added functionality to handle vector values in format of text or list of text,float,double

adapter-pinecone/src/main/java/io/nosqlbench/adapter/pinecone/PineconeSpace.java

@@ -65,7 +65,7 @@ public class PineconeSpace {
     }
 
     /**
-     * Connections are index-specific so we need to allow for multiple connection management across indices.
+     * Connections are index-specific, so we need to allow for multiple connection management across indices.
      * However, note that a single connection object is thread safe and can be used by multiple clients.
      *
      * @param index     The database index for which a connection is being requested

adapter-pinecone/src/main/java/io/nosqlbench/adapter/pinecone/opdispensers/PineconeDescribeIndexStatsOpDispenser.java

@@ -57,7 +57,7 @@ public class PineconeDescribeIndexStatsOpDispenser extends PineconeOpDispenser {
      * The pattern used here is to accommodate the way Request types are constructed for Pinecone.
      * Requests use a Builder pattern, so at time of instantiation the methods should be chained together.
      * For each method in the chain a function is created here and added to the chain of functions
-     * called at time of instantiation. Additionally some of the arguments to the builder methods require
+     * called at time of instantiation. Additionally, some of the arguments to the builder methods require
      * creation through their own builder process. In these cases the pattern adopted includes multiple layers of
      * functions in order to build all objects in the correct manner and ordering.
      */

adapter-pinecone/src/main/java/io/nosqlbench/adapter/pinecone/opdispensers/PineconeOpDispenser.java

@@ -76,15 +76,8 @@ public abstract class PineconeOpDispenser extends BaseOpDispenser<PineconeOp, Pi
         return listValueBuilder.build();
     }
 
-    protected LongFunction<ArrayList<Float>> extractFloatVals(LongFunction<String> af) {
-        return l -> {
-            String[] vals = af.apply(l).split(",");
-            ArrayList<Float> fVals = new ArrayList<>();
-            for (String val : vals) {
-                fVals.add(Float.valueOf(val));
-            }
-            return fVals;
-        };
+    protected LongFunction<List<Float>> extractFloatVals(LongFunction<Object> af) {
+        return l -> this.getVectorValues(af.apply(l));
     }
 
     protected Map<String, Value> generateMetadataMap(Map<String, Object> metadata_values_map) {
@@ -102,4 +95,41 @@ public abstract class PineconeOpDispenser extends BaseOpDispenser<PineconeOp, Pi
         return metadata_map;
     }
 
+    protected List<Float> getVectorValues(Object rawVectorValues) {
+        List<Float> floatValues;
+        if (rawVectorValues instanceof String) {
+            floatValues = new ArrayList<>();
+            String[] rawValues = (((String) rawVectorValues).split(","));
+            for (String val : rawValues) {
+                floatValues.add(Float.valueOf(val));
+            }
+        } else if (rawVectorValues instanceof List) {
+            floatValues = switch (((List<?>) rawVectorValues).get(0).getClass().getSimpleName()) {
+                case "Float" -> (List<Float>) rawVectorValues;
+                case "Double" -> ((List<Double>) rawVectorValues).stream().map(Double::floatValue).toList();
+                case "String" -> ((List<String>) rawVectorValues).stream().map(Float::parseFloat).toList();
+                default -> throw new RuntimeException("Invalid type specified for values");
+            };
+        } else {
+            throw new RuntimeException("Invalid type specified for values");
+        }
+        return floatValues;
+    }
+
+    protected List<Integer> getIndexValues(Object rawIndexValues) {
+        List<Integer> intValues;
+        if (rawIndexValues instanceof String) {
+            intValues = new ArrayList<>();
+            String[] rawValues = (((String) rawIndexValues).split(","));
+            for (String val : rawValues) {
+                intValues.add(Integer.valueOf(val));
+            }
+        } else if (rawIndexValues instanceof List) {
+            intValues = (List<Integer>) rawIndexValues;
+        }else {
+            throw new RuntimeException("Invalid type specified for Index values");
+        }
+        return intValues;
+    }
+
 }

adapter-pinecone/src/main/java/io/nosqlbench/adapter/pinecone/opdispensers/PineconeQueryOpDispenser.java

