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feat: support groupby size on go-layer(#33544) (#33845) 

related: #33544

Signed-off-by: MrPresent-Han <chun.han@gmail.com>
Co-authored-by: MrPresent-Han <chun.han@gmail.com>
pull/35730/head
Chun Han 2024-08-27 14:21:00 +08:00 committed by GitHub
parent fe83805d56
commit bfd9d86fe9
No known key found for this signature in database
GPG Key ID: B5690EEEBB952194
13 changed files with 683 additions and 316 deletions
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6
internal/proto/internal.proto
View File

@ -96,6 +96,11 @@ message SubSearchRequest {
string metricType = 9;
}
message ExtraSearchParam {
int64 group_by_field_id = 1;
int64 group_size = 2;
}
message SearchRequest {
common.MsgBase base = 1;
int64 reqID = 2;
@ -120,6 +125,7 @@ message SearchRequest {
bool is_advanced = 20;
int64 offset = 21;
common.ConsistencyLevel consistency_level = 22;
ExtraSearchParam extra_search_param = 23;
}
message SubSearchResults {

109
internal/proxy/search_reduce_util.go
View File

@ -58,7 +58,8 @@ func reduceSearchResult(ctx context.Context, reduceInfo *reduceSearchResultInfo)
reduceInfo.topK,
reduceInfo.metricType,
reduceInfo.pkType,
reduceInfo.offset)
reduceInfo.offset,
reduceInfo.queryInfo.GroupSize)
}
return reduceSearchResultDataNoGroupBy(ctx,
reduceInfo.subSearchResultData,
@ -69,7 +70,21 @@ func reduceSearchResult(ctx context.Context, reduceInfo *reduceSearchResultInfo)
reduceInfo.offset)
}
func reduceSearchResultDataWithGroupBy(ctx context.Context, subSearchResultData []*schemapb.SearchResultData, nq int64, topk int64, metricType string, pkType schemapb.DataType, offset int64) (*milvuspb.SearchResults, error) {
type MilvusPKType interface{}
type groupReduceInfo struct {
subSearchIdx int
resultIdx int64
score float32
id MilvusPKType
}
func reduceSearchResultDataWithGroupBy(ctx context.Context, subSearchResultData []*schemapb.SearchResultData,
nq int64, topk int64, metricType string,
pkType schemapb.DataType,
offset int64,
groupSize int64,
) (*milvuspb.SearchResults, error) {
tr := timerecord.NewTimeRecorder("reduceSearchResultData")
defer func() {
tr.CtxElapse(ctx, "done")
@ -131,12 +146,14 @@ func reduceSearchResultDataWithGroupBy(ctx context.Context, subSearchResultData
subSearchNum = len(subSearchResultData)
// for results of each subSearchResultData, storing the start offset of each query of nq queries
subSearchNqOffset = make([][]int64, subSearchNum)
totalResCount int64 = 0
)
for i := 0; i < subSearchNum; i++ {
subSearchNqOffset[i] = make([]int64, subSearchResultData[i].GetNumQueries())
for j := int64(1); j < nq; j++ {
subSearchNqOffset[i][j] = subSearchNqOffset[i][j-1] + subSearchResultData[i].Topks[j-1]
}
totalResCount += subSearchNqOffset[i][nq-1]
}
var (
@ -146,6 +163,7 @@ func reduceSearchResultDataWithGroupBy(ctx context.Context, subSearchResultData
var retSize int64
maxOutputSize := paramtable.Get().QuotaConfig.MaxOutputSize.GetAsInt64()
groupBound := groupSize * limit
// reducing nq * topk results
for i := int64(0); i < nq; i++ {
@ -155,15 +173,14 @@ func reduceSearchResultDataWithGroupBy(ctx context.Context, subSearchResultData
cursors = make([]int64, subSearchNum)
j int64
idSet = make(map[interface{}]struct{})
groupByValSet = make(map[interface{}]struct{})
pkSet = make(map[interface{}]struct{})
groupByValMap = make(map[interface{}][]*groupReduceInfo)
skipOffsetMap = make(map[interface{}]bool)
groupByValList = make([]interface{}, limit)
groupByValIdx = 0
)
// keep limit results
for j = 0; j < limit; {
// From all the sub-query result sets of the i-th query vector,
// find the sub-query result set index of the score j-th data,
// and the index of the data in schemapb.SearchResultData
for j = 0; j < groupBound; {
subSearchIdx, resultDataIdx := selectHighestScoreIndex(subSearchResultData, subSearchNqOffset, cursors, i)
if subSearchIdx == -1 {
break
@ -171,44 +188,63 @@ func reduceSearchResultDataWithGroupBy(ctx context.Context, subSearchResultData
subSearchRes := subSearchResultData[subSearchIdx]
id := typeutil.GetPK(subSearchRes.GetIds(), resultDataIdx)
score := subSearchRes.Scores[resultDataIdx]
score := subSearchRes.GetScores()[resultDataIdx]
groupByVal := typeutil.GetData(subSearchRes.GetGroupByFieldValue(), int(resultDataIdx))
if groupByVal == nil {
return nil, errors.New("get nil groupByVal from subSearchRes, wrong states, as milvus doesn't support nil value," +
"there must be sth wrong on queryNode side")
}
// remove duplicates
if _, ok := idSet[id]; !ok {
_, groupByValExist := groupByValSet[groupByVal]
if !groupByValExist {
groupByValSet[groupByVal] = struct{}{}
if int64(len(groupByValSet)) <= offset {
continue
// skip offset groups
if _, ok := pkSet[id]; !ok {
if int64(len(skipOffsetMap)) < offset || skipOffsetMap[groupByVal] {
skipOffsetMap[groupByVal] = true
// the first offset's group will be ignored
skipDupCnt++
} else if len(groupByValMap[groupByVal]) == 0 && int64(len(groupByValMap)) >= limit {
// skip when groupbyMap has been full and found new groupByVal
skipDupCnt++
} else if int64(len(groupByValMap[groupByVal])) >= groupSize {
// skip when target group has been full
skipDupCnt++
} else {
if len(groupByValMap[groupByVal]) == 0 {
groupByValList[groupByValIdx] = groupByVal
groupByValIdx++
}
retSize += typeutil.AppendFieldData(ret.Results.FieldsData, subSearchResultData[subSearchIdx].FieldsData, resultDataIdx)
typeutil.AppendPKs(ret.Results.Ids, id)
ret.Results.Scores = append(ret.Results.Scores, score)
idSet[id] = struct{}{}
if err := typeutil.AppendGroupByValue(ret.Results, groupByVal, subSearchRes.GetGroupByFieldValue().GetType()); err != nil {
groupByValMap[groupByVal] = append(groupByValMap[groupByVal], &groupReduceInfo{
subSearchIdx: subSearchIdx,
resultIdx: resultDataIdx, id: id, score: score,
})
pkSet[id] = struct{}{}
j++
}
} else {
skipDupCnt++
}
cursors[subSearchIdx]++
}
// assemble all eligible values in group
// values in groupByValList is sorted by the highest score in each group
for _, groupVal := range groupByValList {
if groupVal != nil {
groupEntities := groupByValMap[groupVal]
for _, groupEntity := range groupEntities {
subResData := subSearchResultData[groupEntity.subSearchIdx]
retSize += typeutil.AppendFieldData(ret.Results.FieldsData, subResData.FieldsData, groupEntity.resultIdx)
typeutil.AppendPKs(ret.Results.Ids, groupEntity.id)
ret.Results.Scores = append(ret.Results.Scores, groupEntity.score)
if err := typeutil.AppendGroupByValue(ret.Results, groupVal, subResData.GetGroupByFieldValue().GetType()); err != nil {
log.Ctx(ctx).Error("failed to append groupByValues", zap.Error(err))
return ret, err
}
j++
} else {
// skip entity with same groupby
skipDupCnt++
}
} else {
// skip entity with same id
skipDupCnt++
}
cursors[subSearchIdx]++
}
if realTopK != -1 && realTopK != j {
log.Ctx(ctx).Warn("Proxy Reduce Search Result", zap.Error(errors.New("the length (topk) between all result of query is different")))
// return nil, errors.New("the length (topk) between all result of query is different")
}
realTopK = j
ret.Results.Topks = append(ret.Results.Topks, realTopK)
@ -218,10 +254,13 @@ func reduceSearchResultDataWithGroupBy(ctx context.Context, subSearchResultData
return nil, fmt.Errorf("search results exceed the maxOutputSize Limit %d", maxOutputSize)
}
}
log.Ctx(ctx).Debug("skip duplicated search result", zap.Int64("count", skipDupCnt))
log.Ctx(ctx).Debug("skip duplicated search result when doing group by", zap.Int64("count", skipDupCnt))
if skipDupCnt > 0 {
log.Ctx(ctx).Info("skip duplicated search result", zap.Int64("count", skipDupCnt))
if float64(skipDupCnt) >= float64(totalResCount)*0.3 {
log.Warn("GroupBy reduce skipped too many results, "+
"this may influence the final result seriously",
zap.Int64("skipDupCnt", skipDupCnt),
zap.Int64("groupBound", groupBound))
}
ret.Results.TopK = realTopK // realTopK is the topK of the nq-th query

