diff --git a/tests/python_client/bulk_load/test_bulk_load.py b/tests/python_client/bulk_load/test_bulk_load.py
index ab442e5d51..08e61eef9b 100644
--- a/tests/python_client/bulk_load/test_bulk_load.py
+++ b/tests/python_client/bulk_load/test_bulk_load.py
@@ -28,31 +28,8 @@ def entity_suffix(entities):
     return suffix
 
 
-def gen_file_prefix(row_based=True, auto_id=True, prefix=""):
-    if row_based:
-        if auto_id:
-            return f"{prefix}row_auto"
-        else:
-            return f"{prefix}row_cust"
-    else:
-        if auto_id:
-            return f"{prefix}col_auto"
-        else:
-            return f"{prefix}col_cust"
-
-
 class TestBulkLoad(TestcaseBase):
 
-    def setup_class(self):
-        log.info("[setup_import] Start setup class...")
-        # TODO: copy data files to minio
-        log.info("copy data files to minio")
-
-    def teardown_class(self):
-        log.info("[teardown_import] Start teardown class...")
-        # TODO: clean up data or not is a question
-        log.info("clean up data files in minio")
-
     @pytest.mark.tags(CaseLabel.L3)
     @pytest.mark.parametrize("row_based", [True, False])
     @pytest.mark.parametrize("auto_id", [True, False])
@@ -100,14 +77,19 @@ class TestBulkLoad(TestcaseBase):
         # verify imported data is available for search
         self.collection_wrap.load()
         # log.info(f"query seg info: {self.utility_wrap.get_query_segment_info(c_name)[0]}")
-        search_data = cf.gen_vectors(1, dim)
+        nq = 2
+        topk = 2
+        search_data = cf.gen_vectors(nq, dim)
         search_params = {"metric_type": "L2", "params": {"nprobe": 2}}
         res, _ = self.collection_wrap.search(search_data, df.vec_field,
-                                             param=search_params, limit=1,
+                                             param=search_params, limit=topk,
                                              check_task=CheckTasks.check_search_results,
-                                             check_items={"nq": 1,
-                                                          "limit": 1})
-        # self.collection_wrap.query(expr=f"id in {ids}")
+                                             check_items={"nq": nq,
+                                                          "limit": topk})
+        for hits in res:
+            ids = hits.ids
+            results, _ = self.collection_wrap.query(expr=f"{df.pk_field} in {ids}")
+            assert len(results) == len(ids)
 
     @pytest.mark.tags(CaseLabel.L3)
     @pytest.mark.parametrize("row_based", [True, False])
@@ -154,14 +136,21 @@ class TestBulkLoad(TestcaseBase):
         # verify imported data is available for search
         self.collection_wrap.load()
         log.info(f"query seg info: {self.utility_wrap.get_query_segment_info(c_name)[0]}")
-        search_data = cf.gen_vectors(1, dim)
+        nq = 3
+        topk = 2
+        search_data = cf.gen_vectors(nq, dim)
         search_params = {"metric_type": "L2", "params": {"nprobe": 2}}
         res, _ = self.collection_wrap.search(search_data, df.vec_field,
-                                             param=search_params, limit=1,
+                                             param=search_params, limit=topk,
                                              check_task=CheckTasks.check_search_results,
-                                             check_items={"nq": 1,
-                                                          "limit": 1})
-        # self.collection_wrap.query(expr=f"id in {ids}")
+                                             check_items={"nq": nq,
+                                                          "limit": topk})
+        for hits in res:
+            ids = hits.ids
+            expr = f"{df.pk_field} in {ids}"
+            expr = expr.replace("'", "\"")
+            results, _ = self.collection_wrap.query(expr=expr)
+            assert len(results) == len(ids)
 
     @pytest.mark.tags(CaseLabel.L3)
     @pytest.mark.parametrize("row_based", [True, False])
@@ -223,14 +212,19 @@ class TestBulkLoad(TestcaseBase):
         assert res == exp_res
 
         log.info(f"query seg info: {self.utility_wrap.get_query_segment_info(c_name)[0]}")
-
-        search_data = cf.gen_vectors(1, dim)
+        nq = 10
+        topk = 5
+        search_data = cf.gen_vectors(nq, dim)
         search_params = {"metric_type": "L2", "params": {"nprobe": 16}}
         res, _ = self.collection_wrap.search(search_data, df.vec_field,
-                                             param=search_params, limit=1,
+                                             param=search_params, limit=topk,
                                              check_task=CheckTasks.check_search_results,
-                                             check_items={"nq": 1,
-                                                          "limit": 1})
+                                             check_items={"nq": nq,
+                                                          "limit": topk})
+        for hits in res:
+            ids = hits.ids
+            results, _ = self.collection_wrap.query(expr=f"{df.pk_field} in {ids}")
+            assert len(results) == len(ids)
 
