diff --git a/osbenchmark/worker_coordinator/runner.py b/osbenchmark/worker_coordinator/runner.py
index ece6c7fb0..3ed101bfe 100644
--- a/osbenchmark/worker_coordinator/runner.py
+++ b/osbenchmark/worker_coordinator/runner.py
@@ -1318,7 +1318,7 @@ def calculate_radial_search_recall(predictions, neighbors, enable_top_1_recall=F
                     if predictions[j] in truth_set:
                         correct += 1.0
 
-                return float(correct) / min_num_of_results
+                return correct / min_num_of_results
 
             result = {
                 "weight": 1,
diff --git a/osbenchmark/workload/params.py b/osbenchmark/workload/params.py
index 703a8af7c..d59ff557e 100644
--- a/osbenchmark/workload/params.py
+++ b/osbenchmark/workload/params.py
@@ -1102,8 +1102,7 @@ def __init__(self, workloads, params, query_params, **kwargs):
             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:
+        if bool(self.k) + bool(self.distance) + bool(self.score) > 1:
             raise ValueError("Only one of k, max_distance, or min_score can be specified in vector search.")
 
     @staticmethod
@@ -1129,14 +1128,16 @@ def _get_query_neighbors(self):
             return Context.MAX_DISTANCE_NEIGHBORS
         raise Exception("Unknown query type [%s]" % self.query_type)
 
+    def _get_query_size(self):
+        if self.query_type == self.KNN_QUERY_TYPE:
+            return self.k
+        return self.DEFAULT_RADIAL_SEARCH_QUERY_RESULT_SIZE
+
     def _update_body_params(self, vector):
         # accept body params if passed from workload, else, create empty dictionary
         body_params = self.query_params.get(self.PARAMS_NAME_BODY) or dict()
         if self.PARAMS_NAME_SIZE not in body_params:
-            if self.query_type == self.KNN_QUERY_TYPE:
-                body_params[self.PARAMS_NAME_SIZE] = self.k
-            else:
-                body_params[self.PARAMS_NAME_SIZE] = self.DEFAULT_RADIAL_SEARCH_QUERY_RESULT_SIZE
+            body_params[self.PARAMS_NAME_SIZE] = self._get_query_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)
@@ -1175,10 +1176,7 @@ def params(self):
             raise StopIteration
         vector = self.data_set.read(1)[0]
         neighbor = self.neighbors_data_set.read(1)[0]
-        if self.k:
-            true_neighbors = list(map(str, neighbor[:self.k]))
-        else:
-            true_neighbors = list(map(str, neighbor))
+        true_neighbors = list(map(str, neighbor[:self.k] if self.k else neighbor))
         self.query_params.update({
             "neighbors": true_neighbors,
         })