Resolve slice dimension

5 files changed, 43 insertions, 11 deletions

diff --git a/config-model/src/main/java/com/yahoo/searchdefinition/MapEvaluationTypeContext.java b/config-model/src/main/java/com/yahoo/searchdefinition/MapEvaluationTypeContext.java
index fef7ff56763..08475813317 100644
--- a/config-model/src/main/java/com/yahoo/searchdefinition/MapEvaluationTypeContext.java
+++ b/config-model/src/main/java/com/yahoo/searchdefinition/MapEvaluationTypeContext.java
@@ -104,7 +104,6 @@ public class MapEvaluationTypeContext extends FunctionReferenceContext implement
     @Override
     public TensorType getType(Reference reference) {
         // computeIfAbsent without concurrent modification due to resolve adding more resolved entries:
-
         boolean canBeResolvedGlobally = referenceCanBeResolvedGlobally(reference);
 
         TensorType resolvedType = resolvedTypes.get(reference);
diff --git a/config-model/src/main/java/com/yahoo/searchdefinition/RankProfile.java b/config-model/src/main/java/com/yahoo/searchdefinition/RankProfile.java
index 5b842b002bd..49c52b21907 100644
--- a/config-model/src/main/java/com/yahoo/searchdefinition/RankProfile.java
+++ b/config-model/src/main/java/com/yahoo/searchdefinition/RankProfile.java
@@ -998,7 +998,8 @@ public class RankProfile implements Cloneable {
         return featureTypes;
     }
     
-    public MapEvaluationTypeContext typeContext(QueryProfileRegistry queryProfiles, Map<Reference, TensorType> featureTypes) {
+    public MapEvaluationTypeContext typeContext(QueryProfileRegistry queryProfiles,
+                                                Map<Reference, TensorType> featureTypes) {
         MapEvaluationTypeContext context = new MapEvaluationTypeContext(getExpressionFunctions(), featureTypes);
 
         // Add small and large constants, respectively
diff --git a/config-model/src/main/java/com/yahoo/searchdefinition/derived/RawRankProfile.java b/config-model/src/main/java/com/yahoo/searchdefinition/derived/RawRankProfile.java
index 75703c33f07..9370075bcf3 100644
--- a/config-model/src/main/java/com/yahoo/searchdefinition/derived/RawRankProfile.java
+++ b/config-model/src/main/java/com/yahoo/searchdefinition/derived/RawRankProfile.java
@@ -63,8 +63,8 @@ public class RawRankProfile implements RankProfilesConfig.Producer {
                           QueryProfileRegistry queryProfiles, ImportedMlModels importedModels,
                           AttributeFields attributeFields, ModelContext.Properties deployProperties) {
         this.name = rankProfile.name();
-        compressedProperties = compress(new Deriver(rankProfile.compile(queryProfiles, importedModels),
-                                                    attributeFields, deployProperties).derive(largeExpressions));
+        compressedProperties = compress(new Deriver(rankProfile.compile(queryProfiles, importedModels), attributeFields, deployProperties, queryProfiles)
+                                                .derive(largeExpressions));
     }
 
     private Compressor.Compression compress(List<Pair<String, String>> properties) {
@@ -156,7 +156,10 @@ public class RawRankProfile implements RankProfilesConfig.Producer {
         /**
          * Creates a raw rank profile from the given rank profile
          */
-        Deriver(RankProfile compiled, AttributeFields attributeFields, ModelContext.Properties deployProperties) {
+        Deriver(RankProfile compiled,
+                AttributeFields attributeFields,
+                ModelContext.Properties deployProperties,
+                QueryProfileRegistry queryProfiles) {
             rankprofileName = compiled.name();
             attributeTypes = compiled.getAttributeTypes();
             queryFeatureTypes = compiled.getQueryFeatureTypes();
@@ -179,7 +182,9 @@ public class RawRankProfile implements RankProfilesConfig.Producer {
             Map<String, RankProfile.RankingExpressionFunction> functions = compiled.getFunctions();
             List<ExpressionFunction> functionExpressions = functions.values().stream().map(f -> f.function()).collect(Collectors.toList());
             Map<String, String> functionProperties = new LinkedHashMap<>();
-            SerializationContext functionSerializationContext = new SerializationContext(functionExpressions);
+            SerializationContext functionSerializationContext = new SerializationContext(functionExpressions,
+                                                                                         Map.of(),
+                                                                                         compiled.typeContext(queryProfiles));
 
