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issue: https://github.com/milvus-io/milvus/issues/42148 For a vector field inside a STRUCT, since a STRUCT can only appear as the element type of an ARRAY field, the vector field in STRUCT is effectively an array of vectors, i.e. an embedding list. Milvus already supports searching embedding lists with metrics whose names start with the prefix MAX_SIM_. This PR allows Milvus to search embeddings inside an embedding list using the same metrics as normal embedding fields. Each embedding in the list is treated as an independent vector and participates in ANN search. Further, since STRUCT may contain scalar fields that are highly related to the embedding field, this PR introduces an element-level filter expression to refine search results. The grammar of the element-level filter is: element_filter(structFieldName, $[subFieldName] == 3) where $[subFieldName] refers to the value of subFieldName in each element of the STRUCT array structFieldName. It can be combined with existing filter expressions, for example: "varcharField == 'aaa' && element_filter(struct_field, $[struct_int] == 3)" A full example: ``` struct_schema = milvus_client.create_struct_field_schema() struct_schema.add_field("struct_str", DataType.VARCHAR, max_length=65535) struct_schema.add_field("struct_int", DataType.INT32) struct_schema.add_field("struct_float_vec", DataType.FLOAT_VECTOR, dim=EMBEDDING_DIM) schema.add_field( "struct_field", datatype=DataType.ARRAY, element_type=DataType.STRUCT, struct_schema=struct_schema, max_capacity=1000, ) ... filter = "varcharField == 'aaa' && element_filter(struct_field, $[struct_int] == 3 && $[struct_str] == 'abc')" res = milvus_client.search( COLLECTION_NAME, data=query_embeddings, limit=10, anns_field="struct_field[struct_float_vec]", filter=filter, output_fields=["struct_field[struct_int]", "varcharField"], ) ``` TODO: 1. When an `element_filter` expression is used, a regular filter expression must also be present. Remove this restriction. 2. Implement `element_filter` expressions in the `query`. --------- Signed-off-by: SpadeA <tangchenjie1210@gmail.com>
145 lines
5.3 KiB
Go
145 lines
5.3 KiB
Go
package indexparamcheck
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/*
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#cgo pkg-config: milvus_core
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#include <stdlib.h> // free
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#include "segcore/vector_index_c.h"
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*/
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import "C"
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import (
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"fmt"
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"math"
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"unsafe"
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"github.com/cockroachdb/errors"
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"google.golang.org/protobuf/proto"
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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/schemapb"
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"github.com/milvus-io/milvus/internal/util/vecindexmgr"
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"github.com/milvus-io/milvus/pkg/v2/common"
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"github.com/milvus-io/milvus/pkg/v2/proto/indexcgopb"
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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 vecIndexChecker struct {
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baseChecker
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}
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// HandleCStatus deals with the error returned from CGO
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func HandleCStatus(status *C.CStatus) error {
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if status.error_code == 0 {
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return nil
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}
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errorMsg := C.GoString(status.error_msg)
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defer C.free(unsafe.Pointer(status.error_msg))
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return fmt.Errorf("%s", errorMsg)
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}
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func (c vecIndexChecker) StaticCheck(dataType schemapb.DataType, elementType schemapb.DataType, params map[string]string) error {
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if typeutil.IsDenseFloatVectorType(dataType) {
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if !CheckStrByValues(params, Metric, FloatVectorMetrics) {
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return fmt.Errorf("metric type %s not found or not supported, supported: %v", params[Metric], FloatVectorMetrics)
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}
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} else if typeutil.IsSparseFloatVectorType(dataType) {
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if !CheckStrByValues(params, Metric, SparseMetrics) {
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return fmt.Errorf("metric type not found or not supported, supported: %v", SparseMetrics)
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}
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} else if typeutil.IsBinaryVectorType(dataType) {
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if !CheckStrByValues(params, Metric, BinaryVectorMetrics) {
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return fmt.Errorf("metric type %s not found or not supported, supported: %v", params[Metric], BinaryVectorMetrics)
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}
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} else if typeutil.IsIntVectorType(dataType) {
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if !CheckStrByValues(params, Metric, IntVectorMetrics) {
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return fmt.Errorf("metric type %s not found or not supported, supported: %v", params[Metric], IntVectorMetrics)
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}
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} else if typeutil.IsArrayOfVectorType(dataType) {
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if !CheckStrByValues(params, Metric, EmbListMetrics) {
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if typeutil.IsDenseFloatVectorType(elementType) {
