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related: #45993 This commit extends nullable vector support to the proxy layer, querynode, and adds comprehensive validation, search reduce, and field data handling for nullable vectors with sparse storage. Proxy layer changes: - Update validate_util.go checkAligned() with getExpectedVectorRows() helper to validate nullable vector field alignment using valid data count - Update checkFloatVectorFieldData/checkSparseFloatVectorFieldData for nullable vector validation with proper row count expectations - Add FieldDataIdxComputer in typeutil/schema.go for logical-to-physical index translation during search reduce operations - Update search_reduce_util.go reduceSearchResultData to use idxComputers for correct field data indexing with nullable vectors - Update task.go, task_query.go, task_upsert.go for nullable vector handling - Update msg_pack.go with nullable vector field data processing QueryNode layer changes: - Update segments/result.go for nullable vector result handling - Update segments/search_reduce.go with nullable vector offset translation Storage and index changes: - Update data_codec.go and utils.go for nullable vector serialization - Update indexcgowrapper/dataset.go and index.go for nullable vector indexing Utility changes: - Add FieldDataIdxComputer struct with Compute() method for efficient logical-to-physical index mapping across multiple field data - Update EstimateEntitySize() and AppendFieldData() with fieldIdxs parameter - Update funcutil.go with nullable vector support functions <!-- This is an auto-generated comment: release notes by coderabbit.ai --> ## Summary by CodeRabbit * **New Features** * Full support for nullable vector fields (float, binary, float16, bfloat16, int8, sparse) across ingest, storage, indexing, search and retrieval; logical↔physical offset mapping preserves row semantics. * Client: compaction control and compaction-state APIs. * **Bug Fixes** * Improved validation for adding vector fields (nullable + dimension checks) and corrected search/query behavior for nullable vectors. * **Chores** * Persisted validity maps with indexes and on-disk formats. * **Tests** * Extensive new and updated end-to-end nullable-vector tests. <sub>✏️ Tip: You can customize this high-level summary in your review settings.</sub> <!-- end of auto-generated comment: release notes by coderabbit.ai --> --------- Signed-off-by: marcelo-cjl <marcelo.chen@zilliz.com>
247 lines
6.7 KiB
Go
247 lines
6.7 KiB
Go
package writebuffer
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import (
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"math/rand"
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"testing"
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"time"
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"github.com/samber/lo"
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"github.com/stretchr/testify/suite"
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"github.com/milvus-io/milvus-proto/go-api/v2/commonpb"
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"github.com/milvus-io/milvus-proto/go-api/v2/msgpb"
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"github.com/milvus-io/milvus-proto/go-api/v2/schemapb"
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"github.com/milvus-io/milvus/pkg/v2/common"
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"github.com/milvus-io/milvus/pkg/v2/mq/msgstream"
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"github.com/milvus-io/milvus/pkg/v2/util/paramtable"
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"github.com/milvus-io/milvus/pkg/v2/util/tsoutil"
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)
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type InsertBufferSuite struct {
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suite.Suite
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collSchema *schemapb.CollectionSchema
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pkField *schemapb.FieldSchema
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}
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func (s *InsertBufferSuite) SetupSuite() {
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paramtable.Get().Init(paramtable.NewBaseTable())
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s.collSchema = &schemapb.CollectionSchema{
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Name: "test_collection",
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Fields: []*schemapb.FieldSchema{
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{
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FieldID: common.RowIDField, Name: common.RowIDFieldName, DataType: schemapb.DataType_Int64,
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},
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{
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FieldID: common.TimeStampField, Name: common.TimeStampFieldName, DataType: schemapb.DataType_Int64,
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},
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{
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FieldID: 100, Name: "pk", DataType: schemapb.DataType_Int64, IsPrimaryKey: true,
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},
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{
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FieldID: 101, Name: "vector", DataType: schemapb.DataType_FloatVector,
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TypeParams: []*commonpb.KeyValuePair{
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{Key: common.DimKey, Value: "128"},
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},
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},
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},
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}
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s.pkField = &schemapb.FieldSchema{FieldID: 100, Name: "pk", DataType: schemapb.DataType_Int64, IsPrimaryKey: true}
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}
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func (s *InsertBufferSuite) composeInsertMsg(rowCount int, dim int) ([]int64, *msgstream.InsertMsg) {
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tss := lo.RepeatBy(rowCount, func(idx int) int64 { return int64(tsoutil.ComposeTSByTime(time.Now(), int64(idx))) })
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vectors := lo.RepeatBy(rowCount, func(_ int) []float32 {
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return lo.RepeatBy(dim, func(_ int) float32 { return rand.Float32() })
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})
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flatten := lo.Flatten(vectors)
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return tss, &msgstream.InsertMsg{
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InsertRequest: &msgpb.InsertRequest{
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Version: msgpb.InsertDataVersion_ColumnBased,
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RowIDs: tss,
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Timestamps: lo.Map(tss, func(id int64, _ int) uint64 { return uint64(id) }),
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FieldsData: []*schemapb.FieldData{
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{
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FieldId: common.RowIDField, FieldName: common.RowIDFieldName, Type: schemapb.DataType_Int64,
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Field: &schemapb.FieldData_Scalars{
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Scalars: &schemapb.ScalarField{
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Data: &schemapb.ScalarField_LongData{
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LongData: &schemapb.LongArray{
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Data: tss,
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},
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},
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},
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},
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},
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{
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FieldId: common.TimeStampField, FieldName: common.TimeStampFieldName, Type: schemapb.DataType_Int64,
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Field: &schemapb.FieldData_Scalars{
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Scalars: &schemapb.ScalarField{
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Data: &schemapb.ScalarField_LongData{
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LongData: &schemapb.LongArray{
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Data: tss,
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},
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},
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},
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},
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},
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{
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FieldId: common.StartOfUserFieldID, FieldName: "pk", Type: schemapb.DataType_Int64,
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Field: &schemapb.FieldData_Scalars{
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Scalars: &schemapb.ScalarField{
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Data: &schemapb.ScalarField_LongData{
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LongData: &schemapb.LongArray{
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Data: tss,
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},
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},
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},
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},
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},
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{