16
internal/proxy/search_util.go
View File

@ -99,7 +99,7 @@ func parseSearchInfo(searchParamsPair []*commonpb.KeyValuePair, schema *schemapb
searchParamStr = ""
}
// 5. parse group by field
// 5. parse group by field and group by size
groupByFieldName, err := funcutil.GetAttrByKeyFromRepeatedKV(GroupByFieldKey, searchParamsPair)
if err != nil {
groupByFieldName = ""
@ -118,7 +118,18 @@ func parseSearchInfo(searchParamsPair []*commonpb.KeyValuePair, schema *schemapb
}
}
// 6. disable groupBy for iterator and range search
var groupSize int64
groupSizeStr, err := funcutil.GetAttrByKeyFromRepeatedKV(GroupSizeKey, searchParamsPair)
if err != nil {
groupSize = 1
} else {
groupSize, err = strconv.ParseInt(groupSizeStr, 0, 64)
if err != nil || groupSize <= 0 {
groupSize = 1
}
}
// 6. parse iterator tag, prevent trying to groupBy when doing iteration or doing range-search
if isIterator == "True" && groupByFieldId > 0 {
return nil, 0, merr.WrapErrParameterInvalid("", "",
"Not allowed to do groupBy when doing iteration")
@ -134,6 +145,7 @@ func parseSearchInfo(searchParamsPair []*commonpb.KeyValuePair, schema *schemapb
SearchParams: searchParamStr,
RoundDecimal: roundDecimal,
GroupByFieldId: groupByFieldId,
GroupSize: groupSize,
}, offset, nil
}

1
internal/proxy/task.go
View File

@ -49,6 +49,7 @@ const (
ReduceStopForBestKey = "reduce_stop_for_best"
IteratorField = "iterator"
GroupByFieldKey = "group_by_field"
GroupSizeKey = "group_size"
AnnsFieldKey = "anns_field"
TopKKey = "topk"
NQKey = "nq"

2
internal/proxy/task_search.go
View File

@ -456,12 +456,12 @@ func (t *searchTask) initSearchRequest(ctx context.Context) error {
if err != nil {
return err
}
t.SearchRequest.PlaceholderGroup = t.request.PlaceholderGroup
t.SearchRequest.Topk = queryInfo.GetTopk()
t.SearchRequest.MetricType = queryInfo.GetMetricType()
t.queryInfos = append(t.queryInfos, queryInfo)
t.SearchRequest.DslType = commonpb.DslType_BoolExprV1
t.SearchRequest.ExtraSearchParam = &internalpb.ExtraSearchParam{GroupByFieldId: queryInfo.GroupByFieldId, GroupSize: queryInfo.GroupSize}
log.Debug("proxy init search request",
zap.Int64s("plan.OutputFieldIds", plan.GetOutputFieldIds()),
zap.Stringer("plan", plan)) // may be very large if large term passed.