@@ -98,12 +98,12 @@ public class PineconeQueryOpDispenser extends PineconeOpDispenser {
             rFunc = l -> finalFunc.apply(l).setIncludeValues(af.apply(l));
         }
 
-        Optional<LongFunction<String>> vFunc = op.getAsOptionalFunction("vector", String.class);
+        Optional<LongFunction<Object>> vFunc = op.getAsOptionalFunction("vector", Object.class);
         if (vFunc.isPresent()) {
             LongFunction<QueryRequest.Builder> finalFunc = rFunc;
-            LongFunction<String> af = vFunc.get();
+            LongFunction<Object> af = vFunc.get();
 
-            LongFunction<ArrayList<Float>> alf = extractFloatVals(af);
+            LongFunction<List<Float>> alf = extractFloatVals(af);
             rFunc = l -> finalFunc.apply(l).addAllVector(alf.apply(l));
         }
 
@@ -135,12 +135,7 @@ public class PineconeQueryOpDispenser extends PineconeOpDispenser {
             List<Map<String, Object>> vectors = listLongFunction.apply(l);
             for (Map<String, Object> vector : vectors) {
                 QueryVector.Builder qvb = QueryVector.newBuilder();
-                String[] rawValues = ((String) vector.get("values")).split(",");
-                ArrayList<Float> floatValues = new ArrayList<>();
-                for (String val : rawValues) {
-                    floatValues.add(Float.valueOf(val));
-                }
-                qvb.addAllValues(floatValues);
+                qvb.addAllValues(getVectorValues(vector.get("values")));
                 qvb.setNamespace((String) vector.get("namespace"));
                 if (vector.containsKey("top_k")) {
                     qvb.setTopK((Integer) vector.get("top_k"));
@@ -151,19 +146,9 @@ public class PineconeQueryOpDispenser extends PineconeOpDispenser {
                 }
                 if (vector.containsKey("sparse_values")) {
                     Map<String,String> sparse_values = (Map<String, String>) vector.get("sparse_values");
-                    rawValues = sparse_values.get("values").split(",");
-                    floatValues = new ArrayList<>();
-                    for (String val : rawValues) {
-                        floatValues.add(Float.valueOf(val));
-                    }
-                    rawValues = sparse_values.get("indices").split(",");
-                    List<Integer> intValues = new ArrayList<>();
-                    for (String val : rawValues) {
-                        intValues.add(Integer.valueOf(val));
-                    }
                     qvb.setSparseValues(SparseValues.newBuilder()
-                        .addAllValues(floatValues)
-                        .addAllIndices(intValues)
+                        .addAllValues(getVectorValues(sparse_values.get("values")))
+                        .addAllIndices(getIndexValues(sparse_values.get("indices")))
                         .build());
                 }
                 returnVectors.add(qvb.build());

adapter-pinecone/src/main/java/io/nosqlbench/adapter/pinecone/opdispensers/PineconeUpdateOpDispenser.java

@@ -17,7 +17,6 @@
 package io.nosqlbench.adapter.pinecone.opdispensers;
 
 import com.google.protobuf.Struct;
-import com.google.protobuf.Value;
 import io.nosqlbench.adapter.pinecone.PineconeDriverAdapter;
 import io.nosqlbench.adapter.pinecone.PineconeSpace;
 import io.nosqlbench.adapter.pinecone.ops.PineconeOp;
@@ -28,8 +27,9 @@ import io.pinecone.proto.UpdateRequest;
 import org.apache.logging.log4j.LogManager;
 import org.apache.logging.log4j.Logger;
 
