updates after review

5 files changed, 29 insertions, 27 deletions

diff --git a/container-search/abi-spec.json b/container-search/abi-spec.json
index ddd754ce419..2a03614396b 100644
--- a/container-search/abi-spec.json
+++ b/container-search/abi-spec.json
@@ -855,10 +855,10 @@
       "public"
     ],
     "methods": [
+      "public void <init>(java.lang.String, java.lang.String)",
       "public int getTargetNumHits()",
       "public java.lang.String getIndexName()",
-      "public java.lang.String getQueryRankFeatureName()",
-      "public void <init>(java.lang.String, java.lang.String)",
+      "public java.lang.String getQueryTensorName()",
       "public void setTargetNumHits(int)",
       "public void setIndexName(java.lang.String)",
       "public com.yahoo.prelude.query.Item$ItemType getItemType()",
diff --git a/container-search/src/main/java/com/yahoo/prelude/query/NearestNeighborItem.java b/container-search/src/main/java/com/yahoo/prelude/query/NearestNeighborItem.java
index 51a336fa4ba..35b87ec0190 100644
--- a/container-search/src/main/java/com/yahoo/prelude/query/NearestNeighborItem.java
+++ b/container-search/src/main/java/com/yahoo/prelude/query/NearestNeighborItem.java
@@ -9,9 +9,9 @@ import java.nio.ByteBuffer;
 
 /**
  * Represent a query item matching the K nearest neighbors in a multi-dimensional vector space.
- * The query point vector is referenced by the name of a tensor rank feature passed in the query,
- * so specifying "myvector" as the name means the query must set "ranking.features.query(myvector)",
- * which must be configured with the correct tensor type in the active query profile.
+ * The query point vector is referenced by the name of a tensor passed as a query rank feature;
+ * specifying "myvector" as the name means the query must set "ranking.features.query(myvector)".
+ * This rank feature must be configured with the correct tensor type in the active query profile.
  * The field name (AKA the index name) given must be an attribute, with the exact same tensor type.
  *
  * @author arnej
@@ -19,25 +19,26 @@ import java.nio.ByteBuffer;
 @Beta
 public class NearestNeighborItem extends SimpleTaggableItem {
 
-    private int targetNumber = 0;
+    private int targetNumHits = 0;
     private String field;
-    private String property;
+    private String queryTensorName;
 
-    /** @return the K number of hits to produce */
-    public int getTargetNumHits() { return targetNumber; }
+    public NearestNeighborItem(String fieldName, String queryTensorName) {
+        this.field = fieldName;
+        this.queryTensorName = queryTensorName;
+    }
 
-    /** @return the field name */
-    public String getIndexName() { return field; }
+    /** Returns the K number of hits to produce */
+    public int getTargetNumHits() { return targetNumHits; }
 
-    /** @return the name of the query ranking feature */
-    public String getQueryRankFeatureName() { return property; }
+    /** Returns the field name */
+    public String getIndexName() { return field; }
 
-    public NearestNeighborItem(String fieldName, String queryRankFeatureName) {
-        this.field = fieldName;
-        this.property = queryRankFeatureName;
-    }
+    /** Returns the name of the query tensor */
+    public String getQueryTensorName() { return queryTensorName; }
 
-    public void setTargetNumHits(int target) { this.targetNumber = target; }
+    /** Set the K number of hits to produce */
+    public void setTargetNumHits(int target) { this.targetNumHits = target; }
 
     @Override
     public void setIndexName(String index) { this.field = index; }
@@ -55,15 +56,15 @@ public class NearestNeighborItem extends SimpleTaggableItem {
     public int encode(ByteBuffer buffer) {
         super.encodeThis(buffer);
         putString(field, buffer);
-        putString(property, buffer);
-        IntegerCompressor.putCompressedPositiveNumber(targetNumber, buffer);
+        putString(queryTensorName, buffer);
+        IntegerCompressor.putCompressedPositiveNumber(targetNumHits, buffer);
         return 1;  // number of encoded stack dump items
     }
 
     @Override
     protected void appendBodyString(StringBuilder buffer) {
         buffer.append("{field=").append(field);
-        buffer.append(",property=").append(property);
-        buffer.append(",targetNumHits=").append(targetNumber).append("}");
+        buffer.append(",queryTensorName=").append(queryTensorName);
+        buffer.append(",targetNumHits=").append(targetNumHits).append("}");
     }
 }
diff --git a/container-search/src/main/java/com/yahoo/search/searchers/ValidateNearestNeighborSearcher.java b/container-search/src/main/java/com/yahoo/search/searchers/ValidateNearestNeighborSearcher.java
index c2e05b15f33..dfd8205cd05 100644
--- a/container-search/src/main/java/com/yahoo/search/searchers/ValidateNearestNeighborSearcher.java
+++ b/container-search/src/main/java/com/yahoo/search/searchers/ValidateNearestNeighborSearcher.java
@@ -1,4 +1,5 @@
-// Copyright 2017 Yahoo Holdings. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
+// Copyright 2019 Oath Inc. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
+
 package com.yahoo.search.searchers;
 
 import com.google.common.annotations.Beta;
@@ -84,7 +85,7 @@ public class ValidateNearestNeighborSearcher extends Searcher {
                 setError(item.toString() + " has invalid targetNumHits");
                 return;
             }
-            String qprop = item.getQueryRankFeatureName();
+            String qprop = item.getQueryTensorName();
             List<Object> rankPropValList = rankProperties.asMap().get(qprop);
             if (rankPropValList == null) {
                 setError(item.toString() + " query property not found");
diff --git a/container-search/src/main/java/com/yahoo/search/yql/VespaSerializer.java b/container-search/src/main/java/com/yahoo/search/yql/VespaSerializer.java
index 6ab07d95c76..6eef1252998 100644
--- a/container-search/src/main/java/com/yahoo/search/yql/VespaSerializer.java
+++ b/container-search/src/main/java/com/yahoo/search/yql/VespaSerializer.java
@@ -705,7 +705,7 @@ public class VespaSerializer {
             destination.append("}]");
             destination.append(NEAREST_NEIGHBOR).append('(');
             destination.append(item.getIndexName()).append(", ");
-            destination.append(item.getQueryRankFeatureName()).append(')');
+            destination.append(item.getQueryTensorName()).append(')');
             return false;
         }
 
diff --git a/container-search/src/test/java/com/yahoo/search/yql/YqlParserTestCase.java b/container-search/src/test/java/com/yahoo/search/yql/YqlParserTestCase.java
index e191829b875..5eb1f3e3de1 100644
--- a/container-search/src/test/java/com/yahoo/search/yql/YqlParserTestCase.java
+++ b/container-search/src/test/java/com/yahoo/search/yql/YqlParserTestCase.java
@@ -550,9 +550,9 @@ public class YqlParserTestCase {
     @Test
     public void testNearestNeighbor() {
         assertParse("select foo from bar where nearestNeighbor(semantic_embedding, my_vector);",
-                    "NEAREST_NEIGHBOR {field=semantic_embedding,property=my_vector,targetNumHits=0}");
+                    "NEAREST_NEIGHBOR {field=semantic_embedding,queryTensorName=my_vector,targetNumHits=0}");
         assertParse("select foo from bar where [{\"targetNumHits\": 37}]nearestNeighbor(semantic_embedding, my_vector);",
-                    "NEAREST_NEIGHBOR {field=semantic_embedding,property=my_vector,targetNumHits=37}");
+                    "NEAREST_NEIGHBOR {field=semantic_embedding,queryTensorName=my_vector,targetNumHits=37}");
     }
 
     @Test