78
internal/proxy/task_search_test.go
View File

@ -1706,6 +1706,7 @@ func TestTaskSearch_reduceGroupBySearchResultData(t *testing.T) {
}
queryInfo := &planpb.QueryInfo{
GroupByFieldId: 1,
GroupSize: 1,
}
reduced, err := reduceSearchResult(context.TODO(), NewReduceSearchResultInfo(results, nq, topK, metric.L2,
schemapb.DataType_Int64, 0, queryInfo))
@ -1765,6 +1766,7 @@ func TestTaskSearch_reduceGroupBySearchResultDataWithOffset(t *testing.T) {
queryInfo := &planpb.QueryInfo{
GroupByFieldId: 1,
GroupSize: 1,
}
reduced, err := reduceSearchResult(context.TODO(), NewReduceSearchResultInfo(results, nq, limit+offset, metric.L2,
schemapb.DataType_Int64, offset, queryInfo))
@ -1777,6 +1779,82 @@ func TestTaskSearch_reduceGroupBySearchResultDataWithOffset(t *testing.T) {
assert.NoError(t, err)
}
func TestTaskSearch_reduceGroupBySearchWithGroupSizeMoreThanOne(t *testing.T) {
var (
nq int64 = 2
topK int64 = 5
)
ids := [][]int64{
{1, 3, 5, 7, 9, 1, 3, 5, 7, 9},
{2, 4, 6, 8, 10, 2, 4, 6, 8, 10},
}
scores := [][]float32{
{10, 8, 6, 4, 2, 10, 8, 6, 4, 2},
{9, 7, 5, 3, 1, 9, 7, 5, 3, 1},
}
groupByValuesArr := [][][]int64{
{
{1, 2, 3, 4, 5, 1, 2, 3, 4, 5},
{1, 2, 3, 4, 5, 1, 2, 3, 4, 5},
},
{
{1, 2, 3, 4, 5, 1, 2, 3, 4, 5},
{6, 8, 3, 4, 5, 6, 8, 3, 4, 5},
},
}
expectedIDs := [][]int64{
{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10},
{1, 2, 3, 4, 5, 6, 1, 2, 3, 4, 5, 6},
}
expectedScores := [][]float32{
{-10, -9, -8, -7, -6, -5, -4, -3, -2, -1, -10, -9, -8, -7, -6, -5, -4, -3, -2, -1},
{-10, -9, -8, -7, -6, -5, -10, -9, -8, -7, -6, -5},
}
expectedGroupByValues := [][]int64{
{1, 1, 2, 2, 3, 3, 4, 4, 5, 5, 1, 1, 2, 2, 3, 3, 4, 4, 5, 5},
{1, 6, 2, 8, 3, 3, 1, 6, 2, 8, 3, 3},
}
for i, groupByValues := range groupByValuesArr {
t.Run("Group By correctness", func(t *testing.T) {
var results []*schemapb.SearchResultData
for j := range ids {
result := getSearchResultData(nq, topK)
result.Ids.IdField = &schemapb.IDs_IntId{IntId: &schemapb.LongArray{Data: ids[j]}}
result.Scores = scores[j]
result.Topks = []int64{topK, topK}
result.GroupByFieldValue = &schemapb.FieldData{
Type: schemapb.DataType_Int64,
Field: &schemapb.FieldData_Scalars{
Scalars: &schemapb.ScalarField{
Data: &schemapb.ScalarField_LongData{
LongData: &schemapb.LongArray{
Data: groupByValues[j],
},
},
},
},
}
results = append(results, result)
}
queryInfo := &planpb.QueryInfo{
GroupByFieldId: 1,
GroupSize: 2,
}
reduced, err := reduceSearchResult(context.TODO(), NewReduceSearchResultInfo(results, nq, topK, metric.L2,
schemapb.DataType_Int64, 0, queryInfo))
resultIDs := reduced.GetResults().GetIds().GetIntId().Data
resultScores := reduced.GetResults().GetScores()
resultGroupByValues := reduced.GetResults().GetGroupByFieldValue().GetScalars().GetLongData().GetData()
assert.EqualValues(t, expectedIDs[i], resultIDs)
assert.EqualValues(t, expectedScores[i], resultScores)
assert.EqualValues(t, expectedGroupByValues[i], resultGroupByValues)
assert.NoError(t, err)
})
}
}
func TestSearchTask_ErrExecute(t *testing.T) {
var (
err error

7
internal/querynodev2/delegator/delegator.go
View File

@ -351,9 +351,12 @@ func (sd *shardDelegator) Search(ctx context.Context, req *querypb.SearchRequest
return segments.ReduceSearchResults(ctx,
results,
searchReq.Req.GetNq(),
segments.NewReduceInfo(searchReq.Req.GetNq(),
searchReq.Req.GetTopk(),
searchReq.Req.GetMetricType())
searchReq.Req.GetExtraSearchParam().GetGroupByFieldId(),
searchReq.Req.GetExtraSearchParam().GetGroupSize(),
searchReq.Req.GetMetricType()),
)
})
futures[index] = future
}

6
internal/querynodev2/handlers.go
View File

@ -388,7 +388,11 @@ func (node *QueryNode) searchChannel(ctx context.Context, req *querypb.SearchReq
if req.GetReq().GetIsAdvanced() {
resp, err = segments.ReduceAdvancedSearchResults(ctx, results, req.Req.GetNq())
} else {
resp, err = segments.ReduceSearchResults(ctx, results, req.Req.GetNq(), req.Req.GetTopk(), req.Req.GetMetricType())
resp, err = segments.ReduceSearchResults(ctx, results, segments.NewReduceInfo(req.Req.GetNq(),
req.Req.GetTopk(),
req.Req.GetExtraSearchParam().GetGroupByFieldId(),
req.Req.GetExtraSearchParam().GetGroupSize(),
req.Req.GetMetricType()))
}
if err != nil {
return nil, err

