Files
wehub-resource-sync 498b235461
Build and test / Build and test AMD64 Ubuntu 22.04 (push) Failing after 0s
Publish Builder / amazonlinux2023 (push) Failing after 1s
Build and test / UT for Go (push) Has been skipped
Publish KRTE Images / KRTE (push) Failing after 1s
Build and test / Integration Test (push) Has been skipped
Build and test / Upload Code Coverage (push) Has been skipped
Publish Builder / rockylinux9 (push) Failing after 1s
Publish Builder / ubuntu22.04 (push) Failing after 0s
Publish Builder / ubuntu24.04 (push) Failing after 0s
Publish Gpu Builder / publish-gpu-builder (push) Failing after 1s
Publish Test Images / PyTest (push) Failing after 0s
Build and test / UT for Cpp (push) Has been cancelled
chore: import upstream snapshot with attribution
2026-07-13 12:31:17 +08:00

650 lines
20 KiB
Go

// Licensed to the LF AI & Data foundation under one
// or more contributor license agreements. See the NOTICE file
// distributed with this work for additional information
// regarding copyright ownership. The ASF licenses this file
// to you under the Apache License, Version 2.0 (the
// "License"); you may not use this file except in compliance
// with the License. You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
package compactor
import (
"github.com/apache/arrow/go/v17/arrow"
"github.com/apache/arrow/go/v17/arrow/array"
"github.com/apache/arrow/go/v17/arrow/memory"
"github.com/milvus-io/milvus-proto/go-api/v3/schemapb"
"github.com/milvus-io/milvus/internal/storage"
"github.com/milvus-io/milvus/internal/util/function"
"github.com/milvus-io/milvus/pkg/v3/common"
"github.com/milvus-io/milvus/pkg/v3/util/merr"
"github.com/milvus-io/milvus/pkg/v3/util/typeutil"
)
type FunctionMaterializer interface {
Materialize(rec storage.Record) (map[int64]arrow.Array, error)
Close()
}
type rowRange struct {
start int
end int
}
type recordSelection struct {
ranges []rowRange
length int
}
func (s *recordSelection) Len() int {
if s == nil {
return 0
}
return s.length
}
type RecordMaterializer struct {
materializers []FunctionMaterializer
missingFields []*schemapb.FieldSchema
schema *schemapb.CollectionSchema
}
func NewRecordMaterializer(schema *schemapb.CollectionSchema, functions []*schemapb.FunctionSchema, existingFields map[int64]struct{}) (*RecordMaterializer, error) {
materializer := &RecordMaterializer{schema: schema}
materializedFields := make(map[int64]struct{})
for _, functionSchema := range functions {
outputIndexes := functionOutputIndexesToMaterialize(functionSchema, existingFields)
if len(outputIndexes) == 0 {
continue
}
for _, outputIndex := range outputIndexes {
materializedFields[functionSchema.GetOutputFieldIds()[outputIndex]] = struct{}{}
}
runner, err := function.NewFunctionRunner(schema, functionSchema)
if err != nil {
materializer.Close()
return nil, err
}
if runner == nil {
materializer.Close()
return nil, merr.WrapErrFunctionFailedMsg("failed to set up function runner for %s", functionSchema.GetName())
}
functionMaterializer, err := newFunctionMaterializer(schema, runner, outputIndexes, true)
if err != nil {
runner.Close()
materializer.Close()
return nil, err
}
materializer.materializers = append(materializer.materializers, functionMaterializer)
}
materializer.missingFields = missingNonMaterializedSchemaFields(schema, existingFields, materializedFields)
return materializer, nil
}
func (m *RecordMaterializer) Wrap(rec storage.Record) (storage.Record, error) {
return m.WrapWithSelection(rec, nil)
}
func (m *RecordMaterializer) WrapWithSelection(rec storage.Record, selection *recordSelection) (storage.Record, error) {
base := rec
var selected *selectedRecord
if selection != nil {
selected = newSelectedRecord(rec, m.schema, selection)
base = selected
}
if !m.hasMaterialization() {
return base, nil
