test global phase reranking with dummy evaluation

2 files changed, 14 insertions, 7 deletions

diff --git a/container-search/src/main/java/com/yahoo/search/ranking/GlobalPhaseRanker.java b/container-search/src/main/java/com/yahoo/search/ranking/GlobalPhaseRanker.java
index bb5a991c304..829d0c268e5 100644
--- a/container-search/src/main/java/com/yahoo/search/ranking/GlobalPhaseRanker.java
+++ b/container-search/src/main/java/com/yahoo/search/ranking/GlobalPhaseRanker.java
@@ -50,9 +50,7 @@ public class GlobalPhaseRanker {
         return Optional.empty();
     }
 
-    public void rerankHits(Query query, Result result, String schema) {
-        var setup = globalPhaseSetupFor(query, schema).orElse(null);
-        if (setup == null) return;
+    static void rerankHitsImpl(GlobalPhaseSetup setup, Query query, Result result) {
         var mainSpec = setup.globalPhaseEvalSpec;
         var mainSrc = withQueryPrep(mainSpec.evalSource(), mainSpec.fromQuery(), query);
         int rerankCount = resolveRerankCount(setup, query);
@@ -68,6 +66,13 @@ public class GlobalPhaseRanker {
         hideImplicitMatchFeatures(result, setup.matchFeaturesToHide);
     }
 
+    public void rerankHits(Query query, Result result, String schema) {
+        var setup = globalPhaseSetupFor(query, schema);
+        if (setup.isPresent()) {
+            rerankHitsImpl(setup.get(), query, result);
+        }
+    }
+
     static Supplier<Evaluator> withQueryPrep(Supplier<Evaluator> evalSource, List<String> queryFeatures, Query query) {
         var prepared = PreparedInput.findFromQuery(query, queryFeatures);
         Supplier<Evaluator> supplier = () -> {
@@ -80,7 +85,7 @@ public class GlobalPhaseRanker {
         return supplier;
     }
 
-    private void hideImplicitMatchFeatures(Result result, Collection<String> namesToHide) {
+    private static void hideImplicitMatchFeatures(Result result, Collection<String> namesToHide) {
         if (namesToHide.size() == 0) return;
         var filter = new MatchFeatureFilter(namesToHide);
         for (var iterator = result.hits().deepIterator(); iterator.hasNext();) {
@@ -94,7 +99,7 @@ public class GlobalPhaseRanker {
                     if (newValue.fieldCount() == 0) {
                         hit.removeField("matchfeatures");
                     } else {
-                        hit.setField("matchfeatures", newValue);
+                        hit.setField("matchfeatures", new FeatureData(newValue));
                     }
                 }
             }
@@ -106,7 +111,7 @@ public class GlobalPhaseRanker {
                 .flatMap(evaluator -> evaluator.getGlobalPhaseSetup(query.getRanking().getProfile()));
     }
 
-    private int resolveRerankCount(GlobalPhaseSetup setup, Query query) {
+    private static int resolveRerankCount(GlobalPhaseSetup setup, Query query) {
         if (setup == null) {
             // there is no global-phase at all (ignore override)
             return 0;
diff --git a/container-search/src/main/java/com/yahoo/search/ranking/PreparedInput.java b/container-search/src/main/java/com/yahoo/search/ranking/PreparedInput.java
index 5ab2d7160f9..346acccd916 100644
--- a/container-search/src/main/java/com/yahoo/search/ranking/PreparedInput.java
+++ b/container-search/src/main/java/com/yahoo/search/ranking/PreparedInput.java
@@ -30,7 +30,7 @@ record PreparedInput(String name, Tensor value) {
         for (String queryFeatureName : queryFeatures) {
             String needed = "query(" + queryFeatureName + ")";
             // searchers are recommended to place query features here:
-            var feature = rankFeatures.getTensor(queryFeatureName);
+            var feature = rankFeatures.getTensor(needed);
             if (feature.isPresent()) {
                 result.add(new PreparedInput(needed, feature.get()));
             } else {
@@ -38,6 +38,8 @@ record PreparedInput(String name, Tensor value) {
                 var objList = rankProps.get(queryFeatureName);
                 if (objList != null && objList.size() == 1 && objList.get(0) instanceof Tensor t) {
                     result.add(new PreparedInput(needed, t));
+                } else if (objList != null && objList.size() == 1 && objList.get(0) instanceof Double d) {
+                    result.add(new PreparedInput(needed, Tensor.from(d)));
                 } else {
                     throw new IllegalArgumentException("missing query feature: " + queryFeatureName);
                 }