: {hits.hits.2._id: "1"}

x-pack/plugin/vectors/src/main/java/org/elasticsearch/xpack/vectors/query/ScoreScriptUtils.java

@@ -27,9 +27,6 @@
 
 public class ScoreScriptUtils {
     private static final DeprecationLogger deprecationLogger = new DeprecationLogger(LogManager.getLogger(ScoreScriptUtils.class));
-    static final String DEPRECATION_MESSAGE = "The vector functions of the form function(query, doc['field']) are deprecated, and " +
-        "the form function(query, 'field') should be used instead. For example, cosineSimilarity(query, doc['field']) is replaced by " +
-        "cosineSimilarity(query, 'field').";
 
     //**************FUNCTIONS FOR DENSE VECTORS
     // Functions are implemented as classes to accept a hidden parameter scoreScript that contains some index settings.
@@ -43,7 +40,7 @@ public static class DenseVectorFunction {
 
         public DenseVectorFunction(ScoreScript scoreScript,
                                    List<Number> queryVector,
-                                   Object field) {
+                                   String field) {
             this(scoreScript, queryVector, field, false);
         }
 
@@ -56,9 +53,10 @@ public DenseVectorFunction(ScoreScript scoreScript,
          */
         public DenseVectorFunction(ScoreScript scoreScript,
                                    List<Number> queryVector,
-                                   Object field,
+                                   String field,
                                    boolean normalizeQuery) {
             this.scoreScript = scoreScript;
+            this.docValues = (DenseVectorScriptDocValues) scoreScript.getDoc().get(field);
 
             this.queryVector = new float[queryVector.size()];
             double queryMagnitude = 0.0;
@@ -74,17 +72,6 @@ public DenseVectorFunction(ScoreScript scoreScript,
                     this.queryVector[dim] /= queryMagnitude;
                 }
             }
-
-            if (field instanceof String) {
-                String fieldName = (String) field;
-                docValues = (DenseVectorScriptDocValues) scoreScript.getDoc().get(fieldName);
-            } else if (field instanceof DenseVectorScriptDocValues) {
-                docValues = (DenseVectorScriptDocValues) field;
-                deprecationLogger.deprecatedAndMaybeLog("vector_function_signature", DEPRECATION_MESSAGE);
-            } else {
-                throw new IllegalArgumentException("For vector functions, the 'field' argument must be of type String or " +
-                    "VectorScriptDocValues");
-            }
         }
 
         BytesRef getEncodedVector() {
@@ -112,7 +99,7 @@ BytesRef getEncodedVector() {
     // Calculate l1 norm (Manhattan distance) between a query's dense vector and documents' dense vectors
     public static final class L1Norm extends DenseVectorFunction {
 
-        public L1Norm(ScoreScript scoreScript, List<Number> queryVector, Object field) {
+        public L1Norm(ScoreScript scoreScript, List<Number> queryVector, String field) {
             super(scoreScript, queryVector, field);
         }
 
@@ -132,7 +119,7 @@ public double l1norm() {
     // Calculate l2 norm (Euclidean distance) between a query's dense vector and documents' dense vectors
     public static final class L2Norm extends DenseVectorFunction {
 
-        public L2Norm(ScoreScript scoreScript, List<Number> queryVector, Object field) {
+        public L2Norm(ScoreScript scoreScript, List<Number> queryVector, String field) {
             super(scoreScript, queryVector, field);
         }
 
@@ -152,7 +139,7 @@ public double l2norm() {
     // Calculate a dot product between a query's dense vector and documents' dense vectors
     public static final class DotProduct extends DenseVectorFunction {
 
-        public DotProduct(ScoreScript scoreScript, List<Number> queryVector, Object field) {
+        public DotProduct(ScoreScript scoreScript, List<Number> queryVector, String field) {
             super(scoreScript, queryVector, field);
         }
 
@@ -171,7 +158,7 @@ public double dotProduct() {
     // Calculate cosine similarity between a query's dense vector and documents' dense vectors
     public static final class CosineSimilarity extends DenseVectorFunction {
 
-        public CosineSimilarity(ScoreScript scoreScript, List<Number> queryVector, Object field) {
+        public CosineSimilarity(ScoreScript scoreScript, List<Number> queryVector, String field) {
             super(scoreScript, queryVector, field, true);
         }
 