}
computed := make(map[int64]arrow.Array)
for _, materializer := range m.materializers {
arrays, err := materializer.Materialize(base)
if err != nil {
releaseArrowArrays(computed)
if base != rec {
base.Release()
}
if selected != nil && selected.err != nil {
return nil, selected.err
}
return nil, err
}
if selected != nil && selected.err != nil {
releaseArrowArrays(computed)
base.Release()
return nil, selected.err
}
for fieldID, arr := range arrays {
computed[fieldID] = arr
}
}
for _, field := range m.missingFields {
fieldID := field.GetFieldID()
if _, ok := computed[fieldID]; ok {
continue
}
arr, err := storage.GenerateEmptyArrayFromSchema(field, base.Len())
if err != nil {
releaseArrowArrays(computed)
if base != rec {
base.Release()
}
return nil, err
}
computed[fieldID] = arr
}
if len(computed) == 0 {
return base, nil
}
return &materializedRecord{base: base, computed: computed}, nil
}
func (m *RecordMaterializer) Close() {
if m == nil {
return
}
for _, materializer := range m.materializers {
materializer.Close()
}
}
func (m *RecordMaterializer) hasMaterialization() bool {
return m != nil && (len(m.materializers) > 0 || len(m.missingFields) > 0)
}
type materializedRecord struct {
base storage.Record
computed map[int64]arrow.Array
}
var _ storage.Record = (*materializedRecord)(nil)
func (r *materializedRecord) Column(fieldID storage.FieldID) arrow.Array {
if col, ok := r.computed[fieldID]; ok {
return col
}
return r.base.Column(fieldID)
}
func (r *materializedRecord) Len() int {
return r.base.Len()
}
func (r *materializedRecord) Retain() {
r.base.Retain()
for _, col := range r.computed {
col.Retain()
}
}
func (r *materializedRecord) retainBase() {
r.base.Retain()
}
func (r *materializedRecord) Release() {
r.base.Release()
for _, col := range r.computed {
col.Release()
}
}
type selectedRecord struct {
base storage.Record
fields map[int64]*schemapb.FieldSchema
selection *recordSelection
columns map[int64]arrow.Array
err error
}
var _ storage.Record = (*selectedRecord)(nil)
func newSelectedRecord(base storage.Record, schema *schemapb.CollectionSchema, selection *recordSelection) *selectedRecord {
fields := make(map[int64]*schemapb.FieldSchema)
for _, field := range typeutil.GetAllFieldSchemas(schema) {
fields[field.GetFieldID()] = field
}
return &selectedRecord{
base: base,
fields: fields,
selection: selection,
columns: make(map[int64]arrow.Array),
}
}
func (r *selectedRecord) Column(fieldID storage.FieldID) arrow.Array {
if col, ok := r.columns[fieldID]; ok {
return col
}
field := r.fields[fieldID]
if field == nil {
return nil
}
builder := storage.NewRecordBuilder(&schemapb.CollectionSchema{Fields: []*schemapb.FieldSchema{field}})
defer builder.Release()
for _, rowRange := range r.selection.ranges {
if err := builder.Append(r.base, rowRange.start, rowRange.end); err != nil {
r.err = err
return nil
}
}
selected := builder.Build()
defer selected.Release()
col := selected.Column(fieldID)
if col == nil {
r.err = merr.WrapErrServiceInternalMsg("selected record field %d not found", fieldID)
return nil
}
col.Retain()
r.columns[fieldID] = col
return col
}
func (r *selectedRecord) Len() int {
return r.selection.Len()
}
func (r *selectedRecord) Retain() {
r.base.Retain()
for _, col := range r.columns {
col.Retain()
}
}
func (r *selectedRecord) Release() {
r.base.Release()
for _, col := range r.columns {
col.Release()
}
}
type materializedRecordReader struct {
base storage.RecordReader
materializer *RecordMaterializer
current storage.Record
}
var _ storage.RecordReader = (*materializedRecordReader)(nil)
func newMaterializedRecordReader(base storage.RecordReader, materializer *RecordMaterializer) storage.RecordReader {
if !materializer.hasMaterialization() {
return base
}
return &materializedRecordReader{base: base, materializer: materializer}