106
internal/querynodev2/segments/result.go
View File

@ -42,7 +42,7 @@ var _ typeutil.ResultWithID = &internalpb.RetrieveResults{}
var _ typeutil.ResultWithID = &segcorepb.RetrieveResults{}
func ReduceSearchResults(ctx context.Context, results []*internalpb.SearchResults, nq int64, topk int64, metricType string) (*internalpb.SearchResults, error) {
func ReduceSearchResults(ctx context.Context, results []*internalpb.SearchResults, info *ReduceInfo) (*internalpb.SearchResults, error) {
results = lo.Filter(results, func(result *internalpb.SearchResults, _ int) bool {
return result != nil && result.GetSlicedBlob() != nil
})
@ -60,8 +60,8 @@ func ReduceSearchResults(ctx context.Context, results []*internalpb.SearchResult
channelsMvcc[ch] = ts
}
// shouldn't let new SearchResults.MetricType to be empty, though the req.MetricType is empty
if metricType == "" {
metricType = r.MetricType
if info.metricType == "" {
info.metricType = r.MetricType
}
}
log := log.Ctx(ctx)
@ -80,12 +80,13 @@ func ReduceSearchResults(ctx context.Context, results []*internalpb.SearchResult
zap.Int64("topk", sData.TopK))
}
reducedResultData, err := ReduceSearchResultData(ctx, searchResultData, nq, topk)
searchReduce := InitSearchReducer(info)
reducedResultData, err := searchReduce.ReduceSearchResultData(ctx, searchResultData, info)
if err != nil {
log.Warn("shard leader reduce errors", zap.Error(err))
return nil, err
}
searchResults, err := EncodeSearchResultData(ctx, reducedResultData, nq, topk, metricType)
searchResults, err := EncodeSearchResultData(ctx, reducedResultData, info.nq, info.topK, info.metricType)
if err != nil {
log.Warn("shard leader encode search result errors", zap.Error(err))
return nil, err
@ -207,101 +208,6 @@ func MergeToAdvancedResults(ctx context.Context, results []*internalpb.SearchRes
return searchResults, nil
}
func ReduceSearchResultData(ctx context.Context, searchResultData []*schemapb.SearchResultData, nq int64, topk int64) (*schemapb.SearchResultData, error) {
ctx, sp := otel.Tracer(typeutil.QueryNodeRole).Start(ctx, "ReduceSearchResultData")
defer sp.End()
log := log.Ctx(ctx)
if len(searchResultData) == 0 {
return &schemapb.SearchResultData{
NumQueries: nq,
TopK: topk,
FieldsData: make([]*schemapb.FieldData, 0),
Scores: make([]float32, 0),
Ids: &schemapb.IDs{},
Topks: make([]int64, 0),
}, nil
}
ret := &schemapb.SearchResultData{
NumQueries: nq,
TopK: topk,
FieldsData: make([]*schemapb.FieldData, len(searchResultData[0].FieldsData)),
Scores: make([]float32, 0),
Ids: &schemapb.IDs{},
Topks: make([]int64, 0),
}
resultOffsets := make([][]int64, len(searchResultData))
for i := 0; i < len(searchResultData); i++ {
resultOffsets[i] = make([]int64, len(searchResultData[i].Topks))
for j := int64(1); j < nq; j++ {
resultOffsets[i][j] = resultOffsets[i][j-1] + searchResultData[i].Topks[j-1]
}
ret.AllSearchCount += searchResultData[i].GetAllSearchCount()
}
var skipDupCnt int64
var retSize int64
maxOutputSize := paramtable.Get().QuotaConfig.MaxOutputSize.GetAsInt64()
for i := int64(0); i < nq; i++ {
offsets := make([]int64, len(searchResultData))
idSet := make(map[interface{}]struct{})
groupByValueSet := make(map[interface{}]struct{})
var j int64
for j = 0; j < topk; {
sel := SelectSearchResultData(searchResultData, resultOffsets, offsets, i)
if sel == -1 {
break
}
idx := resultOffsets[sel][i] + offsets[sel]
id := typeutil.GetPK(searchResultData[sel].GetIds(), idx)
groupByVal := typeutil.GetData(searchResultData[sel].GetGroupByFieldValue(), int(idx))
score := searchResultData[sel].Scores[idx]
// remove duplicates
if _, ok := idSet[id]; !ok {
groupByValExist := false
if groupByVal != nil {
_, groupByValExist = groupByValueSet[groupByVal]
}
if !groupByValExist {
retSize += typeutil.AppendFieldData(ret.FieldsData, searchResultData[sel].FieldsData, idx)
typeutil.AppendPKs(ret.Ids, id)
ret.Scores = append(ret.Scores, score)
if groupByVal != nil {
groupByValueSet[groupByVal] = struct{}{}
if err := typeutil.AppendGroupByValue(ret, groupByVal, searchResultData[sel].GetGroupByFieldValue().GetType()); err != nil {
log.Error("Failed to append groupByValues", zap.Error(err))
return ret, err
}
}
idSet[id] = struct{}{}
j++
}
} else {
// skip entity with same id
skipDupCnt++
}
offsets[sel]++
}
// if realTopK != -1 && realTopK != j {
// log.Warn("Proxy Reduce Search Result", zap.Error(errors.New("the length (topk) between all result of query is different")))
// // return nil, errors.New("the length (topk) between all result of query is different")
// }
ret.Topks = append(ret.Topks, j)
// limit search result to avoid oom
if retSize > maxOutputSize {
return nil, fmt.Errorf("search results exceed the maxOutputSize Limit %d", maxOutputSize)
}
}
log.Debug("skip duplicated search result", zap.Int64("count", skipDupCnt))
return ret, nil
}
func SelectSearchResultData(dataArray []*schemapb.SearchResultData, resultOffsets [][]int64, offsets []int64, qi int64) int {
var (
sel = -1