-import java.util.*;
-import java.util.function.BiConsumer;
+import java.util.List;
+import java.util.Map;
+import java.util.Optional;
 import java.util.function.LongFunction;
 
 public class PineconeUpdateOpDispenser extends PineconeOpDispenser {
@@ -69,19 +69,9 @@ public class PineconeUpdateOpDispenser extends PineconeOpDispenser {
         Optional<LongFunction<Map>> mFunc = op.getAsOptionalFunction("sparse_values", Map.class);
         return mFunc.<LongFunction<SparseValues>>map(mapLongFunction -> l -> {
             Map<String, String> sparse_values_map = mapLongFunction.apply(l);
-            String[] rawValues = (sparse_values_map.get("values")).split(",");
-            ArrayList floatValues = new ArrayList<>();
-            for (String val : rawValues) {
-                floatValues.add(Float.valueOf(val));
-            }
-            rawValues = sparse_values_map.get("indices").split(",");
-            List<Integer> intValues = new ArrayList<>();
-            for (String val : rawValues) {
-                intValues.add(Integer.valueOf(val));
-            }
             return SparseValues.newBuilder()
-                .addAllValues(floatValues)
-                .addAllIndices(intValues)
+                .addAllValues(getVectorValues(sparse_values_map.get("values")))
+                .addAllIndices(getIndexValues(sparse_values_map.get("indices")))
                 .build();
         }).orElse(null);
     }
@@ -134,11 +124,11 @@ public class PineconeUpdateOpDispenser extends PineconeOpDispenser {
             rFunc = l -> finalFunc.apply(l).setId(af.apply(l));
         }
 
-        Optional<LongFunction<String>> vFunc = op.getAsOptionalFunction("values", String.class);
+        Optional<LongFunction<Object>> vFunc = op.getAsOptionalFunction("values", Object.class);
         if (vFunc.isPresent()) {
             LongFunction<UpdateRequest.Builder> finalFunc = rFunc;
-            LongFunction<String> af = vFunc.get();
-            LongFunction<ArrayList<Float>> alf = extractFloatVals(af);
+            LongFunction<Object> af = vFunc.get();
+            LongFunction<List<Float>> alf = extractFloatVals(af);
             rFunc = l -> finalFunc.apply(l).addAllValues(alf.apply(l));
         }
 

adapter-pinecone/src/main/java/io/nosqlbench/adapter/pinecone/opdispensers/PineconeUpsertOpDispenser.java

@@ -16,9 +16,7 @@
 
 package io.nosqlbench.adapter.pinecone.opdispensers;
 
-import com.google.protobuf.ListValue;
 import com.google.protobuf.Struct;
-import com.google.protobuf.Value;
 import io.nosqlbench.adapter.pinecone.PineconeDriverAdapter;
 import io.nosqlbench.adapter.pinecone.PineconeSpace;
 import io.nosqlbench.adapter.pinecone.ops.PineconeOp;
@@ -31,7 +29,6 @@ import org.apache.logging.log4j.LogManager;
 import org.apache.logging.log4j.Logger;
 
 import java.util.*;
-import java.util.function.BiConsumer;
 import java.util.function.LongFunction;
 
 public class PineconeUpsertOpDispenser extends PineconeOpDispenser {
@@ -75,27 +72,12 @@ public class PineconeUpsertOpDispenser extends PineconeOpDispenser {
                 Vector.Builder vb = Vector.newBuilder();
                 // No need to check for key, it is invalid if id is not there, let it throw an exception
                 vb.setId(vector.get("id").toString());
-                String[] rawValues = ((String) vector.get("values")).split(",");
-                ArrayList<Float> floatValues = new ArrayList<>();
-                for (String val : rawValues) {
-                    floatValues.add(Float.valueOf(val));
-                }
-                vb.addAllValues(floatValues);
+                vb.addAllValues(getVectorValues(vector.get("values")));
                 if (vector.containsKey("sparse_values")) {
                     Map<String,String> sparse_values = (Map<String, String>) vector.get("sparse_values");
-                    rawValues = sparse_values.get("values").split(",");
-                    floatValues = new ArrayList<>();
-                    for (String val : rawValues) {
-                        floatValues.add(Float.valueOf(val));
-                    }
-                    rawValues = sparse_values.get("indices").split(",");
-                    List<Integer> intValues = new ArrayList<>();
-                    for (String val : rawValues) {
-                        intValues.add(Integer.valueOf(val));
-                    }
                     vb.setSparseValues(SparseValues.newBuilder()
-                        .addAllValues(floatValues)
-                        .addAllIndices(intValues)
+                        .addAllValues(getVectorValues(sparse_values.get("values")))
+                        .addAllIndices(getIndexValues(sparse_values.get("indices")))
                         .build());
                 }
                 if (vector.containsKey("metadata")) {

