diff --git a/modelscope/pipelines/nlp/table_question_answering_pipeline.py b/modelscope/pipelines/nlp/table_question_answering_pipeline.py
index ca17c9b1..08501953 100644
--- a/modelscope/pipelines/nlp/table_question_answering_pipeline.py
+++ b/modelscope/pipelines/nlp/table_question_answering_pipeline.py
@@ -72,6 +72,7 @@ class TableQuestionAnsweringPipeline(Pipeline):
         action = self.action_ops[result['action']]
         headers = table['header_name']
         current_sql = result['sql']
+        current_sql['from'] = [table['table_id']]
 
         if history_sql is None:
             return current_sql
@@ -216,10 +217,11 @@ class TableQuestionAnsweringPipeline(Pipeline):
         else:
             return current_sql
 
-    def sql_dict_to_str(self, result, table):
+    def sql_dict_to_str(self, result, tables):
         """
         convert sql struct to string
         """
+        table = tables[result['sql']['from'][0]]
         header_names = table['header_name'] + ['空列']
         header_ids = table['header_id'] + ['null']
         sql = result['sql']
@@ -279,42 +281,43 @@ class TableQuestionAnsweringPipeline(Pipeline):
         """
         result = inputs['result']
         history_sql = inputs['history_sql']
-        result['sql'] = self.post_process_multi_turn(
-            history_sql=history_sql,
-            result=result,
-            table=self.db.tables[result['table_id']])
-        result['sql']['from'] = [result['table_id']]
-        sql = self.sql_dict_to_str(
-            result=result, table=self.db.tables[result['table_id']])
+        try:
+            result['sql'] = self.post_process_multi_turn(
+                history_sql=history_sql,
+                result=result,
+                table=self.db.tables[result['table_id']])
+        except Exception:
+            result['sql'] = history_sql
+        sql = self.sql_dict_to_str(result=result, tables=self.db.tables)
 
         # add sqlite
         if self.db.is_use_sqlite:
             try:
                 cursor = self.db.connection_obj.cursor().execute(sql.query)
-                names = [{
-                    'name':
-                    description[0],
-                    'label':
-                    self.db.tables[result['table_id']]['headerid2name'].get(
-                        description[0], description[0])
-                } for description in cursor.description]
-                cells = []
+                header_ids, header_names = [], []
+                for description in cursor.description:
+                    header_ids.append(self.db.tables[result['table_id']]
+                                      ['headerid2name'].get(
+                                          description[0], description[0]))
+                    header_names.append(description[0])
+                rows = []
                 for res in cursor.fetchall():
-                    row = {}
-                    for name, cell in zip(names, res):
-                        row[name['name']] = cell
-                    cells.append(row)
-                tabledata = {'headers': names, 'cells': cells}
+                    rows.append(list(res))
+                tabledata = {
+                    'header_id': header_ids,
+                    'header_name': header_names,
+                    'rows': rows
+                }
             except Exception:
-                tabledata = {'headers': [], 'cells': []}
+                tabledata = {'header_id': [], 'header_name': [], 'rows': []}
         else:
-            tabledata = {'headers': [], 'cells': []}
+            tabledata = {'header_id': [], 'header_name': [], 'rows': []}
 
         output = {
             OutputKeys.SQL_STRING: sql.string,
             OutputKeys.SQL_QUERY: sql.query,
             OutputKeys.HISTORY: result['sql'],
-            OutputKeys.QUERT_RESULT: json.dumps(tabledata, ensure_ascii=False),
+            OutputKeys.QUERT_RESULT: tabledata,
         }
 
         return output
diff --git a/modelscope/preprocessors/star3/fields/database.py b/modelscope/preprocessors/star3/fields/database.py
index 3d3a1f8d..5debfe2c 100644
--- a/modelscope/preprocessors/star3/fields/database.py
+++ b/modelscope/preprocessors/star3/fields/database.py
@@ -13,7 +13,7 @@ class Database:
                  tokenizer,
                  table_file_path,
                  syn_dict_file_path,
-                 is_use_sqlite=False):
+                 is_use_sqlite=True):
         self.tokenizer = tokenizer
         self.is_use_sqlite = is_use_sqlite
         if self.is_use_sqlite:
diff --git a/modelscope/preprocessors/star3/fields/schema_link.py b/modelscope/preprocessors/star3/fields/schema_link.py
index 7f483a1f..220a71d8 100644
--- a/modelscope/preprocessors/star3/fields/schema_link.py
+++ b/modelscope/preprocessors/star3/fields/schema_link.py
@@ -293,6 +293,7 @@ class SchemaLinker:
                            nlu_t,
                            tables,
                            col_syn_dict,
+                           table_id=None,
                            history_sql=None):
         """
         get linking between question and schema column
@@ -300,6 +301,9 @@ class SchemaLinker:
         typeinfos = []
         numbers = re.findall(r'[-]?\d*\.\d+|[-]?\d+|\d+', nlu)
 
+        if table_id is not None and table_id in tables:
+            tables = {table_id: tables[table_id]}
+
         # search schema link in every table
         search_result_list = []
         for tablename in tables:
@@ -411,26 +415,25 @@ class SchemaLinker:
             # get the match score of each table
             match_score = self.get_table_match_score(nlu_t, schema_link)
 
