Add _validate_query_type_parameters function

Signed-off-by: Junqiu Lei <[email protected]>

osbenchmark/workload/params.py

@@ -1046,6 +1046,7 @@ class VectorSearchPartitionParamSource(VectorDataSetPartitionParamSource):
     MIN_SCORE_QUERY_TYPE = "min_score"
     MAX_DISTANCE_QUERY_TYPE = "max_distance"
     KNN_QUERY_TYPE = "knn"
+    RADIAL_SEARCH_QUERY_RESULT_SIZE = 10000
 
     def __init__(self, workloads, params, query_params, **kwargs):
         super().__init__(workloads, params, Context.QUERY, **kwargs)
@@ -1062,6 +1063,7 @@ def __init__(self, workloads, params, query_params, **kwargs):
         if self.PARAMS_NAME_MIN_SCORE in params:
             self.score = parse_float_parameter(self.PARAMS_NAME_MIN_SCORE, params)
             self.query_type = self.MIN_SCORE_QUERY_TYPE
+        self._validate_query_type_parameters()
         self.logger.info("query type is set up to %s", self.query_type)
         self.repetitions = parse_int_parameter(self.PARAMS_NAME_REPETITIONS, params, 1)
         self.current_rep = 1
@@ -1100,6 +1102,11 @@ def __init__(self, workloads, params, query_params, **kwargs):
             neighbors_corpora = self.extract_corpora(self.neighbors_data_set_corpus, self.neighbors_data_set_format)
             self.corpora.extend(corpora for corpora in neighbors_corpora if corpora not in self.corpora)
 
+    def _validate_query_type_parameters(self):
+        count = sum([self.k is not None, self.distance is not None, self.score is not None])
+        if count > 1:
+            raise ValueError("Only one of k, max_distance, or min_score can be specified in vector search.")
+
     @staticmethod
     def _validate_neighbors_data_set(file_path, corpus):
         if file_path and corpus:
@@ -1131,8 +1138,7 @@ def _update_body_params(self, vector):
             if self.query_type == self.KNN_QUERY_TYPE:
                 body_params[self.PARAMS_NAME_SIZE] = self.k
             else:
-                # if distance is set, set size to 10000, which is the maximum number results returned by default
-                body_params[self.PARAMS_NAME_SIZE] = 10000
+                body_params[self.PARAMS_NAME_SIZE] = self.RADIAL_SEARCH_QUERY_RESULT_SIZE
         if self.PARAMS_NAME_QUERY in body_params:
             self.logger.warning(
                 "[%s] param from body will be replaced with vector search query.", self.PARAMS_NAME_QUERY)