adapter-pinecone/src/main/resources/activities/pinecone-query-multiple.yaml

@@ -18,7 +18,17 @@ blocks:
               operator: "$eq"
               comparator: "movies"
           - id: "2"
-            values: "0.8602578079921012,0.12103044768221516,0.7737329191858439,0.4521093269320254,0.29351661477669416,0.4261807015226558,0.14131665592103335,0.882370813029422,0.4412833140430886,0.9916525700115515"
+            values:
+              - 0.8602578079921012
+              - 0.12103044768221516
+              - 0.7737329191858439
+              - 0.4521093269320254
+              - 0.29351661477669416
+              - 0.4261807015226558
+              - 0.14131665592103335
+              - 0.882370813029422
+              - 0.4412833140430886
+              - 0.9916525700115515
             namespace: "example_namespace"
             top_k: 3
             filter:

adapter-pinecone/src/main/resources/activities/pinecone-upsert-scenario.yaml

@@ -1,10 +1,11 @@
 scenarios:
   default:
-    upsert: run driver=pinecone tags==blocks:upsert cycles=1000 cycles===TEMPLATE(rampup-cycles,10000000) threads=auto
+    upsert: run driver=pinecone tags==block:upsert cycles===TEMPLATE(upsert-cycles,10000000) threads=auto
+    query: run driver=pinecone tags==block:query cycles===TEMPLATE(query-cycles,10000000) threads=auto
 
 bindings:
   id: Mod(<<keycount:1000000000>>); ToString() -> String
-  vector_value: ListSizedHashed(<<dimensions:5>>,HashRange(0.0f,100.0f) -> float); ToString() -> String
+  vector_value: ListSizedHashed(<<dimensions:5>>,HashRange(0.0f,100.0f) -> float)
   city: Cities()
 
 blocks:
@@ -14,7 +15,7 @@ blocks:
         upsert: "test-index"
         namespace: "example_namespace"
         upsert_vectors:
-          - id: {id}
-            values: {vector_value}
+          - id: "{id}"
+            values: "{vector_value}"
             metadata:
-              city: {city}
+              city: "{city}"

adapter-pinecone/src/main/resources/activities/pinecone-upsert.yaml

@@ -10,7 +10,17 @@ blocks:
         namespace: "example_namespace"
         upsert_vectors:
           - id: "item_0"
-            values: "0.8238042071878214,0.6579519242642494,0.2772098082162267,0.11434681368630942,0.7496610470760962,0.08914691629812001,0.13249049306247204,0.8875869003282576,0.21615924382746318,0.8454796243176312"
+            values:
+              - 0.8238042071878214
+              - 0.6579519242642494
+              - 0.2772098082162267
+              - 0.11434681368630942
+              - 0.7496610470760962
+              - 0.08914691629812001
+              - 0.13249049306247204
+              - 0.8875869003282576
+              - 0.21615924382746318
+              - 0.8454796243176312
             metadata:
               category: "sports"
               colors: "blue,red,green"

adapter-pinecone/src/test/java/io/nosqlbench/adapter/pinecone/PineconeOpMapperTest.java

@@ -198,7 +198,10 @@ public class PineconeOpMapperTest {
                 index: "test-index"
                 upsert_vectors:
                  - id: 1
-                   values: "1.0,2.0,3.0"
+                   values:
+                     - 1.0
+                     - 2.0
+                     - 3.0
                    sparse_values:
                      indices: "1,2,3"
                      values: "4.0,5.0,6.0"
@@ -206,7 +209,10 @@ public class PineconeOpMapperTest {
                      key1: "val1"
                      key2: 2
                  - id: 2
-                   values: "7.0,8.0,9.0"
+                   values:
+                     - 7.0
+                     - 8.0
+                     - 9.0
                    sparse_values:
                      indices: "4,5,6"
                      values: "1.1,2.2,3.3"