@@ -214,8 +201,10 @@ public static class SparseVectorFunction {
         // queryVector represents a map of dimensions to values
         public SparseVectorFunction(ScoreScript scoreScript,
                                     Map<String, Number> queryVector,
-                                    Object field) {
+                                    String field) {
             this.scoreScript = scoreScript;
+            this.docValues = (SparseVectorScriptDocValues) scoreScript.getDoc().get(field);
+
             //break vector into two arrays dims and values
             int n = queryVector.size();
             queryValues = new float[n];
@@ -232,18 +221,6 @@ public SparseVectorFunction(ScoreScript scoreScript,
             }
             // Sort dimensions in the ascending order and sort values in the same order as their corresponding dimensions
             sortSparseDimsFloatValues(queryDims, queryValues, n);
-
-            if (field instanceof String) {
-                String fieldName = (String) field;
-                docValues = (SparseVectorScriptDocValues) scoreScript.getDoc().get(fieldName);
-            } else if (field instanceof SparseVectorScriptDocValues) {
-                docValues = (SparseVectorScriptDocValues) field;
-                deprecationLogger.deprecatedAndMaybeLog("vector_function_signature", DEPRECATION_MESSAGE);
-            } else {
-                throw new IllegalArgumentException("For vector functions, the 'field' argument must be of type String or " +
-                    "VectorScriptDocValues");
-            }
-
             deprecationLogger.deprecatedAndMaybeLog("sparse_vector_function", SparseVectorFieldMapper.DEPRECATION_MESSAGE);
         }
 
@@ -264,8 +241,8 @@ BytesRef getEncodedVector() {
 
     // Calculate l1 norm (Manhattan distance) between a query's sparse vector and documents' sparse vectors
     public static final class L1NormSparse extends SparseVectorFunction {
-        public L1NormSparse(ScoreScript scoreScript,Map<String, Number> queryVector, Object docVector) {
-            super(scoreScript, queryVector, docVector);
+        public L1NormSparse(ScoreScript scoreScript,Map<String, Number> queryVector, String field) {
+            super(scoreScript, queryVector, field);
         }
 
         public double l1normSparse() {
@@ -303,8 +280,8 @@ public double l1normSparse() {
 
     // Calculate l2 norm (Euclidean distance) between a query's sparse vector and documents' sparse vectors
     public static final class L2NormSparse extends SparseVectorFunction {
-        public L2NormSparse(ScoreScript scoreScript, Map<String, Number> queryVector, Object docVector) {
-           super(scoreScript, queryVector, docVector);
+        public L2NormSparse(ScoreScript scoreScript, Map<String, Number> queryVector, String field) {
+           super(scoreScript, queryVector, field);
         }
 
         public double l2normSparse() {
@@ -345,8 +322,8 @@ public double l2normSparse() {
 
     // Calculate a dot product between a query's sparse vector and documents' sparse vectors
     public static final class DotProductSparse extends SparseVectorFunction {
-        public DotProductSparse(ScoreScript scoreScript, Map<String, Number> queryVector, Object docVector) {
-           super(scoreScript, queryVector, docVector);
+        public DotProductSparse(ScoreScript scoreScript, Map<String, Number> queryVector, String field) {
+           super(scoreScript, queryVector, field);
         }
 
         public double dotProductSparse() {
@@ -362,8 +339,8 @@ public double dotProductSparse() {
     public static final class CosineSimilaritySparse extends SparseVectorFunction {
         final double queryVectorMagnitude;
 
-        public CosineSimilaritySparse(ScoreScript scoreScript, Map<String, Number> queryVector, Object docVector) {
-            super(scoreScript, queryVector, docVector);
+        public CosineSimilaritySparse(ScoreScript scoreScript, Map<String, Number> queryVector, String field) {
+            super(scoreScript, queryVector, field);
             double dotProduct = 0;
             for (int i = 0; i< queryDims.length; i++) {
                 dotProduct +=  queryValues[i] *  queryValues[i];

x-pack/plugin/vectors/src/main/resources/org/elasticsearch/xpack/vectors/query/whitelist.txt