}
func (r *materializedRecordReader) Next() (storage.Record, error) {
if r.current != nil {
r.current.Release()
r.current = nil
}
rec, err := r.base.Next()
if err != nil {
return nil, err
}
wrapped, err := r.materializer.Wrap(rec)
if err != nil {
rec.Release()
return nil, err
}
if materialized, ok := wrapped.(*materializedRecord); ok {
materialized.retainBase()
} else {
wrapped.Retain()
}
r.current = wrapped
return wrapped, nil
}
func (r *materializedRecordReader) Close() error {
if r.current != nil {
r.current.Release()
r.current = nil
}
r.materializer.Close()
return r.base.Close()
}
type bm25FunctionMaterializer struct {
runner function.FunctionRunner
inputFieldIDs []int64
outputFieldIDs []int64
missingOutputIndexes []int
outputFields map[int64]*schemapb.FieldSchema
ownRunner bool
}
type minHashFunctionMaterializer struct {
runner function.FunctionRunner
inputFieldIDs []int64
outputFieldIDs []int64
missingOutputIndexes []int
outputFields map[int64]*schemapb.FieldSchema
ownRunner bool
}
var (
_ FunctionMaterializer = (*bm25FunctionMaterializer)(nil)
_ FunctionMaterializer = (*minHashFunctionMaterializer)(nil)
)
func newFunctionMaterializer(schema *schemapb.CollectionSchema, runner function.FunctionRunner, missingOutputIndexes []int, ownRunner bool) (FunctionMaterializer, error) {
functionSchema := runner.GetSchema()
switch functionSchema.GetType() {
case schemapb.FunctionType_BM25:
return newBM25FunctionMaterializer(schema, runner, missingOutputIndexes, ownRunner)
case schemapb.FunctionType_MinHash:
return newMinHashFunctionMaterializer(schema, runner, missingOutputIndexes, ownRunner)
default:
return nil, merr.WrapErrParameterInvalidMsg("unsupported function type %s", functionSchema.GetType().String())
}
}
func newMinHashFunctionMaterializer(schema *schemapb.CollectionSchema, runner function.FunctionRunner, missingOutputIndexes []int, ownRunner bool) (*minHashFunctionMaterializer, error) {
functionSchema := runner.GetSchema()
inputFields := runner.GetInputFields()
if len(inputFields) == 0 {
return nil, merr.WrapErrFunctionFailedMsg("minhash function should have input fields")
}
inputFieldIDs := make([]int64, 0, len(inputFields))
for _, inputField := range inputFields {
if inputField == nil || typeutil.GetField(schema, inputField.GetFieldID()) == nil {
return nil, merr.WrapErrFunctionFailedMsg("input field not found in schema")
}
if inputField.GetDataType() != schemapb.DataType_VarChar && inputField.GetDataType() != schemapb.DataType_Text {
return nil, merr.WrapErrFunctionFailedMsg("input field data type must be varchar or text for minhash function materialization")
}
inputFieldIDs = append(inputFieldIDs, inputField.GetFieldID())
}
outputFieldIDs := functionSchema.GetOutputFieldIds()
if len(outputFieldIDs) == 0 {
return nil, merr.WrapErrFunctionFailedMsg("minhash function should have output fields")
}
outputFields := make(map[int64]*schemapb.FieldSchema, len(outputFieldIDs))
for _, outputFieldID := range outputFieldIDs {
outputField := typeutil.GetField(schema, outputFieldID)
if outputField == nil {
return nil, merr.WrapErrFunctionFailedMsg("output field not found in schema")
}
if outputField.GetDataType() != schemapb.DataType_BinaryVector {
return nil, merr.WrapErrFunctionFailedMsg("output field data type must be binary vector for minhash function materialization")
}
if outputField.GetNullable() {
return nil, merr.WrapErrFunctionFailedMsg("function output field cannot be nullable: function %s, field %s", functionSchema.GetName(), outputField.GetName())
}
outputFields[outputFieldID] = outputField
}
return &minHashFunctionMaterializer{
runner: runner,
inputFieldIDs: inputFieldIDs,
outputFieldIDs: outputFieldIDs,
missingOutputIndexes: missingOutputIndexes,
outputFields: outputFields,