171
internal/querynodev2/segments/result_test.go
View File

@ -702,177 +702,6 @@ func (suite *ResultSuite) TestResult_MergeStopForBestResult() {
})
}
func (suite *ResultSuite) TestResult_ReduceSearchResultData() {
const (
nq = 1
topk = 4
metricType = "L2"
)
suite.Run("case1", func() {
ids := []int64{1, 2, 3, 4}
scores := []float32{-1.0, -2.0, -3.0, -4.0}
topks := []int64{int64(len(ids))}
data1 := genSearchResultData(nq, topk, ids, scores, topks)
data2 := genSearchResultData(nq, topk, ids, scores, topks)
dataArray := make([]*schemapb.SearchResultData, 0)
dataArray = append(dataArray, data1)
dataArray = append(dataArray, data2)
res, err := ReduceSearchResultData(context.TODO(), dataArray, nq, topk)
suite.Nil(err)
suite.Equal(ids, res.Ids.GetIntId().Data)
suite.Equal(scores, res.Scores)
})
suite.Run("case2", func() {
ids1 := []int64{1, 2, 3, 4}
scores1 := []float32{-1.0, -2.0, -3.0, -4.0}
topks1 := []int64{int64(len(ids1))}
ids2 := []int64{5, 1, 3, 4}
scores2 := []float32{-1.0, -1.0, -3.0, -4.0}
topks2 := []int64{int64(len(ids2))}
data1 := genSearchResultData(nq, topk, ids1, scores1, topks1)
data2 := genSearchResultData(nq, topk, ids2, scores2, topks2)
dataArray := make([]*schemapb.SearchResultData, 0)
dataArray = append(dataArray, data1)
dataArray = append(dataArray, data2)
res, err := ReduceSearchResultData(context.TODO(), dataArray, nq, topk)
suite.Nil(err)
suite.ElementsMatch([]int64{1, 5, 2, 3}, res.Ids.GetIntId().Data)
})
}
func (suite *ResultSuite) TestResult_SearchGroupByResult() {
const (
nq = 1
topk = 4
)
suite.Run("reduce_group_by_int", func() {
ids1 := []int64{1, 2, 3, 4}
scores1 := []float32{-1.0, -2.0, -3.0, -4.0}
topks1 := []int64{int64(len(ids1))}
ids2 := []int64{5, 1, 3, 4}
scores2 := []float32{-1.0, -1.0, -3.0, -4.0}
topks2 := []int64{int64(len(ids2))}
data1 := genSearchResultData(nq, topk, ids1, scores1, topks1)
data2 := genSearchResultData(nq, topk, ids2, scores2, topks2)
data1.GroupByFieldValue = &schemapb.FieldData{
Type: schemapb.DataType_Int8,
Field: &schemapb.FieldData_Scalars{
Scalars: &schemapb.ScalarField{
Data: &schemapb.ScalarField_IntData{
IntData: &schemapb.IntArray{
Data: []int32{2, 3, 4, 5},
},
},
},
},
}
data2.GroupByFieldValue = &schemapb.FieldData{
Type: schemapb.DataType_Int8,
Field: &schemapb.FieldData_Scalars{
Scalars: &schemapb.ScalarField{
Data: &schemapb.ScalarField_IntData{
IntData: &schemapb.IntArray{
Data: []int32{2, 3, 4, 5},
},
},
},
},
}
dataArray := make([]*schemapb.SearchResultData, 0)
dataArray = append(dataArray, data1)
dataArray = append(dataArray, data2)
res, err := ReduceSearchResultData(context.TODO(), dataArray, nq, topk)
suite.Nil(err)
suite.ElementsMatch([]int64{1, 2, 3, 4}, res.Ids.GetIntId().Data)
suite.ElementsMatch([]float32{-1.0, -2.0, -3.0, -4.0}, res.Scores)
suite.ElementsMatch([]int32{2, 3, 4, 5}, res.GroupByFieldValue.GetScalars().GetIntData().Data)
})
suite.Run("reduce_group_by_bool", func() {
ids1 := []int64{1, 2}
scores1 := []float32{-1.0, -2.0}
topks1 := []int64{int64(len(ids1))}
ids2 := []int64{3, 4}
scores2 := []float32{-1.0, -1.0}
topks2 := []int64{int64(len(ids2))}
data1 := genSearchResultData(nq, topk, ids1, scores1, topks1)
data2 := genSearchResultData(nq, topk, ids2, scores2, topks2)
data1.GroupByFieldValue = &schemapb.FieldData{
Type: schemapb.DataType_Bool,
Field: &schemapb.FieldData_Scalars{
Scalars: &schemapb.ScalarField{
Data: &schemapb.ScalarField_BoolData{
BoolData: &schemapb.BoolArray{
Data: []bool{true, false},
},
},
},
},
}
data2.GroupByFieldValue = &schemapb.FieldData{
Type: schemapb.DataType_Bool,
Field: &schemapb.FieldData_Scalars{
Scalars: &schemapb.ScalarField{
Data: &schemapb.ScalarField_BoolData{
BoolData: &schemapb.BoolArray{
Data: []bool{true, false},
},
},
},
},
}
dataArray := make([]*schemapb.SearchResultData, 0)
dataArray = append(dataArray, data1)
dataArray = append(dataArray, data2)
res, err := ReduceSearchResultData(context.TODO(), dataArray, nq, topk)
suite.Nil(err)
suite.ElementsMatch([]int64{1, 4}, res.Ids.GetIntId().Data)
suite.ElementsMatch([]float32{-1.0, -1.0}, res.Scores)
suite.ElementsMatch([]bool{true, false}, res.GroupByFieldValue.GetScalars().GetBoolData().Data)
})
suite.Run("reduce_group_by_string", func() {
ids1 := []int64{1, 2, 3, 4}
scores1 := []float32{-1.0, -2.0, -3.0, -4.0}
topks1 := []int64{int64(len(ids1))}
ids2 := []int64{5, 1, 3, 4}
scores2 := []float32{-1.0, -1.0, -3.0, -4.0}
topks2 := []int64{int64(len(ids2))}
data1 := genSearchResultData(nq, topk, ids1, scores1, topks1)
data2 := genSearchResultData(nq, topk, ids2, scores2, topks2)
data1.GroupByFieldValue = &schemapb.FieldData{
Type: schemapb.DataType_VarChar,
Field: &schemapb.FieldData_Scalars{
Scalars: &schemapb.ScalarField{
Data: &schemapb.ScalarField_StringData{
StringData: &schemapb.StringArray{
Data: []string{"1", "2", "3", "4"},
},
},
},
},
}
data2.GroupByFieldValue = &schemapb.FieldData{
Type: schemapb.DataType_VarChar,
Field: &schemapb.FieldData_Scalars{
Scalars: &schemapb.ScalarField{
Data: &schemapb.ScalarField_StringData{
StringData: &schemapb.StringArray{
Data: []string{"1", "2", "3", "4"},
},
},
},
},
}
dataArray := make([]*schemapb.SearchResultData, 0)
dataArray = append(dataArray, data1)
dataArray = append(dataArray, data2)
res, err := ReduceSearchResultData(context.TODO(), dataArray, nq, topk)
suite.Nil(err)
suite.ElementsMatch([]int64{1, 2, 3, 4}, res.Ids.GetIntId().Data)
suite.ElementsMatch([]float32{-1.0, -2.0, -3.0, -4.0}, res.Scores)
suite.ElementsMatch([]string{"1", "2", "3", "4"}, res.GroupByFieldValue.GetScalars().GetStringData().Data)
})
}
func (suite *ResultSuite) TestResult_SelectSearchResultData_int() {
type args struct {
dataArray []*schemapb.SearchResultData

