diff --git a/modelscope/pipelines/nlp/table_question_answering_pipeline.py b/modelscope/pipelines/nlp/table_question_answering_pipeline.py
index 52ba33e0..fc0d07b1 100644
--- a/modelscope/pipelines/nlp/table_question_answering_pipeline.py
+++ b/modelscope/pipelines/nlp/table_question_answering_pipeline.py
@@ -17,6 +17,9 @@ from modelscope.preprocessors.space_T_cn.fields.database import Database
 from modelscope.preprocessors.space_T_cn.fields.struct import (Constant,
                                                                SQLQuery)
 from modelscope.utils.constant import ModelFile, Tasks
+from modelscope.utils.logger import get_logger
+
+logger = get_logger()
 
 __all__ = ['TableQuestionAnsweringPipeline']
 
@@ -309,7 +312,8 @@ class TableQuestionAnsweringPipeline(Pipeline):
                     'header_name': header_names,
                     'rows': rows
                 }
-            except Exception:
+            except Exception as e:
+                logger.error(e)
                 tabledata = {'header_id': [], 'header_name': [], 'rows': []}
         else:
             tabledata = {'header_id': [], 'header_name': [], 'rows': []}
diff --git a/modelscope/preprocessors/space_T_cn/fields/database.py b/modelscope/preprocessors/space_T_cn/fields/database.py
index 481bd1db..7ae38ee2 100644
--- a/modelscope/preprocessors/space_T_cn/fields/database.py
+++ b/modelscope/preprocessors/space_T_cn/fields/database.py
@@ -17,7 +17,8 @@ class Database:
         self.tokenizer = tokenizer
         self.is_use_sqlite = is_use_sqlite
         if self.is_use_sqlite:
-            self.connection_obj = sqlite3.connect(':memory:')
+            self.connection_obj = sqlite3.connect(
+                ':memory:', check_same_thread=False)
             self.type_dict = {'text': 'TEXT', 'number': 'INT', 'date': 'TEXT'}
         self.tables = self.init_tables(table_file_path=table_file_path)
         self.syn_dict = self.init_syn_dict(
diff --git a/tests/pipelines/test_table_question_answering.py b/tests/pipelines/test_table_question_answering.py
index 828ef5ac..44f1531b 100644
--- a/tests/pipelines/test_table_question_answering.py
+++ b/tests/pipelines/test_table_question_answering.py
@@ -1,6 +1,7 @@
 # Copyright (c) Alibaba, Inc. and its affiliates.
 import os
 import unittest
+from threading import Thread
 from typing import List
 
 import json
@@ -108,8 +109,6 @@ class TableQuestionAnswering(unittest.TestCase):
         self.task = Tasks.table_question_answering
         self.model_id = 'damo/nlp_convai_text2sql_pretrain_cn'
 
-    model_id = 'damo/nlp_convai_text2sql_pretrain_cn'
-
     @unittest.skipUnless(test_level() >= 2, 'skip test in current test level')
     def test_run_by_direct_model_download(self):
         cache_path = snapshot_download(self.model_id)
@@ -122,6 +121,27 @@ class TableQuestionAnswering(unittest.TestCase):
         ]
         tableqa_tracking_and_print_results_with_history(pipelines)
 
+    @unittest.skipUnless(test_level() >= 2, 'skip test in current test level')
+    def test_run_by_direct_model_download_with_multithreads(self):
+        cache_path = snapshot_download(self.model_id)
+        pl = pipeline(Tasks.table_question_answering, model=cache_path)
+
+        def print_func(pl, i):
+            result = pl({
+                'question': '长江流域的小(2)型水库的库容总量是多少？',
+                'table_id': 'reservoir',
+                'history_sql': None
+            })
+            print(i, json.dumps(result))
+
+        procs = []
+        for i in range(5):
+            proc = Thread(target=print_func, args=(pl, i))
+            procs.append(proc)
+            proc.start()
+        for proc in procs:
+            proc.join()
+
     @unittest.skipUnless(test_level() >= 1, 'skip test in current test level')
     def test_run_with_model_from_modelhub(self):
         model = Model.from_pretrained(self.model_id)