ownRunner: ownRunner,
}, nil
}
func newBM25FunctionMaterializer(schema *schemapb.CollectionSchema, runner function.FunctionRunner, missingOutputIndexes []int, ownRunner bool) (*bm25FunctionMaterializer, error) {
functionSchema := runner.GetSchema()
inputFields := runner.GetInputFields()
if len(inputFields) == 0 {
return nil, merr.WrapErrParameterInvalidMsg("bm25 function should have input fields")
}
inputFieldIDs := make([]int64, 0, len(inputFields))
for _, inputField := range inputFields {
if inputField == nil || typeutil.GetField(schema, inputField.GetFieldID()) == nil {
return nil, merr.WrapErrParameterInvalidMsg("input field not found in schema")
}
if inputField.GetDataType() != schemapb.DataType_VarChar && inputField.GetDataType() != schemapb.DataType_Text {
return nil, merr.WrapErrParameterInvalidMsg("input field data type must be varchar or text for bm25 function materialization")
}
inputFieldIDs = append(inputFieldIDs, inputField.GetFieldID())
}
outputFieldIDs := functionSchema.GetOutputFieldIds()
if len(outputFieldIDs) == 0 {
return nil, merr.WrapErrParameterInvalidMsg("bm25 function should have output fields")
}
outputFields := make(map[int64]*schemapb.FieldSchema, len(outputFieldIDs))
for _, outputFieldID := range outputFieldIDs {
outputField := typeutil.GetField(schema, outputFieldID)
if outputField == nil {
return nil, merr.WrapErrParameterInvalidMsg("output field not found in schema")
}
if outputField.GetDataType() != schemapb.DataType_SparseFloatVector {
return nil, merr.WrapErrParameterInvalidMsg("output field data type must be sparse float vector for bm25 function materialization")
}
if outputField.GetNullable() {
return nil, merr.WrapErrParameterInvalidMsg("function output field cannot be nullable: function %s, field %s", functionSchema.GetName(), outputField.GetName())
}
outputFields[outputFieldID] = outputField
}
return &bm25FunctionMaterializer{
runner: runner,
inputFieldIDs: inputFieldIDs,
outputFieldIDs: outputFieldIDs,
missingOutputIndexes: missingOutputIndexes,
outputFields: outputFields,
ownRunner: ownRunner,
}, nil
}
func (m *bm25FunctionMaterializer) Materialize(rec storage.Record) (map[int64]arrow.Array, error) {
inputs := make([]any, 0, len(m.inputFieldIDs))
for _, inputFieldID := range m.inputFieldIDs {
input, err := stringInputsFromRecord(rec, inputFieldID)
if err != nil {
return nil, err
}
inputs = append(inputs, input)
}
outputs, err := m.runner.BatchRun(inputs...)
if err != nil {
return nil, err
}
if len(outputs) != len(m.outputFieldIDs) {
return nil, merr.WrapErrFunctionFailedMsg("bm25 function materialization expects %d outputs, got %d", len(m.outputFieldIDs), len(outputs))
}
result := make(map[int64]arrow.Array, len(m.missingOutputIndexes))
for _, outputIndex := range m.missingOutputIndexes {
outputFieldID := m.outputFieldIDs[outputIndex]
outputSparseArray, ok := outputs[outputIndex].(*schemapb.SparseFloatArray)
if !ok {
releaseArrowArrays(result)
return nil, merr.WrapErrFunctionFailedMsg("unexpected output type from BM25 function runner, expected SparseFloatArray, got %T", outputs[outputIndex])
}
arr, err := buildSparseFloatVectorArrowArray(m.outputFields[outputFieldID], outputSparseArray, rec.Len())
if err != nil {
releaseArrowArrays(result)
return nil, err
}
result[outputFieldID] = arr
}
return result, nil
}
func (m *bm25FunctionMaterializer) Close() {
if m.ownRunner && m.runner != nil {
m.runner.Close()
}
}
func (m *minHashFunctionMaterializer) Materialize(rec storage.Record) (map[int64]arrow.Array, error) {
inputs := make([]any, 0, len(m.inputFieldIDs))
for _, inputFieldID := range m.inputFieldIDs {
input, err := stringInputsFromRecord(rec, inputFieldID)
if err != nil {
return nil, err
}
inputs = append(inputs, input)
}
outputs, err := m.runner.BatchRun(inputs...)