227
internal/querynodev2/segments/search_reduce.go Normal file
View File

@ -0,0 +1,227 @@
package segments
import (
"context"
"fmt"
"go.opentelemetry.io/otel"
"go.uber.org/zap"
"github.com/milvus-io/milvus-proto/go-api/v2/schemapb"
"github.com/milvus-io/milvus/pkg/log"
"github.com/milvus-io/milvus/pkg/util/merr"
"github.com/milvus-io/milvus/pkg/util/paramtable"
"github.com/milvus-io/milvus/pkg/util/typeutil"
)
type ReduceInfo struct {
nq int64
topK int64
groupByFieldID int64
groupSize int64
metricType string
}
func NewReduceInfo(nq int64, topK int64, groupByFieldID int64, groupSize int64, metric string) *ReduceInfo {
return &ReduceInfo{nq, topK, groupByFieldID, groupSize, metric}
}
type SearchReduce interface {
ReduceSearchResultData(ctx context.Context, searchResultData []*schemapb.SearchResultData, info *ReduceInfo) (*schemapb.SearchResultData, error)
}
type SearchCommonReduce struct{}
func (scr *SearchCommonReduce) ReduceSearchResultData(ctx context.Context, searchResultData []*schemapb.SearchResultData, info *ReduceInfo) (*schemapb.SearchResultData, error) {
ctx, sp := otel.Tracer(typeutil.QueryNodeRole).Start(ctx, "ReduceSearchResultData")
defer sp.End()
log := log.Ctx(ctx)
if len(searchResultData) == 0 {
return &schemapb.SearchResultData{
NumQueries: info.nq,
TopK: info.topK,
FieldsData: make([]*schemapb.FieldData, 0),
Scores: make([]float32, 0),
Ids: &schemapb.IDs{},
Topks: make([]int64, 0),
}, nil
}
ret := &schemapb.SearchResultData{
NumQueries: info.nq,
TopK: info.topK,
FieldsData: make([]*schemapb.FieldData, len(searchResultData[0].FieldsData)),
Scores: make([]float32, 0),
Ids: &schemapb.IDs{},
Topks: make([]int64, 0),
}
resultOffsets := make([][]int64, len(searchResultData))
for i := 0; i < len(searchResultData); i++ {
resultOffsets[i] = make([]int64, len(searchResultData[i].Topks))
for j := int64(1); j < info.nq; j++ {
resultOffsets[i][j] = resultOffsets[i][j-1] + searchResultData[i].Topks[j-1]
}
ret.AllSearchCount += searchResultData[i].GetAllSearchCount()
}
var skipDupCnt int64
var retSize int64
maxOutputSize := paramtable.Get().QuotaConfig.MaxOutputSize.GetAsInt64()
for i := int64(0); i < info.nq; i++ {
offsets := make([]int64, len(searchResultData))
idSet := make(map[interface{}]struct{})
var j int64
for j = 0; j < info.topK; {
sel := SelectSearchResultData(searchResultData, resultOffsets, offsets, i)
if sel == -1 {
break
}
idx := resultOffsets[sel][i] + offsets[sel]
id := typeutil.GetPK(searchResultData[sel].GetIds(), idx)
score := searchResultData[sel].Scores[idx]
// remove duplicates
if _, ok := idSet[id]; !ok {
retSize += typeutil.AppendFieldData(ret.FieldsData, searchResultData[sel].FieldsData, idx)
typeutil.AppendPKs(ret.Ids, id)
ret.Scores = append(ret.Scores, score)
idSet[id] = struct{}{}
j++
} else {
// skip entity with same id
skipDupCnt++
}
offsets[sel]++
}
// if realTopK != -1 && realTopK != j {
// log.Warn("Proxy Reduce Search Result", zap.Error(errors.New("the length (topk) between all result of query is different")))
// // return nil, errors.New("the length (topk) between all result of query is different")
// }
ret.Topks = append(ret.Topks, j)
// limit search result to avoid oom
if retSize > maxOutputSize {
return nil, fmt.Errorf("search results exceed the maxOutputSize Limit %d", maxOutputSize)
}
}
log.Debug("skip duplicated search result", zap.Int64("count", skipDupCnt))
return ret, nil
}
type SearchGroupByReduce struct{}
func (sbr *SearchGroupByReduce) ReduceSearchResultData(ctx context.Context, searchResultData []*schemapb.SearchResultData, info *ReduceInfo) (*schemapb.SearchResultData, error) {
ctx, sp := otel.Tracer(typeutil.QueryNodeRole).Start(ctx, "ReduceSearchResultData")
defer sp.End()
log := log.Ctx(ctx)
if len(searchResultData) == 0 {
return &schemapb.SearchResultData{
NumQueries: info.nq,
TopK: info.topK,
FieldsData: make([]*schemapb.FieldData, 0),
Scores: make([]float32, 0),
Ids: &schemapb.IDs{},
Topks: make([]int64, 0),
}, nil
}
ret := &schemapb.SearchResultData{
NumQueries: info.nq,
TopK: info.topK,
FieldsData: make([]*schemapb.FieldData, len(searchResultData[0].FieldsData)),
Scores: make([]float32, 0),
Ids: &schemapb.IDs{},
Topks: make([]int64, 0),
}
resultOffsets := make([][]int64, len(searchResultData))
for i := 0; i < len(searchResultData); i++ {
resultOffsets[i] = make([]int64, len(searchResultData[i].Topks))
for j := int64(1); j < info.nq; j++ {
resultOffsets[i][j] = resultOffsets[i][j-1] + searchResultData[i].Topks[j-1]
}
ret.AllSearchCount += searchResultData[i].GetAllSearchCount()
}
var filteredCount int64
var retSize int64
maxOutputSize := paramtable.Get().QuotaConfig.MaxOutputSize.GetAsInt64()
groupSize := info.groupSize
if groupSize <= 0 {
groupSize = 1
}
groupBound := info.topK * groupSize
for i := int64(0); i < info.nq; i++ {
offsets := make([]int64, len(searchResultData))
idSet := make(map[interface{}]struct{})
groupByValueMap := make(map[interface{}]int64)
var j int64
for j = 0; j < groupBound; {
sel := SelectSearchResultData(searchResultData, resultOffsets, offsets, i)
if sel == -1 {
break
}
idx := resultOffsets[sel][i] + offsets[sel]
id := typeutil.GetPK(searchResultData[sel].GetIds(), idx)
groupByVal := typeutil.GetData(searchResultData[sel].GetGroupByFieldValue(), int(idx))
score := searchResultData[sel].Scores[idx]
if _, ok := idSet[id]; !ok {
if groupByVal == nil {
return ret, merr.WrapErrParameterMissing("GroupByVal returned from segment cannot be null")
}
groupCount := groupByValueMap[groupByVal]
if groupCount == 0 && int64(len(groupByValueMap)) >= info.topK {
// exceed the limit for group count, filter this entity
filteredCount++
} else if groupCount >= groupSize {
// exceed the limit for each group, filter this entity
filteredCount++
} else {
retSize += typeutil.AppendFieldData(ret.FieldsData, searchResultData[sel].FieldsData, idx)
typeutil.AppendPKs(ret.Ids, id)
ret.Scores = append(ret.Scores, score)
if err := typeutil.AppendGroupByValue(ret, groupByVal, searchResultData[sel].GetGroupByFieldValue().GetType()); err != nil {
log.Error("Failed to append groupByValues", zap.Error(err))
return ret, err
}
groupByValueMap[groupByVal] += 1
idSet[id] = struct{}{}
j++
}
} else {
// skip entity with same pk
filteredCount++
}
offsets[sel]++
}
ret.Topks = append(ret.Topks, j)
// limit search result to avoid oom
if retSize > maxOutputSize {
return nil, fmt.Errorf("search results exceed the maxOutputSize Limit %d", maxOutputSize)
}
}
if float64(filteredCount) >= 0.3*float64(groupBound) {
log.Warn("GroupBy reduce filtered too many results, "+
"this may influence the final result seriously",
zap.Int64("filteredCount", filteredCount),
zap.Int64("groupBound", groupBound))
}
log.Debug("skip duplicated search result", zap.Int64("count", filteredCount))
return ret, nil
}
func InitSearchReducer(info *ReduceInfo) SearchReduce {
if info.groupByFieldID > 0 {
return &SearchGroupByReduce{}
}
return &SearchCommonReduce{}
}

