Change l1 method name to l1Norm for painless extensions (#316)

opendistro-for-elasticsearch · Feb 3, 2021 · ba5c91d · ba5c91d
1 parent 9381e7e
commit ba5c91d
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Showing 4 changed files with 9 additions and 9 deletions.
diff --git a/src/main/java/com/amazon/opendistroforelasticsearch/knn/plugin/script/KNNScoringSpace.java b/src/main/java/com/amazon/opendistroforelasticsearch/knn/plugin/script/KNNScoringSpace.java
@@ -168,7 +168,7 @@ public L1(Object query, MappedFieldType fieldType) {
 
             this.processedQuery = parseToFloatArray(query,
                     ((KNNVectorFieldMapper.KNNVectorFieldType) fieldType).getDimension());
-            this.scoringMethod = (float[] q, float[] v) -> 1 / (1 + KNNScoringUtil.l1distance(q, v));
+            this.scoringMethod = (float[] q, float[] v) -> 1 / (1 + KNNScoringUtil.l1Norm(q, v));
         }
 
         public ScoreScript getScoreScript(Map<String, Object> params, String field, SearchLookup lookup,

diff --git a/src/main/java/com/amazon/opendistroforelasticsearch/knn/plugin/script/KNNScoringUtil.java b/src/main/java/com/amazon/opendistroforelasticsearch/knn/plugin/script/KNNScoringUtil.java
@@ -217,7 +217,7 @@ public static float calculateHammingBit(Long queryLong, Long inputLong) {
      * @param inputVector input vector
      * @return L1 score
      */
-    public static float l1distance(float[] queryVector, float[] inputVector) {
+    public static float l1Norm(float[] queryVector, float[] inputVector) {
         requireEqualDimension(queryVector, inputVector);
         float distance = 0;
         for (int i = 0; i < inputVector.length; i++) {
@@ -232,7 +232,7 @@ public static float l1distance(float[] queryVector, float[] inputVector) {
      * and document vectors
      * Example
      *  "script": {
-     *         "source": "1/(1 + l1distance(params.query_vector, doc[params.field]))",
+     *         "source": "1/(1 + l1Norm(params.query_vector, doc[params.field]))",
      *         "params": {
      *           "query_vector": [1, 2, 3.4],
      *           "field": "my_dense_vector"
@@ -243,7 +243,7 @@ public static float l1distance(float[] queryVector, float[] inputVector) {
      * @param docValues   script doc values
      * @return L1 score
      */
-    public static float l1distance(List<Number> queryVector, KNNVectorScriptDocValues docValues) {
-        return l1distance(toFloat(queryVector), docValues.getValue());
+    public static float l1Norm(List<Number> queryVector, KNNVectorScriptDocValues docValues) {
+        return l1Norm(toFloat(queryVector), docValues.getValue());
     }
 }
diff --git a/src/main/resources/com/amazon/opendistroforelasticsearch/knn/plugin/script/knn_whitelist.txt b/src/main/resources/com/amazon/opendistroforelasticsearch/knn/plugin/script/knn_whitelist.txt
@@ -17,7 +17,7 @@ class com.amazon.opendistroforelasticsearch.knn.index.KNNVectorScriptDocValues {
 }
 static_import {
   float l2Squared(List, com.amazon.opendistroforelasticsearch.knn.index.KNNVectorScriptDocValues) from_class com.amazon.opendistroforelasticsearch.knn.plugin.script.KNNScoringUtil
-  float l1distance(List, com.amazon.opendistroforelasticsearch.knn.index.KNNVectorScriptDocValues) from_class com.amazon.opendistroforelasticsearch.knn.plugin.script.KNNScoringUtil
+  float l1Norm(List, com.amazon.opendistroforelasticsearch.knn.index.KNNVectorScriptDocValues) from_class com.amazon.opendistroforelasticsearch.knn.plugin.script.KNNScoringUtil
   float cosineSimilarity(List, com.amazon.opendistroforelasticsearch.knn.index.KNNVectorScriptDocValues) from_class com.amazon.opendistroforelasticsearch.knn.plugin.script.KNNScoringUtil
   float cosineSimilarity(List, com.amazon.opendistroforelasticsearch.knn.index.KNNVectorScriptDocValues, Number) from_class com.amazon.opendistroforelasticsearch.knn.plugin.script.KNNScoringUtil
 }
diff --git a/...java/com/amazon/opendistroforelasticsearch/knn/plugin/script/PainlessScriptScoringIT.java b/...java/com/amazon/opendistroforelasticsearch/knn/plugin/script/PainlessScriptScoringIT.java
@@ -256,15 +256,15 @@ public void testCosineSimilarityNormalizedScriptScoreWithNumericField() throws E
 
     // L1 tests
     public void testL1ScriptScoreFails() throws Exception {
-        String source = String.format("1/(1 + l1distance([1.0f, 1.0f], doc['%s']))", FIELD_NAME);
+        String source = String.format("1/(1 + l1Norm([1.0f, 1.0f], doc['%s']))", FIELD_NAME);
         Request request = buildPainlessScriptRequest(source, 3, getL1TestData());
         addDocWithNumericField(INDEX_NAME, "100", NUMERIC_INDEX_FIELD_NAME, 1000);
         expectThrows(ResponseException.class, () -> client().performRequest(request));
         deleteKNNIndex(INDEX_NAME);
     }
     public void testL1ScriptScore() throws Exception {
 
-        String source = String.format("1/(1 + l1distance([1.0f, 1.0f], doc['%s']))", FIELD_NAME);
+        String source = String.format("1/(1 + l1Norm([1.0f, 1.0f], doc['%s']))", FIELD_NAME);
         Request request = buildPainlessScriptRequest(source, 3, getL1TestData());
 
         Response response = client().performRequest(request);
@@ -285,7 +285,7 @@ public void testL1ScriptScore() throws Exception {
     public void testL1ScriptScoreWithNumericField() throws Exception {
 
         String source = String.format(
-                "doc['%s'].size() == 0 ? 0 : 1/(1 + l1distance([1.0f, 1.0f], doc['%s']))", FIELD_NAME, FIELD_NAME);
+                "doc['%s'].size() == 0 ? 0 : 1/(1 + l1Norm([1.0f, 1.0f], doc['%s']))", FIELD_NAME, FIELD_NAME);
         Request request = buildPainlessScriptRequest(source, 3, getL1TestData());
         addDocWithNumericField(INDEX_NAME, "100", NUMERIC_INDEX_FIELD_NAME, 1000);
         Response response = client().performRequest(request);