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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>
266 lines
9.4 KiB
Go
266 lines
9.4 KiB
Go
package segments
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import (
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"context"
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"fmt"
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"go.opentelemetry.io/otel"
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"go.uber.org/zap"
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"github.com/milvus-io/milvus-proto/go-api/v2/schemapb"
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"github.com/milvus-io/milvus/internal/util/reduce"
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"github.com/milvus-io/milvus/pkg/v2/log"
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"github.com/milvus-io/milvus/pkg/v2/util/merr"
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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/typeutil"
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)
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type SearchReduce interface {
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ReduceSearchResultData(ctx context.Context, searchResultData []*schemapb.SearchResultData, info *reduce.ResultInfo) (*schemapb.SearchResultData, error)
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}
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type SearchCommonReduce struct{}
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func (scr *SearchCommonReduce) ReduceSearchResultData(ctx context.Context, searchResultData []*schemapb.SearchResultData, info *reduce.ResultInfo) (*schemapb.SearchResultData, error) {
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ctx, sp := otel.Tracer(typeutil.QueryNodeRole).Start(ctx, "ReduceSearchResultData")
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defer sp.End()
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log := log.Ctx(ctx)
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if len(searchResultData) == 0 {
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return &schemapb.SearchResultData{
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NumQueries: info.GetNq(),
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TopK: info.GetTopK(),
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FieldsData: make([]*schemapb.FieldData, 0),
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Scores: make([]float32, 0),
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Ids: &schemapb.IDs{},
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Topks: make([]int64, 0),
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}, nil
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}
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ret := &schemapb.SearchResultData{
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NumQueries: info.GetNq(),
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TopK: info.GetTopK(),
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FieldsData: make([]*schemapb.FieldData, len(searchResultData[0].FieldsData)),
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Scores: make([]float32, 0),
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Ids: &schemapb.IDs{},
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Topks: make([]int64, 0),
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}
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// Check element-level consistency: all results must have ElementIndices or none
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hasElementIndices := searchResultData[0].ElementIndices != nil
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for i, data := range searchResultData {
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if (data.ElementIndices != nil) != hasElementIndices {
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return nil, fmt.Errorf("inconsistent element-level flag in search results: result[0] has ElementIndices=%v, but result[%d] has ElementIndices=%v",
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hasElementIndices, i, data.ElementIndices != nil)
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}
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}
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if hasElementIndices {
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ret.ElementIndices = &schemapb.LongArray{
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Data: make([]int64, 0),
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}
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}
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resultOffsets := make([][]int64, len(searchResultData))
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for i := 0; i < len(searchResultData); i++ {
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resultOffsets[i] = make([]int64, len(searchResultData[i].Topks))
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for j := int64(1); j < info.GetNq(); j++ {
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resultOffsets[i][j] = resultOffsets[i][j-1] + searchResultData[i].Topks[j-1]
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}
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ret.AllSearchCount += searchResultData[i].GetAllSearchCount()
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}
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idxComputers := make([]*typeutil.FieldDataIdxComputer, len(searchResultData))
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for i, srd := range searchResultData {
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idxComputers[i] = typeutil.NewFieldDataIdxComputer(srd.FieldsData)
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}
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var skipDupCnt int64
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var retSize int64
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maxOutputSize := paramtable.Get().QuotaConfig.MaxOutputSize.GetAsInt64()
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for i := int64(0); i < info.GetNq(); i++ {
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offsets := make([]int64, len(searchResultData))
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idSet := make(map[interface{}]struct{})
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var j int64
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for j = 0; j < info.GetTopK(); {
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sel := SelectSearchResultData(searchResultData, resultOffsets, offsets, i)
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if sel == -1 {
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break
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}
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idx := resultOffsets[sel][i] + offsets[sel]
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id := typeutil.GetPK(searchResultData[sel].GetIds(), idx)
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score := searchResultData[sel].Scores[idx]
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// remove duplicates
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if _, ok := idSet[id]; !ok {
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fieldsData := searchResultData[sel].FieldsData
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fieldIdxs := idxComputers[sel].Compute(idx)
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retSize += typeutil.AppendFieldData(ret.FieldsData, fieldsData, idx, fieldIdxs...)