258
internal/querynodev2/segments/search_reduce_test.go Normal file
View File

@ -0,0 +1,258 @@
package segments
import (
"context"
"testing"
"github.com/stretchr/testify/suite"
"github.com/milvus-io/milvus-proto/go-api/v2/schemapb"
"github.com/milvus-io/milvus/pkg/util/paramtable"
)
type SearchReduceSuite struct {
suite.Suite
}
func (suite *SearchReduceSuite) TestResult_ReduceSearchResultData() {
const (
nq = 1
topk = 4
)
suite.Run("case1", func() {
ids := []int64{1, 2, 3, 4}
scores := []float32{-1.0, -2.0, -3.0, -4.0}
topks := []int64{int64(len(ids))}
data1 := genSearchResultData(nq, topk, ids, scores, topks)
data2 := genSearchResultData(nq, topk, ids, scores, topks)
dataArray := make([]*schemapb.SearchResultData, 0)
dataArray = append(dataArray, data1)
dataArray = append(dataArray, data2)
reduceInfo := &ReduceInfo{nq: nq, topK: topk}
searchReduce := InitSearchReducer(reduceInfo)
res, err := searchReduce.ReduceSearchResultData(context.TODO(), dataArray, reduceInfo)
suite.Nil(err)
suite.Equal(ids, res.Ids.GetIntId().Data)
suite.Equal(scores, res.Scores)
})
suite.Run("case2", func() {
ids1 := []int64{1, 2, 3, 4}
scores1 := []float32{-1.0, -2.0, -3.0, -4.0}
topks1 := []int64{int64(len(ids1))}
ids2 := []int64{5, 1, 3, 4}
scores2 := []float32{-1.0, -1.0, -3.0, -4.0}
topks2 := []int64{int64(len(ids2))}
data1 := genSearchResultData(nq, topk, ids1, scores1, topks1)
data2 := genSearchResultData(nq, topk, ids2, scores2, topks2)
dataArray := make([]*schemapb.SearchResultData, 0)
dataArray = append(dataArray, data1)
dataArray = append(dataArray, data2)
reduceInfo := &ReduceInfo{nq: nq, topK: topk}
searchReduce := InitSearchReducer(reduceInfo)
res, err := searchReduce.ReduceSearchResultData(context.TODO(), dataArray, reduceInfo)
suite.Nil(err)
suite.ElementsMatch([]int64{1, 5, 2, 3}, res.Ids.GetIntId().Data)
})
}
func (suite *SearchReduceSuite) TestResult_SearchGroupByResult() {
const (
nq = 1
topk = 4
)
suite.Run("reduce_group_by_int", func() {
ids1 := []int64{1, 2, 3, 4}
scores1 := []float32{-1.0, -2.0, -3.0, -4.0}
topks1 := []int64{int64(len(ids1))}
ids2 := []int64{5, 1, 3, 4}
scores2 := []float32{-1.0, -1.0, -3.0, -4.0}
topks2 := []int64{int64(len(ids2))}
data1 := genSearchResultData(nq, topk, ids1, scores1, topks1)
data2 := genSearchResultData(nq, topk, ids2, scores2, topks2)
data1.GroupByFieldValue = &schemapb.FieldData{
Type: schemapb.DataType_Int8,
Field: &schemapb.FieldData_Scalars{
Scalars: &schemapb.ScalarField{
Data: &schemapb.ScalarField_IntData{
IntData: &schemapb.IntArray{
Data: []int32{2, 3, 4, 5},
},
},
},
},
}
data2.GroupByFieldValue = &schemapb.FieldData{
Type: schemapb.DataType_Int8,
Field: &schemapb.FieldData_Scalars{
Scalars: &schemapb.ScalarField{
Data: &schemapb.ScalarField_IntData{
IntData: &schemapb.IntArray{
Data: []int32{2, 3, 4, 5},
},
},
},
},
}
dataArray := make([]*schemapb.SearchResultData, 0)
dataArray = append(dataArray, data1)
dataArray = append(dataArray, data2)
reduceInfo := &ReduceInfo{nq: nq, topK: topk, groupByFieldID: 101}
searchReduce := InitSearchReducer(reduceInfo)
res, err := searchReduce.ReduceSearchResultData(context.TODO(), dataArray, reduceInfo)
suite.Nil(err)
suite.ElementsMatch([]int64{1, 2, 3, 4}, res.Ids.GetIntId().Data)
suite.ElementsMatch([]float32{-1.0, -2.0, -3.0, -4.0}, res.Scores)
suite.ElementsMatch([]int32{2, 3, 4, 5}, res.GroupByFieldValue.GetScalars().GetIntData().Data)
})
suite.Run("reduce_group_by_bool", func() {
ids1 := []int64{1, 2}
scores1 := []float32{-1.0, -2.0}
topks1 := []int64{int64(len(ids1))}
ids2 := []int64{3, 4}
scores2 := []float32{-1.0, -1.0}
topks2 := []int64{int64(len(ids2))}
data1 := genSearchResultData(nq, topk, ids1, scores1, topks1)
data2 := genSearchResultData(nq, topk, ids2, scores2, topks2)
data1.GroupByFieldValue = &schemapb.FieldData{
Type: schemapb.DataType_Bool,
Field: &schemapb.FieldData_Scalars{
Scalars: &schemapb.ScalarField{
Data: &schemapb.ScalarField_BoolData{
BoolData: &schemapb.BoolArray{
Data: []bool{true, false},
},
},
},
},
}
data2.GroupByFieldValue = &schemapb.FieldData{
Type: schemapb.DataType_Bool,
Field: &schemapb.FieldData_Scalars{
Scalars: &schemapb.ScalarField{
Data: &schemapb.ScalarField_BoolData{
BoolData: &schemapb.BoolArray{
Data: []bool{true, false},
},
},
},
},
}
dataArray := make([]*schemapb.SearchResultData, 0)
dataArray = append(dataArray, data1)
dataArray = append(dataArray, data2)
reduceInfo := &ReduceInfo{nq: nq, topK: topk, groupByFieldID: 101}
searchReduce := InitSearchReducer(reduceInfo)
res, err := searchReduce.ReduceSearchResultData(context.TODO(), dataArray, reduceInfo)
suite.Nil(err)
suite.ElementsMatch([]int64{1, 4}, res.Ids.GetIntId().Data)