@@ -13,12 +13,12 @@ class org.elasticsearch.script.ScoreScript @no_import {
 }
 
 static_import {
-    double l1norm(org.elasticsearch.script.ScoreScript, List, Object) bound_to org.elasticsearch.xpack.vectors.query.ScoreScriptUtils$L1Norm
-    double l2norm(org.elasticsearch.script.ScoreScript, List, Object) bound_to org.elasticsearch.xpack.vectors.query.ScoreScriptUtils$L2Norm
-    double cosineSimilarity(org.elasticsearch.script.ScoreScript, List, Object) bound_to org.elasticsearch.xpack.vectors.query.ScoreScriptUtils$CosineSimilarity
-    double dotProduct(org.elasticsearch.script.ScoreScript, List, Object) bound_to org.elasticsearch.xpack.vectors.query.ScoreScriptUtils$DotProduct
-    double l1normSparse(org.elasticsearch.script.ScoreScript, Map, Object) bound_to org.elasticsearch.xpack.vectors.query.ScoreScriptUtils$L1NormSparse
-    double l2normSparse(org.elasticsearch.script.ScoreScript, Map, Object) bound_to org.elasticsearch.xpack.vectors.query.ScoreScriptUtils$L2NormSparse
-    double dotProductSparse(org.elasticsearch.script.ScoreScript, Map, Object) bound_to org.elasticsearch.xpack.vectors.query.ScoreScriptUtils$DotProductSparse
-    double cosineSimilaritySparse(org.elasticsearch.script.ScoreScript, Map, Object) bound_to org.elasticsearch.xpack.vectors.query.ScoreScriptUtils$CosineSimilaritySparse
+    double l1norm(org.elasticsearch.script.ScoreScript, List, String) bound_to org.elasticsearch.xpack.vectors.query.ScoreScriptUtils$L1Norm
+    double l2norm(org.elasticsearch.script.ScoreScript, List, String) bound_to org.elasticsearch.xpack.vectors.query.ScoreScriptUtils$L2Norm
+    double cosineSimilarity(org.elasticsearch.script.ScoreScript, List, String) bound_to org.elasticsearch.xpack.vectors.query.ScoreScriptUtils$CosineSimilarity
+    double dotProduct(org.elasticsearch.script.ScoreScript, List, String) bound_to org.elasticsearch.xpack.vectors.query.ScoreScriptUtils$DotProduct
+    double l1normSparse(org.elasticsearch.script.ScoreScript, Map, String) bound_to org.elasticsearch.xpack.vectors.query.ScoreScriptUtils$L1NormSparse
+    double l2normSparse(org.elasticsearch.script.ScoreScript, Map, String) bound_to org.elasticsearch.xpack.vectors.query.ScoreScriptUtils$L2NormSparse
+    double dotProductSparse(org.elasticsearch.script.ScoreScript, Map, String) bound_to org.elasticsearch.xpack.vectors.query.ScoreScriptUtils$DotProductSparse
+    double cosineSimilaritySparse(org.elasticsearch.script.ScoreScript, Map, String) bound_to org.elasticsearch.xpack.vectors.query.ScoreScriptUtils$CosineSimilaritySparse
 }

x-pack/plugin/vectors/src/test/java/org/elasticsearch/xpack/vectors/query/DenseVectorFunctionTests.java

@@ -50,68 +50,48 @@ public void testDenseVectorFunctions() {
             when(scoreScript._getIndexVersion()).thenReturn(indexVersion);
             when(scoreScript.getDoc()).thenReturn(Collections.singletonMap(field, docValues));
 
-            testDotProduct(docValues, scoreScript);
-            testCosineSimilarity(docValues, scoreScript);
-            testL1Norm(docValues, scoreScript);
-            testL2Norm(docValues, scoreScript);
+            testDotProduct(scoreScript);
+            testCosineSimilarity(scoreScript);
+            testL1Norm(scoreScript);
+            testL2Norm(scoreScript);
         }
     }
 
-    private void testDotProduct(DenseVectorScriptDocValues docValues, ScoreScript scoreScript) {
+    private void testDotProduct(ScoreScript scoreScript) {
         DotProduct function = new DotProduct(scoreScript, queryVector, field);
         double result = function.dotProduct();
         assertEquals("dotProduct result is not equal to the expected value!", 65425.624, result, 0.001);
 
