text: -- @testpoint: kmeans创建mode，带正确的超参batch_size
  
  --step1: 创建表并插入数据;expect: 创建表并插入数据成功
  drop table if exists t_model_tab_0042;
  create table t_model_tab_0042(id integer not null,"position" double precision[] not null,closest_centroid integer not null, l1_distance double precision not null, l2_distance double precision not null,l2_squared_distance double precision not null,linf_distance double precision not null );
  insert into t_model_tab_0042 values (214,'{82.2331969052000034,52.153098620199998,64.0342866000999933,-.325498642699999981,-64.6012142075999947,81.5499670644999952,59.6012626708999989}',3,10.0679804558999992,4.35061551650000012,18.9278551126999999,2.38425523010000019);
  
  --step2: kmeans创建mode带正确的超参batch_size;expect: 创建成功
  create model m_model_kmeans_batch_size_0042 using kmeans from (select position from t_model_tab_0042 ) with batch_size=100000,num_features = 7;
  
  --step3: 查询系统表中的 hyperparametersvalues;expect: 返回的内容中含设置的batch_size的值100000
  select hyperparametersvalues from gs_model_warehouse where modelname='m_model_kmeans_batch_size_0042';
  
  --step4: 清理环境;expext: 清理成功
  drop table t_model_tab_0042;
  drop model m_model_kmeans_batch_size_0042;