suite.ElementsMatch([]float32{-1.0, -1.0}, res.Scores)
suite.ElementsMatch([]bool{true, false}, res.GroupByFieldValue.GetScalars().GetBoolData().Data)
})
suite.Run("reduce_group_by_string", func() {
ids1 := []int64{1, 2, 3, 4}
scores1 := []float32{-1.0, -2.0, -3.0, -4.0}
topks1 := []int64{int64(len(ids1))}
ids2 := []int64{5, 1, 3, 4}
scores2 := []float32{-1.0, -1.0, -3.0, -4.0}
topks2 := []int64{int64(len(ids2))}
data1 := genSearchResultData(nq, topk, ids1, scores1, topks1)
data2 := genSearchResultData(nq, topk, ids2, scores2, topks2)
data1.GroupByFieldValue = &schemapb.FieldData{
Type: schemapb.DataType_VarChar,
Field: &schemapb.FieldData_Scalars{
Scalars: &schemapb.ScalarField{
Data: &schemapb.ScalarField_StringData{
StringData: &schemapb.StringArray{
Data: []string{"1", "2", "3", "4"},
},
},
},
},
}
data2.GroupByFieldValue = &schemapb.FieldData{
Type: schemapb.DataType_VarChar,
Field: &schemapb.FieldData_Scalars{
Scalars: &schemapb.ScalarField{
Data: &schemapb.ScalarField_StringData{
StringData: &schemapb.StringArray{
Data: []string{"1", "2", "3", "4"},
},
},
},
},
}
dataArray := make([]*schemapb.SearchResultData, 0)
dataArray = append(dataArray, data1)
dataArray = append(dataArray, data2)
reduceInfo := &ReduceInfo{nq: nq, topK: topk, groupByFieldID: 101}
searchReduce := InitSearchReducer(reduceInfo)
res, err := searchReduce.ReduceSearchResultData(context.TODO(), dataArray, reduceInfo)
suite.Nil(err)
suite.ElementsMatch([]int64{1, 2, 3, 4}, res.Ids.GetIntId().Data)
suite.ElementsMatch([]float32{-1.0, -2.0, -3.0, -4.0}, res.Scores)
suite.ElementsMatch([]string{"1", "2", "3", "4"}, res.GroupByFieldValue.GetScalars().GetStringData().Data)
})
suite.Run("reduce_group_by_string_with_group_size", func() {
ids1 := []int64{1, 2, 3, 4}
scores1 := []float32{-1.0, -2.0, -3.0, -4.0}
topks1 := []int64{int64(len(ids1))}
ids2 := []int64{4, 5, 6, 7}
scores2 := []float32{-1.0, -1.0, -3.0, -4.0}
topks2 := []int64{int64(len(ids2))}
data1 := genSearchResultData(nq, topk, ids1, scores1, topks1)
data2 := genSearchResultData(nq, topk, ids2, scores2, topks2)
data1.GroupByFieldValue = &schemapb.FieldData{
Type: schemapb.DataType_VarChar,
Field: &schemapb.FieldData_Scalars{
Scalars: &schemapb.ScalarField{
Data: &schemapb.ScalarField_StringData{
StringData: &schemapb.StringArray{
Data: []string{"1", "2", "3", "4"},
},
},
},
},
}
data2.GroupByFieldValue = &schemapb.FieldData{
Type: schemapb.DataType_VarChar,
Field: &schemapb.FieldData_Scalars{
Scalars: &schemapb.ScalarField{
Data: &schemapb.ScalarField_StringData{
StringData: &schemapb.StringArray{
Data: []string{"1", "2", "3", "4"},
},
},
},
},
}
dataArray := make([]*schemapb.SearchResultData, 0)
dataArray = append(dataArray, data1)
dataArray = append(dataArray, data2)
reduceInfo := &ReduceInfo{nq: nq, topK: topk, groupByFieldID: 101, groupSize: 3}
searchReduce := InitSearchReducer(reduceInfo)
res, err := searchReduce.ReduceSearchResultData(context.TODO(), dataArray, reduceInfo)
suite.Nil(err)
suite.ElementsMatch([]int64{1, 4, 2, 5, 3, 6, 7}, res.Ids.GetIntId().Data)
suite.ElementsMatch([]float32{-1.0, -1.0, -1.0, -2.0, -3.0, -3.0, -4.0}, res.Scores)
suite.ElementsMatch([]string{"1", "1", "2", "2", "3", "3", "4"}, res.GroupByFieldValue.GetScalars().GetStringData().Data)
})
suite.Run("reduce_group_by_empty_input", func() {
dataArray := make([]*schemapb.SearchResultData, 0)
reduceInfo := &ReduceInfo{nq: nq, topK: topk, groupByFieldID: 101, groupSize: 3}
searchReduce := InitSearchReducer(reduceInfo)
res, err := searchReduce.ReduceSearchResultData(context.TODO(), dataArray, reduceInfo)
suite.Nil(err)
suite.Nil(res.GetIds().GetIdField())
suite.Equal(0, len(res.GetTopks()))
suite.Equal(0, len(res.GetScores()))
suite.Equal(int64(nq), res.GetNumQueries())
suite.Equal(int64(topk), res.GetTopK())
suite.Equal(0, len(res.GetFieldsData()))
})
}
func TestSearchReduce(t *testing.T) {
paramtable.Init()
suite.Run(t, new(SearchReduceSuite))
}

6
internal/querynodev2/services.go
View File

@ -790,7 +790,11 @@ func (node *QueryNode) Search(ctx context.Context, req *querypb.SearchRequest) (
if req.GetReq().GetIsAdvanced() {
result, err2 = segments.ReduceAdvancedSearchResults(ctx, toReduceResults, req.Req.GetNq())
} else {
result, err2 = segments.ReduceSearchResults(ctx, toReduceResults, req.Req.GetNq(), req.Req.GetTopk(), req.Req.GetMetricType())
result, err2 = segments.ReduceSearchResults(ctx, toReduceResults, segments.NewReduceInfo(req.Req.GetNq(),
req.Req.GetTopk(),
req.Req.GetExtraSearchParam().GetGroupByFieldId(),
req.Req.GetExtraSearchParam().GetGroupSize(),
req.Req.GetMetricType()))
}
if err2 != nil {