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typeutil.AppendPKs(ret.Ids, id)
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ret.Scores = append(ret.Scores, score)
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if searchResultData[sel].ElementIndices != nil && ret.ElementIndices != nil {
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ret.ElementIndices.Data = append(ret.ElementIndices.Data, searchResultData[sel].ElementIndices.Data[idx])
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}
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idSet[id] = struct{}{}
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j++
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} else {
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// skip entity with same id
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skipDupCnt++
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}
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offsets[sel]++
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}
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// if realTopK != -1 && realTopK != j {
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// log.Warn("Proxy Reduce Search Result", zap.Error(errors.New("the length (topk) between all result of query is different")))
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// // return nil, errors.New("the length (topk) between all result of query is different")
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// }
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ret.Topks = append(ret.Topks, j)
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// limit search result to avoid oom
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if retSize > maxOutputSize {
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return nil, fmt.Errorf("search results exceed the maxOutputSize Limit %d", maxOutputSize)
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}
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}
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log.Debug("skip duplicated search result", zap.Int64("count", skipDupCnt))
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return ret, nil
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}
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type SearchGroupByReduce struct{}
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func (sbr *SearchGroupByReduce) ReduceSearchResultData(ctx context.Context, searchResultData []*schemapb.SearchResultData, info *reduce.ResultInfo) (*schemapb.SearchResultData, error) {
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ctx, sp := otel.Tracer(typeutil.QueryNodeRole).Start(ctx, "ReduceSearchResultData")
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defer sp.End()
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log := log.Ctx(ctx)
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if len(searchResultData) == 0 {
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log.Debug("Shortcut return SearchGroupByReduce, directly return empty result", zap.Any("result info", info))
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return &schemapb.SearchResultData{
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NumQueries: info.GetNq(),
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TopK: info.GetTopK(),
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FieldsData: make([]*schemapb.FieldData, 0),
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Scores: make([]float32, 0),
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Ids: &schemapb.IDs{},
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Topks: make([]int64, 0),
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}, nil
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}
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ret := &schemapb.SearchResultData{
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NumQueries: info.GetNq(),
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TopK: info.GetTopK(),
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FieldsData: make([]*schemapb.FieldData, len(searchResultData[0].FieldsData)),
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Scores: make([]float32, 0),
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Ids: &schemapb.IDs{},
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Topks: make([]int64, 0),
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}
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// Check element-level consistency: all results must have ElementIndices or none
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hasElementIndices := searchResultData[0].ElementIndices != nil
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for i, data := range searchResultData {
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if (data.ElementIndices != nil) != hasElementIndices {
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return nil, fmt.Errorf("inconsistent element-level flag in search results: result[0] has ElementIndices=%v, but result[%d] has ElementIndices=%v",
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hasElementIndices, i, data.ElementIndices != nil)
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}
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}
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if hasElementIndices {
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ret.ElementIndices = &schemapb.LongArray{
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Data: make([]int64, 0),
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}
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}
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resultOffsets := make([][]int64, len(searchResultData))
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groupByValIterator := make([]func(int) any, len(searchResultData))
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for i := range searchResultData {
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resultOffsets[i] = make([]int64, len(searchResultData[i].Topks))
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for j := int64(1); j < info.GetNq(); j++ {
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resultOffsets[i][j] = resultOffsets[i][j-1] + searchResultData[i].Topks[j-1]
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}
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ret.AllSearchCount += searchResultData[i].GetAllSearchCount()
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groupByValIterator[i] = typeutil.GetDataIterator(searchResultData[i].GetGroupByFieldValue())
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}
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gpFieldBuilder, err := typeutil.NewFieldDataBuilder(searchResultData[0].GetGroupByFieldValue().GetType(), true, int(info.GetTopK()))
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if err != nil {
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return ret, merr.WrapErrServiceInternal("failed to construct group by field data builder, this is abnormal as segcore should always set up a group by field, no matter data status, check code on qn", err.Error())
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}
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idxComputers := make([]*typeutil.FieldDataIdxComputer, len(searchResultData))
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for i, srd := range searchResultData {
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idxComputers[i] = typeutil.NewFieldDataIdxComputer(srd.FieldsData)
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}
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var filteredCount int64
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var retSize int64
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maxOutputSize := paramtable.Get().QuotaConfig.MaxOutputSize.GetAsInt64()
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groupSize := info.GetGroupSize()
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if groupSize <= 0 {
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groupSize = 1
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}
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groupBound := info.GetTopK() * groupSize
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for i := int64(0); i < info.GetNq(); i++ {
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offsets := make([]int64, len(searchResultData))
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idSet := make(map[interface{}]struct{})
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groupByValueMap := make(map[interface{}]int64)
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var j int64
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for j = 0; j < groupBound; {
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sel := SelectSearchResultData(searchResultData, resultOffsets, offsets, i)
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if sel == -1 {
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break
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}
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idx := resultOffsets[sel][i] + offsets[sel]
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id := typeutil.GetPK(searchResultData[sel].GetIds(), idx)
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groupByVal := groupByValIterator[sel](int(idx))
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score := searchResultData[sel].Scores[idx]
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if _, ok := idSet[id]; !ok {
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groupCount := groupByValueMap[groupByVal]
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if groupCount == 0 && int64(len(groupByValueMap)) >= info.GetTopK() {
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// exceed the limit for group count, filter this entity
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filteredCount++
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} else if groupCount >= groupSize {
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// exceed the limit for each group, filter this entity
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filteredCount++
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} else {
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fieldsData := searchResultData[sel].FieldsData
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fieldIdxs := idxComputers[sel].Compute(idx)
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retSize += typeutil.AppendFieldData(ret.FieldsData, fieldsData, idx, fieldIdxs...)
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typeutil.AppendPKs(ret.Ids, id)
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ret.Scores = append(ret.Scores, score)
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if searchResultData[sel].ElementIndices != nil && ret.ElementIndices != nil {
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ret.ElementIndices.Data = append(ret.ElementIndices.Data, searchResultData[sel].ElementIndices.Data[idx])
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}
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gpFieldBuilder.Add(groupByVal)
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groupByValueMap[groupByVal] += 1
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idSet[id] = struct{}{}
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j++
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}
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} else {
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// skip entity with same pk
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filteredCount++
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}
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offsets[sel]++
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}
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ret.Topks = append(ret.Topks, j)
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// limit search result to avoid oom
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if retSize > maxOutputSize {
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return nil, fmt.Errorf("search results exceed the maxOutputSize Limit %d", maxOutputSize)
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}
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}
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ret.GroupByFieldValue = gpFieldBuilder.Build()
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if float64(filteredCount) >= 0.3*float64(groupBound) {
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log.Warn("GroupBy reduce filtered too many results, "+
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"this may influence the final result seriously",
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zap.Int64("filteredCount", filteredCount),
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zap.Int64("groupBound", groupBound))
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}
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log.Debug("skip duplicated search result", zap.Int64("count", filteredCount))
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return ret, nil
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}
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func InitSearchReducer(info *reduce.ResultInfo) SearchReduce {
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if info.GetGroupByFieldId() > 0 {
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return &SearchGroupByReduce{}
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}
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return &SearchCommonReduce{}
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}
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