fix: remove limitation clustering key can not be primary key

Signed-off-by: wayblink <[email protected]>
milvus-io · Jul 23, 2024 · 73b613f · 73b613f
1 parent 2a76769
commit 73b613f
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Showing 3 changed files with 45 additions and 10 deletions.
diff --git a/pymilvus/exceptions.py b/pymilvus/exceptions.py
@@ -220,7 +220,6 @@ class ExceptionsMessage:
         "Ambiguous parameter, either ids or filter should be specified, cannot support both."
     )
     JSONKeyMustBeStr = "JSON key must be str."
-    ClusteringKeyNotPrimary = "Clustering key field should not be primary field"
     ClusteringKeyType = (
         "Clustering key field type must be DataType.INT8, DataType.INT16, "
         "DataType.INT32, DataType.INT64, DataType.FLOAT, DataType.DOUBLE, "

diff --git a/pymilvus/orm/schema.py b/pymilvus/orm/schema.py
@@ -62,12 +62,8 @@ def validate_partition_key(
         )
 
 
-def validate_clustering_key(
-    clustering_key_field_name: Any, clustering_key_field: Any, primary_field_name: Any
-):
+def validate_clustering_key(clustering_key_field_name: Any, clustering_key_field: Any):
     if clustering_key_field is not None:
-        if clustering_key_field.name == primary_field_name:
-            raise ClusteringKeyException(message=ExceptionsMessage.ClusteringKeyNotPrimary)
         if clustering_key_field.dtype not in [
             DataType.INT8,
             DataType.INT16,
@@ -81,7 +77,7 @@ def validate_clustering_key(
             raise ClusteringKeyException(message=ExceptionsMessage.ClusteringKeyType)
     elif clustering_key_field_name is not None:
         raise ClusteringKeyException(
-            message=ExceptionsMessage.PartitionKeyFieldNotExist % clustering_key_field_name
+            message=ExceptionsMessage.ClusteringKeyFieldNotExist % clustering_key_field_name
         )
 
 
@@ -170,9 +166,7 @@ def _check_fields(self):
         validate_partition_key(
             partition_key_field_name, self._partition_key_field, self._primary_field.name
         )
-        validate_clustering_key(
-            clustering_key_field_name, self._clustering_key_field, self._primary_field.name
-        )
+        validate_clustering_key(clustering_key_field_name, self._clustering_key_field)
 
         auto_id = self._kwargs.get("auto_id", False)
         if auto_id:

diff --git a/tests/test_create_collection.py b/tests/test_create_collection.py
@@ -202,3 +202,45 @@ def test_create_bf16_collection(self, collection_name):
         return_value = future.result()
         assert return_value.code == 0
         assert return_value.reason == "success"
+
+    def test_create_clustering_key_collection(self, collection_name):
+        id_field = {
+            "name": "my_id",
+            "type": DataType.INT64,
+            "auto_id": True,
+            "is_primary": True,
+            "is_clustering_key": True,
+        }
+        vector_field = {
+            "name": "embedding",
+            "type": DataType.FLOAT_VECTOR,
+            "metric_type": "L2",
+            "params": {"dim": "4"},
+        }
+        fields = {"fields": [id_field, vector_field]}
+        future = self._milvus.create_collection(
+            collection_name=collection_name, fields=fields, _async=True
+        )
+
+        invocation_metadata, request, rpc = self._real_time_channel.take_unary_unary(
+            self._servicer.methods_by_name["CreateCollection"]
+        )
+        rpc.send_initial_metadata(())
+        rpc.terminate(
+            common_pb2.Status(
+                code=ErrorCode.SUCCESS, error_code=common_pb2.Success, reason="success"
+            ),
+            (),
+            grpc.StatusCode.OK,
+            "",
+        )
+
+        request_schema = schema_pb2.CollectionSchema()
+        request_schema.ParseFromString(request.schema)
+
+        assert request.collection_name == collection_name
+        assert Fields.equal(request_schema.fields, fields["fields"])
+
+        return_value = future.result()
+        assert return_value.code == 0
+        assert return_value.reason == "success"