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if !CheckStrByValues(params, Metric, FloatVectorMetrics) {
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return fmt.Errorf("metric type %s not found or not supported for array of vector with float element type, supported: %v", params[Metric], FloatVectorMetrics)
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}
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} else if typeutil.IsBinaryVectorType(elementType) {
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if !CheckStrByValues(params, Metric, BinaryVectorMetrics) {
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return fmt.Errorf("metric type %s not found or not supported for array of vector with binary element type, supported: %v", params[Metric], BinaryVectorMetrics)
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}
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} else if typeutil.IsIntVectorType(elementType) {
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if !CheckStrByValues(params, Metric, IntVectorMetrics) {
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return fmt.Errorf("metric type %s not found or not supported for array of vector with int element type, supported: %v", params[Metric], IntVectorMetrics)
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}
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} else {
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return fmt.Errorf("metric type %s not found or not supported for array of vector, supported: %v", params[Metric], EmbListMetrics)
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}
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}
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}
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indexType, exist := params[common.IndexTypeKey]
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if !exist {
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return errors.New("no indexType is specified")
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}
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if !vecindexmgr.GetVecIndexMgrInstance().IsVecIndex(indexType) {
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return fmt.Errorf("indexType %s is not supported", indexType)
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}
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protoIndexParams := &indexcgopb.IndexParams{
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Params: make([]*commonpb.KeyValuePair, 0),
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}
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for key, value := range params {
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protoIndexParams.Params = append(protoIndexParams.Params, &commonpb.KeyValuePair{Key: key, Value: value})
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}
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indexParamsBlob, err := proto.Marshal(protoIndexParams)
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if err != nil {
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return fmt.Errorf("failed to marshal index params: %s", err)
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}
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var status C.CStatus
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cIndexType := C.CString(indexType)
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cDataType := uint32(dataType)
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cElementType := uint32(elementType)
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status = C.ValidateIndexParams(cIndexType, cDataType, cElementType, (*C.uint8_t)(unsafe.Pointer(&indexParamsBlob[0])), (C.uint64_t)(len(indexParamsBlob)))
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C.free(unsafe.Pointer(cIndexType))
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return HandleCStatus(&status)
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}
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func (c vecIndexChecker) CheckTrain(dataType schemapb.DataType, elementType schemapb.DataType, params map[string]string) error {
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if err := c.StaticCheck(dataType, elementType, params); err != nil {
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return err
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}
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if typeutil.IsFixDimVectorType(dataType) || (typeutil.IsArrayOfVectorType(dataType) && typeutil.IsFixDimVectorType(elementType)) {
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if !CheckIntByRange(params, DIM, 1, math.MaxInt) {
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return errors.New("failed to check vector dimension, should be larger than 0 and smaller than math.MaxInt")
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}
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}
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return c.baseChecker.CheckTrain(dataType, elementType, params)
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}
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func (c vecIndexChecker) CheckValidDataType(indexType IndexType, field *schemapb.FieldSchema) error {
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if !typeutil.IsVectorType(field.GetDataType()) {
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return fmt.Errorf("index %s only supports vector data type", indexType)
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}
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if !vecindexmgr.GetVecIndexMgrInstance().IsDataTypeSupport(indexType, field.GetDataType(), field.GetElementType()) {
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return fmt.Errorf("index %s do not support data type: %s", indexType, schemapb.DataType_name[int32(field.GetDataType())])
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}
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return nil
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}
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func (c vecIndexChecker) SetDefaultMetricTypeIfNotExist(dType schemapb.DataType, params map[string]string) {
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paramtable.SetDefaultMetricTypeIfNotExist(dType, params)
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}
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func newVecIndexChecker() IndexChecker {
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return &vecIndexChecker{}
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}
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