-        DotProduct deprecatedFunction = new DotProduct(scoreScript, queryVector, docValues);
-        double deprecatedResult = deprecatedFunction.dotProduct();
-        assertEquals("dotProduct result is not equal to the expected value!", 65425.624, deprecatedResult, 0.001);
-        assertWarnings(ScoreScriptUtils.DEPRECATION_MESSAGE);
-
         DotProduct invalidFunction = new DotProduct(scoreScript, invalidQueryVector, field);
         IllegalArgumentException e = expectThrows(IllegalArgumentException.class, invalidFunction::dotProduct);
         assertThat(e.getMessage(), containsString("query vector has a different number of dimensions [2] than the document vectors [5]"));
     }
 
-    private void testCosineSimilarity(DenseVectorScriptDocValues docValues, ScoreScript scoreScript) {
+    private void testCosineSimilarity(ScoreScript scoreScript) {
         CosineSimilarity function = new CosineSimilarity(scoreScript, queryVector, field);
         double result = function.cosineSimilarity();
         assertEquals("cosineSimilarity result is not equal to the expected value!", 0.790, result, 0.001);
 
-        CosineSimilarity deprecatedFunction = new CosineSimilarity(scoreScript, queryVector, docValues);
-        double deprecatedResult = deprecatedFunction.cosineSimilarity();
-        assertEquals("cosineSimilarity result is not equal to the expected value!", 0.790, deprecatedResult, 0.001);
-        assertWarnings(ScoreScriptUtils.DEPRECATION_MESSAGE);
-
         CosineSimilarity invalidFunction = new CosineSimilarity(scoreScript, invalidQueryVector, field);
         IllegalArgumentException e = expectThrows(IllegalArgumentException.class, invalidFunction::cosineSimilarity);
         assertThat(e.getMessage(), containsString("query vector has a different number of dimensions [2] than the document vectors [5]"));
     }
 
-    private void testL1Norm(DenseVectorScriptDocValues docValues, ScoreScript scoreScript) {
+    private void testL1Norm(ScoreScript scoreScript) {
         L1Norm function = new L1Norm(scoreScript, queryVector, field);
         double result = function.l1norm();
         assertEquals("l1norm result is not equal to the expected value!", 485.184, result, 0.001);
 
-        L1Norm deprecatedFunction = new L1Norm(scoreScript, queryVector, docValues);
-        double deprecatedResult = deprecatedFunction.l1norm();
-        assertEquals("l1norm result is not equal to the expected value!", 485.184, deprecatedResult, 0.001);
-        assertWarnings(ScoreScriptUtils.DEPRECATION_MESSAGE);
-
         L1Norm invalidFunction = new L1Norm(scoreScript, invalidQueryVector, field);
         IllegalArgumentException e = expectThrows(IllegalArgumentException.class, invalidFunction::l1norm);
         assertThat(e.getMessage(), containsString("query vector has a different number of dimensions [2] than the document vectors [5]"));
     }
 
-    private void testL2Norm(DenseVectorScriptDocValues docValues, ScoreScript scoreScript) {
+    private void testL2Norm(ScoreScript scoreScript) {
         L2Norm function = new L2Norm(scoreScript, queryVector, field);
         double result = function.l2norm();
         assertEquals("l2norm result is not equal to the expected value!", 301.361, result, 0.001);
 
-        L2Norm deprecatedFunction = new L2Norm(scoreScript, queryVector, docValues);
-        double deprecatedResult = deprecatedFunction.l2norm();
-        assertEquals("l2norm result is not equal to the expected value!", 301.361, deprecatedResult, 0.001);
-        assertWarnings(ScoreScriptUtils.DEPRECATION_MESSAGE);
-
         L2Norm invalidFunction = new L2Norm(scoreScript, invalidQueryVector, field);
         IllegalArgumentException e = expectThrows(IllegalArgumentException.class, invalidFunction::l2norm);
         assertThat(e.getMessage(), containsString("query vector has a different number of dimensions [2] than the document vectors [5]"));