+            # cal table_score
+            if history_sql is not None and 'from' in history_sql:
+                table_score = int(table['table_id'] == history_sql['from'][0])
+            else:
+                table_score = 0
+
             search_result = {
-                'table_id':
-                table['table_id'],
-                'question_knowledge':
-                final_question,
-                'header_knowledge':
-                final_header,
-                'schema_link':
-                schema_link,
-                'match_score':
-                match_score,
-                'table_score':
-                int(table['table_id'] == history_sql['from'][0])
-                if history_sql is not None else 0
+                'table_id': table['table_id'],
+                'question_knowledge': final_question,
+                'header_knowledge': final_header,
+                'schema_link': schema_link,
+                'match_score': match_score,
+                'table_score': table_score
             }
             search_result_list.append(search_result)
 
         search_result_list = sorted(
             search_result_list,
             key=lambda x: (x['match_score'], x['table_score']),
-            reverse=True)[0:4]
+            reverse=True)[0:1]
 
         return search_result_list
diff --git a/modelscope/preprocessors/star3/table_question_answering_preprocessor.py b/modelscope/preprocessors/star3/table_question_answering_preprocessor.py
index f98aa6d0..ed2911f6 100644
--- a/modelscope/preprocessors/star3/table_question_answering_preprocessor.py
+++ b/modelscope/preprocessors/star3/table_question_answering_preprocessor.py
@@ -95,6 +95,7 @@ class TableQuestionAnsweringPreprocessor(Preprocessor):
 
         # tokenize question
         question = data['question']
+        table_id = data.get('table_id', None)
         history_sql = data.get('history_sql', None)
         nlu = question.lower()
         nlu_t = self.tokenizer.tokenize(nlu)
@@ -106,6 +107,7 @@ class TableQuestionAnsweringPreprocessor(Preprocessor):
             nlu_t=nlu_t,
             tables=self.db.tables,
             col_syn_dict=self.db.syn_dict,
+            table_id=table_id,
             history_sql=history_sql)
 
         # collect data
diff --git a/tests/pipelines/test_table_question_answering.py b/tests/pipelines/test_table_question_answering.py
index 3d943e51..571ca795 100644
--- a/tests/pipelines/test_table_question_answering.py
+++ b/tests/pipelines/test_table_question_answering.py
@@ -43,7 +43,7 @@ def tableqa_tracking_and_print_results_with_history(
             print('sql text:', output_dict[OutputKeys.SQL_STRING])
             print('sql query:', output_dict[OutputKeys.SQL_QUERY])
             print('query result:', output_dict[OutputKeys.QUERT_RESULT])
-            print('json dumps', json.dumps(output_dict))
+            print('json dumps', json.dumps(output_dict, ensure_ascii=False))
             print()
             historical_queries = output_dict[OutputKeys.HISTORY]
 
@@ -66,10 +66,42 @@ def tableqa_tracking_and_print_results_without_history(
             print('sql text:', output_dict[OutputKeys.SQL_STRING])
             print('sql query:', output_dict[OutputKeys.SQL_QUERY])
             print('query result:', output_dict[OutputKeys.QUERT_RESULT])
-            print('json dumps', json.dumps(output_dict))
+            print('json dumps', json.dumps(output_dict, ensure_ascii=False))
             print()
 
 
+def tableqa_tracking_and_print_results_with_tableid(
+        pipelines: List[TableQuestionAnsweringPipeline]):
+    test_case = {
+        'utterance': [
+            ['有哪些风险类型？', 'fund'],
+            ['风险类型有多少种？', 'reservoir'],
+            ['珠江流域的小(2)型水库的库容总量是多少？', 'reservoir'],
+            ['那平均值是多少？', 'reservoir'],
+            ['那水库的名称呢？', 'reservoir'],
+            ['换成中型的呢？', 'reservoir'],
+            ['枣庄营业厅的电话', 'business'],
+            ['那地址呢？', 'business'],
+            ['枣庄营业厅的电话和地址', 'business'],
+        ],
+    }
+    for p in pipelines:
+        historical_queries = None
+        for question, table_id in test_case['utterance']:
+            output_dict = p({
+                'question': question,
+                'table_id': table_id,
+                'history_sql': historical_queries
+            })
+            print('question', question)
+            print('sql text:', output_dict[OutputKeys.SQL_STRING])
+            print('sql query:', output_dict[OutputKeys.SQL_QUERY])
+            print('query result:', output_dict[OutputKeys.QUERT_RESULT])
+            print('json dumps', json.dumps(output_dict, ensure_ascii=False))
+            print()
+            historical_queries = output_dict[OutputKeys.HISTORY]
+
+
 class TableQuestionAnswering(unittest.TestCase):
 
     def setUp(self) -> None:
@@ -93,15 +125,27 @@ class TableQuestionAnswering(unittest.TestCase):
     @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)
+        self.tokenizer = BertTokenizer(
+            os.path.join(model.model_dir, ModelFile.VOCAB_FILE))
+        db = Database(
+            tokenizer=self.tokenizer,
+            table_file_path=[
+                os.path.join(model.model_dir, 'databases', fname)
+                for fname in os.listdir(
+                    os.path.join(model.model_dir, 'databases'))
+            ],
+            syn_dict_file_path=os.path.join(model.model_dir, 'synonym.txt'),
+            is_use_sqlite=False)
         preprocessor = TableQuestionAnsweringPreprocessor(
-            model_dir=model.model_dir)
+            model_dir=model.model_dir, db=db)
         pipelines = [
             pipeline(
                 Tasks.table_question_answering,
                 model=model,
-                preprocessor=preprocessor)
+                preprocessor=preprocessor,
+                db=db)
         ]
-        tableqa_tracking_and_print_results_with_history(pipelines)
+        tableqa_tracking_and_print_results_with_tableid(pipelines)
 
     @unittest.skipUnless(test_level() >= 0, 'skip test in current test level')
     def test_run_with_model_from_task(self):
@@ -132,7 +176,6 @@ class TableQuestionAnswering(unittest.TestCase):
                 db=db)
         ]
         tableqa_tracking_and_print_results_without_history(pipelines)
-        tableqa_tracking_and_print_results_with_history(pipelines)
 
 
 if __name__ == '__main__':