if err != nil {
return nil, err
}
if len(outputs) != len(m.outputFieldIDs) {
return nil, merr.WrapErrFunctionFailedMsg("minhash function materialization expects %d outputs, got %d", len(m.outputFieldIDs), len(outputs))
}
result := make(map[int64]arrow.Array, len(m.missingOutputIndexes))
for _, outputIndex := range m.missingOutputIndexes {
outputFieldID := m.outputFieldIDs[outputIndex]
outputFieldData, ok := outputs[outputIndex].(*schemapb.FieldData)
if !ok {
releaseArrowArrays(result)
return nil, merr.WrapErrFunctionFailedMsg("unexpected output type from MinHash function runner, expected FieldData, got %T", outputs[outputIndex])
}
vectorField := outputFieldData.GetVectors()
if vectorField == nil || vectorField.GetBinaryVector() == nil {
releaseArrowArrays(result)
return nil, merr.WrapErrFunctionFailedMsg("unexpected output from MinHash function runner, expected binary vector field data")
}
fieldData := &storage.BinaryVectorFieldData{
Data: vectorField.GetBinaryVector(),
Dim: int(vectorField.GetDim()),
}
if fieldData.RowNum() != rec.Len() {
releaseArrowArrays(result)
return nil, merr.WrapErrFunctionFailedMsg("minhash function output row count mismatch, expected %d, got %d", rec.Len(), fieldData.RowNum())
}
arr, err := buildArrowArrayFromFieldData(m.outputFields[outputFieldID], fieldData, rec.Len())
if err != nil {
releaseArrowArrays(result)
return nil, err
}
result[outputFieldID] = arr
}
return result, nil
}
func (m *minHashFunctionMaterializer) Close() {
if m.ownRunner && m.runner != nil {
m.runner.Close()
}
}
func functionOutputIndexesToMaterialize(functionSchema *schemapb.FunctionSchema, existingFields map[int64]struct{}) []int {
outputFieldIDs := functionSchema.GetOutputFieldIds()
indexes := make([]int, 0, len(outputFieldIDs))
hasMissingOutput := false
for idx, outputFieldID := range outputFieldIDs {
indexes = append(indexes, idx)
if _, ok := existingFields[outputFieldID]; !ok {
hasMissingOutput = true
}
}
if !hasMissingOutput {
return nil
}
return indexes
}
func missingNonMaterializedSchemaFields(schema *schemapb.CollectionSchema, existingFields map[int64]struct{}, materializedFields map[int64]struct{}) []*schemapb.FieldSchema {
missing := make([]*schemapb.FieldSchema, 0)
for _, field := range typeutil.GetAllFieldSchemas(schema) {
fieldID := field.GetFieldID()
if common.IsSystemField(fieldID) {
continue
}
if _, ok := existingFields[fieldID]; ok {
continue
}
if _, ok := materializedFields[fieldID]; ok {
continue
}
missing = append(missing, field)
}
return missing
}
func stringInputsFromRecord(rec storage.Record, fieldID int64) ([]string, error) {
col := rec.Column(fieldID)
if col == nil {
return nil, merr.WrapErrFunctionFailedMsg("input field %d not found in record", fieldID)
}
inputs := make([]string, rec.Len())
switch values := col.(type) {
case *array.String:
for i := 0; i < rec.Len(); i++ {
if values.IsValid(i) {
inputs[i] = values.Value(i)
}
}
case *array.Binary:
return nil, merr.WrapErrFunctionFailedMsg("cannot materialize bm25 from text binary values without lob decoding")
default:
return nil, merr.WrapErrFunctionFailedMsg("input field %d data type must be varchar or text for bm25 function materialization, got %T", fieldID, col)
}
return inputs, nil
}
func buildSparseFloatVectorArrowArray(field *schemapb.FieldSchema, outputSparseArray *schemapb.SparseFloatArray, rowCount int) (arrow.Array, error) {
if len(outputSparseArray.GetContents()) != rowCount {
return nil, merr.WrapErrFunctionFailedMsg("bm25 function output row count mismatch, expected %d, got %d", rowCount, len(outputSparseArray.GetContents()))
}
fieldData := &storage.SparseFloatVectorFieldData{
SparseFloatArray: schemapb.SparseFloatArray{
Contents: outputSparseArray.GetContents(),
Dim: outputSparseArray.GetDim(),
},
}
return buildArrowArrayFromFieldData(field, fieldData, rowCount)
}
func buildArrowArrayFromFieldData(field *schemapb.FieldSchema, fieldData storage.FieldData, rowCount int) (arrow.Array, error) {
if fieldData.RowNum() != rowCount {
return nil, merr.WrapErrFunctionFailedMsg("function output row count mismatch for field %d, expected %d, got %d", field.GetFieldID(), rowCount, fieldData.RowNum())
}
outputSchema := &schemapb.CollectionSchema{Fields: []*schemapb.FieldSchema{field}}
arrowSchema, err := storage.ConvertToArrowSchema(outputSchema, true)
if err != nil {
return nil, err
}
builder := array.NewRecordBuilder(memory.DefaultAllocator, arrowSchema)
defer builder.Release()
insertData := &storage.InsertData{Data: map[int64]storage.FieldData{
field.GetFieldID(): fieldData,
}}
if err := storage.BuildRecord(builder, insertData, outputSchema); err != nil {
return nil, err
}
record := builder.NewRecord()
defer record.Release()
col := record.Column(0)
col.Retain()
return col, nil
}
func releaseArrowArrays(arrays map[int64]arrow.Array) {
for _, arr := range arrays {
arr.Release()
}
}
func releaseWrappedRecord(wrapped storage.Record, base storage.Record) {
if wrapped != base {
wrapped.Release()
return
}
base.Release()
}