[Bug]: [GoSDK] Insert rows data with varchar field gets error: param column varchar has type string but collection field definition is string

[ThreadDao]

Is there an existing issue for this?

• [X] I have searched the existing issues

Environment

- Milvus version: master-20240528-b138ae74-amd64
- Deployment mode(standalone or cluster):
- MQ type(rocksmq, pulsar or kafka):    
- SDK version(e.g. pymilvus v2.0.0rc2): go-sdk v2
- OS(Ubuntu or CentOS): 
- CPU/Memory: 
- GPU: 
- Others:

Current Behavior

1. create collection with fields: int64(pk), varchar, sparseVec
2. insert row and gets error: param column varchar has type string but collection field definition is string

• case:

  // test insert rows enable or disable dynamic field
  func TestInsertSparseRows(t *testing.T) {
  t.Parallel()
  ctx := hp.CreateContext(t, time.Second*common.DefaultTimeout)
  mc := createDefaultMilvusClient(ctx, t)
  
  for _, autoId := range []bool{true} {
      cp := hp.NewCreateCollectionParams(hp.Int64VarcharSparseVec)
      _, schema := hp.CollPrepare.CreateCollection(ctx, t, mc, cp, hp.TNewFieldsOption(), hp.TNewSchemaOption().TWithAutoID(autoId))
      log.Info("fields", zap.Any("FieldNames", schema.Fields))
  
      // insert rows
      rows := hp.GenInt64VarcharSparseRows(common.DefaultNb, false, autoId, *hp.TNewDataOption().TWithSparseMaxLen(1000))
      ids, err := mc.Insert(ctx, clientv2.NewRowBasedInsertOption(schema.CollectionName, rows...))
      common.CheckErr(t, err, true)
  
      int64Values := make([]int64, 0, common.DefaultNb)
      for i := 0; i < common.DefaultNb; i++ {
          int64Values = append(int64Values, int64(i))
      }
      common.CheckInsertResult(t, ids.IDs, column.NewColumnInt64(common.DefaultInt64FieldName, int64Values))
  
      // flush and check row count
      flushTask, errFlush := mc.Flush(ctx, clientv2.NewFlushOption(schema.CollectionName))
      common.CheckErr(t, errFlush, true)
      errFlush = flushTask.Await(ctx)
      common.CheckErr(t, errFlush, true)
  }
  }

• rows data generation:

  
  func GenInt64VarcharSparseRows(nb int, enableDynamicField bool, autoID bool, option GenDataOption) []interface{} {
  start := option.start
  
  rows := make([]interface{}, 0, nb)
  
  // BaseRow generate insert rows
  for i := start; i < start+nb; i++ {
      baseRow := BaseRow{
          Varchar:      strconv.Itoa(i),
          SparseVec:   common.GenSparseVector(option.sparseMaxLen),
      }
      if !autoID{
          baseRow.Int64 = int64(i)
      }
      if enableDynamicField{
          baseRow.Dynamic = GenDynamicRow(i)
      }
      rows = append(rows, &baseRow)
  }
  return rows
  }
  type Dynamic struct {
  Number int32   `json:"dynamicNumber,omitempty" milvus:"name:dynamicNumber"`
  String string  `json:"dynamicString,omitempty" milvus:"name:dynamicString"`
  Bool   bool    `json:"dynamicBool,omitempty" milvus:"name:dynamicBool"`
  List   []int64 `json:"dynamicList,omitempty" milvus:"name:dynamicList"`
  }

type BaseRow struct { Bool bool json:"bool,omitempty" milvus:"name:bool" Int8 int8 json:"int8,omitempty" milvus:"name:int8" Int16 int16 json:"int16,omitempty" milvus:"name:int16" Int32 int32 json:"int32,omitempty" milvus:"name:int32" Int64 int64 json:"int64,omitempty" milvus:"name:int64" Float float32 json:"float,omitempty" milvus:"name:float" Double float64 json:"double,omitempty" milvus:"name:double" Varchar string json:"varchar,omitempty" milvus:"name:varchar" JSON JSONStruct json:"json,omitempty" milvus:"name:json" FloatVec []float32 json:"floatVec,omitempty" milvus:"name:floatVec" Fp16Vec []byte json:"fp16Vec,omitempty" milvus:"name:fp16Vec" Bf16Vec []byte json:"bf16Vec,omitempty" milvus:"name:bf16Vec" BinaryVec []byte json:"binaryVec,omitempty" milvus:"name:binaryVec" SparseVec entity.SparseEmbedding json:"sparseVec,omitempty" milvus:"name:sparseVec" Array Dynamic }

### Expected Behavior

_No response_

### Steps To Reproduce

_No response_

### Milvus Log

_No response_

### Anything else?

_No response_

[ThreadDao]

fixed

[yanliang567]

close as comments above