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FieldId: common.StartOfUserFieldID + 1, FieldName: "vector", Type: schemapb.DataType_FloatVector,
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Field: &schemapb.FieldData_Vectors{
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Vectors: &schemapb.VectorField{
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Dim: int64(dim),
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Data: &schemapb.VectorField_FloatVector{
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FloatVector: &schemapb.FloatArray{
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Data: flatten,
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},
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},
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},
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},
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},
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},
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},
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}
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}
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func (s *InsertBufferSuite) TestBasic() {
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s.Run("normal_insertbuffer", func() {
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insertBuffer, err := NewInsertBuffer(s.collSchema)
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s.Require().NoError(err)
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s.True(insertBuffer.IsEmpty())
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s.False(insertBuffer.IsFull())
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insertBuffer.size = insertBuffer.sizeLimit + 1
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s.True(insertBuffer.IsFull())
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s.False(insertBuffer.IsEmpty())
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})
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}
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func (s *InsertBufferSuite) TestBuffer() {
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_, insertMsg := s.composeInsertMsg(10, 128)
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insertBuffer, err := NewInsertBuffer(s.collSchema)
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s.Require().NoError(err)
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groups, err := PrepareInsert(s.collSchema, s.pkField, []*msgstream.InsertMsg{insertMsg})
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s.Require().NoError(err)
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s.Require().Len(groups, 1)
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memSize := insertBuffer.Buffer(groups[0], &msgpb.MsgPosition{Timestamp: 100}, &msgpb.MsgPosition{Timestamp: 200})
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s.EqualValues(100, insertBuffer.MinTimestamp())
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s.EqualValues(5376, memSize)
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}
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func (s *InsertBufferSuite) TestYield() {
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insertBuffer, err := NewInsertBuffer(s.collSchema)
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s.Require().NoError(err)
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result := insertBuffer.Yield()
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s.Nil(result)
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insertBuffer, err = NewInsertBuffer(s.collSchema)
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s.Require().NoError(err)
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pks, insertMsg := s.composeInsertMsg(10, 128)
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groups, err := PrepareInsert(s.collSchema, s.pkField, []*msgstream.InsertMsg{insertMsg})
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s.Require().NoError(err)
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s.Require().Len(groups, 1)
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insertBuffer.Buffer(groups[0], &msgpb.MsgPosition{Timestamp: 100}, &msgpb.MsgPosition{Timestamp: 200})
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result = insertBuffer.Yield()
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s.NotNil(result)
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var pkData []int64
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for _, chunk := range result {
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pkField, ok := chunk.Data[common.StartOfUserFieldID]
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s.Require().True(ok)
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pkData = append(pkData, lo.RepeatBy(pkField.RowNum(), func(idx int) int64 { return pkField.GetRow(idx).(int64) })...)
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}
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s.ElementsMatch(pks, pkData)
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}
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type InsertBufferConstructSuite struct {
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suite.Suite
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schema *schemapb.CollectionSchema
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}
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func (*InsertBufferConstructSuite) SetupSuite() {
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paramtable.Get().Init(paramtable.NewBaseTable())
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}
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func (s *InsertBufferConstructSuite) TestCreateSuccess() {
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schema := &schemapb.CollectionSchema{
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Name: "test_collection",
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Fields: []*schemapb.FieldSchema{
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{
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FieldID: 100, Name: "pk", DataType: schemapb.DataType_Int64, IsPrimaryKey: true,
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},
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{
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FieldID: 101, Name: "vector", DataType: schemapb.DataType_FloatVector,
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TypeParams: []*commonpb.KeyValuePair{
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{Key: common.DimKey, Value: "128"},
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},
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},
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},
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}
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insertBuffer, err := NewInsertBuffer(schema)
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s.NoError(err)
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s.NotNil(insertBuffer)
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}
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func (s *InsertBufferConstructSuite) TestCreateFailure() {
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type testCase struct {
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schema *schemapb.CollectionSchema
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tag string
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}
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cases := []testCase{
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{
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tag: "undefined_datatype",
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schema: &schemapb.CollectionSchema{
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Fields: []*schemapb.FieldSchema{
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{FieldID: 101, Name: "vector", DataType: -1},
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},
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},
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},
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{
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tag: "mssing_maxlength",
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schema: &schemapb.CollectionSchema{
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Fields: []*schemapb.FieldSchema{
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{FieldID: 101, Name: "string", DataType: schemapb.DataType_VarChar},
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},
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},
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},
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{
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tag: "empty_schema",
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schema: &schemapb.CollectionSchema{
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Fields: []*schemapb.FieldSchema{},
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},
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},
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}
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for _, tc := range cases {
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s.Run(tc.tag, func() {
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_, err := NewInsertBuffer(tc.schema)
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s.Error(err)
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})
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}
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}
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func TestInsertBuffer(t *testing.T) {
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suite.Run(t, new(InsertBufferSuite))
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suite.Run(t, new(InsertBufferConstructSuite))
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}
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