     @pytest.mark.tags(CaseLabel.L3)
     @pytest.mark.parametrize("row_based", [True, False])
@@ -302,6 +296,10 @@ class TestBulkLoad(TestcaseBase):
                                              check_task=CheckTasks.check_search_results,
                                              check_items={"nq": 1,
                                                           "limit": 1})
+        for hits in res:
+            ids = hits.ids
+            results, _ = self.collection_wrap.query(expr=f"{df.pk_field} in {ids}")
+            assert len(results) == len(ids)
 
     @pytest.mark.tags(CaseLabel.L3)
     @pytest.mark.parametrize("row_based", [True, False])
@@ -384,8 +382,10 @@ class TestBulkLoad(TestcaseBase):
                                                  check_task=CheckTasks.check_search_results,
                                                  check_items={"nq": 1,
                                                               "limit": 1})
-
-            # self.collection_wrap.query(expr=f"id in {ids}")
+            for hits in res:
+                ids = hits.ids
+                results, _ = self.collection_wrap.query(expr=f"{df.pk_field} in {ids}")
+                assert len(results) == len(ids)
 
             # build index
             index_params = {"index_type": "HNSW", "params": {"M": 8, "efConstruction": 100}, "metric_type": "IP"}
@@ -406,6 +406,10 @@ class TestBulkLoad(TestcaseBase):
                                                  check_task=CheckTasks.check_search_results,
                                                  check_items={"nq": 1,
                                                               "limit": 1})
+            for hits in res:
+                ids = hits.ids
+                results, _ = self.collection_wrap.query(expr=f"{df.pk_field} in {ids}")
+                assert len(results) == len(ids)
 
     @pytest.mark.tags(CaseLabel.L3)
     @pytest.mark.parametrize("row_based", [True, False])
@@ -488,8 +492,12 @@ class TestBulkLoad(TestcaseBase):
                                                  check_task=CheckTasks.check_search_results,
                                                  check_items={"nq": 1,
                                                               "limit": 1})
-
-            # self.collection_wrap.query(expr=f"id in {ids}")
+            for hits in res:
+                ids = hits.ids
+                expr = f"{df.pk_field} in {ids}"
+                expr = expr.replace("'", "\"")
+                results, _ = self.collection_wrap.query(expr=expr)
+                assert len(results) == len(ids)
 
             # build index
             index_params = {"index_type": "HNSW", "params": {"M": 8, "efConstruction": 100}, "metric_type": "IP"}
@@ -510,6 +518,12 @@ class TestBulkLoad(TestcaseBase):
                                                  check_task=CheckTasks.check_search_results,
                                                  check_items={"nq": 1,
                                                               "limit": 1})
+            for hits in res:
+                ids = hits.ids
+                expr = f"{df.pk_field} in {ids}"
+                expr = expr.replace("'", "\"")
+                results, _ = self.collection_wrap.query(expr=expr)
+                assert len(results) == len(ids)
 
     @pytest.mark.tags(CaseLabel.L3)
     @pytest.mark.parametrize("row_based", [True, False])      # True, False
@@ -583,15 +597,19 @@ class TestBulkLoad(TestcaseBase):
             # assert res == exp_res
 
             # verify search and query
-            search_data = cf.gen_vectors(1, dim)
+            nq = 5
+            topk = 1
+            search_data = cf.gen_vectors(nq, dim)
             search_params = ct.default_search_params
             res, _ = self.collection_wrap.search(search_data, df.vec_field,
-                                                 param=search_params, limit=1,
+                                                 param=search_params, limit=topk,
                                                  check_task=CheckTasks.check_search_results,
-                                                 check_items={"nq": 1,
-                                                              "limit": 1})
-
-            # self.collection_wrap.query(expr=f"id in {ids}")
+                                                 check_items={"nq": nq,
+                                                              "limit": topk})
+            for hits in res:
+                ids = hits.ids
+                results, _ = self.collection_wrap.query(expr=f"{df.pk_field} in {ids}")
+                assert len(results) == len(ids)
 
     @pytest.mark.tags(CaseLabel.L3)
     @pytest.mark.parametrize("row_based", [True, False])
@@ -674,14 +692,19 @@ class TestBulkLoad(TestcaseBase):
             # verify imported data is available for search
             self.collection_wrap.load()
             log.info(f"query seg info: {self.utility_wrap.get_query_segment_info(c_name)[0]}")
-            search_data = cf.gen_vectors(1, dim)
+            nq = 2
+            topk = 5
+            search_data = cf.gen_vectors(nq, dim)
             search_params = {"metric_type": "L2", "params": {"nprobe": 2}}
             res, _ = self.collection_wrap.search(search_data, df.vec_field,
-                                                 param=search_params, limit=1,
+                                                 param=search_params, limit=topk,
                                                  check_task=CheckTasks.check_search_results,
-                                                 check_items={"nq": 1,
-                                                              "limit": 1})
-            # self.collection_wrap.query(expr=f"id in {ids}")
+                                                 check_items={"nq": nq,
+                                                              "limit": topk})
+            for hits in res:
+                ids = hits.ids
+                results, _ = self.collection_wrap.query(expr=f"{df.pk_field} in {ids}")
+                assert len(results) == len(ids)
 
     @pytest.mark.tags(CaseLabel.L3)
     @pytest.mark.parametrize("row_based", [True, False])