             if (firstPhaseRanking != null) {
                 functionProperties.putAll(firstPhaseRanking.getRankProperties(functionSerializationContext));
@@ -201,8 +206,8 @@ public class RawRankProfile implements RankProfilesConfig.Producer {
         }
 
         private void derivePropertiesAndFeaturesFromFunctions(Map<String, RankProfile.RankingExpressionFunction> functions,
-                                                                     Map<String, String> functionProperties,
-                                                                     SerializationContext functionContext) {
+                                                              Map<String, String> functionProperties,
+                                                              SerializationContext functionContext) {
             if (functions.isEmpty()) return;
 
             replaceFunctionFeatures(summaryFeatures, functionContext);
diff --git a/config-model/src/test/derived/slice/rank-profiles.cfg b/config-model/src/test/derived/slice/rank-profiles.cfg
new file mode 100644
index 00000000000..75725b81ecf
--- /dev/null
+++ b/config-model/src/test/derived/slice/rank-profiles.cfg
@@ -0,0 +1,25 @@
+rankprofile[].name "default"
+rankprofile[].fef.property[].name "vespa.type.query.myTensor"
+rankprofile[].fef.property[].value "tensor<float>(key{})"
+rankprofile[].name "unranked"
+rankprofile[].fef.property[].name "vespa.rank.firstphase"
+rankprofile[].fef.property[].value "value(0)"
+rankprofile[].fef.property[].name "vespa.hitcollector.heapsize"
+rankprofile[].fef.property[].value "0"
+rankprofile[].fef.property[].name "vespa.hitcollector.arraysize"
+rankprofile[].fef.property[].value "0"
+rankprofile[].fef.property[].name "vespa.dump.ignoredefaultfeatures"
+rankprofile[].fef.property[].value "true"
+rankprofile[].fef.property[].name "vespa.type.query.myTensor"
+rankprofile[].fef.property[].value "tensor<float>(key{})"
+rankprofile[].name "parent"
+rankprofile[].fef.property[].name "rankingExpression(mySlice@77dee0712164ce73).rankingScript"
+rankprofile[].fef.property[].value "query(myTensor){key:MY_KEY2}"
+rankprofile[].fef.property[].name "rankingExpression(myFunction).rankingScript"
+rankprofile[].fef.property[].value "4 * query(myTensor){key:MY_KEY1} * rankingExpression(mySlice@77dee0712164ce73)"
+rankprofile[].fef.property[].name "rankingExpression(myValue).rankingScript"
+rankprofile[].fef.property[].value "4"
+rankprofile[].fef.property[].name "rankingExpression(mySlice).rankingScript"
+rankprofile[].fef.property[].value "myTensor{key:MY_KEY2}"
+rankprofile[].fef.property[].name "vespa.type.query.myTensor"
+rankprofile[].fef.property[].value "tensor<float>(key{})"
diff --git a/config-model/src/test/derived/slice/test.sd b/config-model/src/test/derived/slice/test.sd
index fbb581d1b1d..c2060300785 100644
--- a/config-model/src/test/derived/slice/test.sd
+++ b/config-model/src/test/derived/slice/test.sd
@@ -5,8 +5,8 @@ search test {
 
     rank-profile parent {
 
-        function inline cpmScore() {
-            expression: myValue * mySlice(query(myTensor))
+        function inline myFunction() {
+            expression: myValue * query(myTensor){MY_KEY1} * mySlice(query(myTensor))
         }
 
         function inline myValue() {
@@ -14,7 +14,9 @@ search test {
         }
 
         function inline mySlice(myTensor) {
-            expression: myTensor{"NULL"}
+            # TODO: We are missing type resolving across function calls in serialization,
+            #       so using the short form (without 'key') here will fail
+            expression: myTensor{key:MY_KEY2}
         }
     }