milvus/internal/storage/data_sorter.go
cai.zhang 19346fa389
feat: Geospatial Data Type and GIS Function support for milvus (#44547)
issue: #43427

This pr's main goal is merge #37417 to milvus 2.5 without conflicts.

# Main Goals

1. Create and describe collections with geospatial type
2. Insert geospatial data into the insert binlog
3. Load segments containing geospatial data into memory
4. Enable query and search can display  geospatial data
5. Support using GIS funtions like ST_EQUALS in query
6. Support R-Tree index for geometry type

# Solution

1. **Add Type**: Modify the Milvus core by adding a Geospatial type in
both the C++ and Go code layers, defining the Geospatial data structure
and the corresponding interfaces.
2. **Dependency Libraries**: Introduce necessary geospatial data
processing libraries. In the C++ source code, use Conan package
management to include the GDAL library. In the Go source code, add the
go-geom library to the go.mod file.
3. **Protocol Interface**: Revise the Milvus protocol to provide
mechanisms for Geospatial message serialization and deserialization.
4. **Data Pipeline**: Facilitate interaction between the client and
proxy using the WKT format for geospatial data. The proxy will convert
all data into WKB format for downstream processing, providing column
data interfaces, segment encapsulation, segment loading, payload
writing, and cache block management.
5. **Query Operators**: Implement simple display and support for filter
queries. Initially, focus on filtering based on spatial relationships
for a single column of geospatial literal values, providing parsing and
execution for query expressions.Now only support brutal search
7. **Client Modification**: Enable the client to handle user input for
geospatial data and facilitate end-to-end testing.Check the modification
in pymilvus.

---------

Signed-off-by: Yinwei Li <yinwei.li@zilliz.com>
Signed-off-by: Cai Zhang <cai.zhang@zilliz.com>
Co-authored-by: ZhuXi <150327960+Yinwei-Yu@users.noreply.github.com>
2025-09-28 19:43:05 +08:00

159 lines
5.4 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 storage
import (
"github.com/milvus-io/milvus-proto/go-api/v2/schemapb"
"github.com/milvus-io/milvus/pkg/v2/common"
"github.com/milvus-io/milvus/pkg/v2/util/typeutil"
)
// DataSorter sorts insert data
type DataSorter struct {
InsertCodec *InsertCodec
InsertData *InsertData
AllFields []*schemapb.FieldSchema
}
// getRowIDFieldData returns auto generated row id Field
func (ds *DataSorter) getRowIDFieldData() FieldData {
if data, ok := ds.InsertData.Data[common.RowIDField]; ok {
return data
}
return nil
}
// Len returns length of the insert data
func (ds *DataSorter) Len() int {
idField := ds.getRowIDFieldData()
if idField == nil {
return 0
}
fieldData, ok := idField.(*Int64FieldData)
if !ok {
return 0
}
return len(fieldData.Data)
}
// Swap swaps each field's i-th and j-th element
func (ds *DataSorter) Swap(i, j int) {
if ds.AllFields == nil {
ds.AllFields = typeutil.GetAllFieldSchemas(ds.InsertCodec.Schema.Schema)
}
for _, field := range ds.AllFields {
singleData, has := ds.InsertData.Data[field.FieldID]
if !has {
continue
}
switch field.DataType {
case schemapb.DataType_Bool:
data := singleData.(*BoolFieldData).Data
data[i], data[j] = data[j], data[i]
case schemapb.DataType_Int8:
data := singleData.(*Int8FieldData).Data
data[i], data[j] = data[j], data[i]
case schemapb.DataType_Int16:
data := singleData.(*Int16FieldData).Data
data[i], data[j] = data[j], data[i]
case schemapb.DataType_Int32:
data := singleData.(*Int32FieldData).Data
data[i], data[j] = data[j], data[i]
case schemapb.DataType_Int64:
data := singleData.(*Int64FieldData).Data
data[i], data[j] = data[j], data[i]
case schemapb.DataType_Float:
data := singleData.(*FloatFieldData).Data
data[i], data[j] = data[j], data[i]
case schemapb.DataType_Double:
data := singleData.(*DoubleFieldData).Data
data[i], data[j] = data[j], data[i]
case schemapb.DataType_Timestamptz:
data := singleData.(*TimestamptzFieldData).Data
data[i], data[j] = data[j], data[i]
case schemapb.DataType_String, schemapb.DataType_VarChar:
data := singleData.(*StringFieldData).Data
data[i], data[j] = data[j], data[i]
case schemapb.DataType_BinaryVector:
data := singleData.(*BinaryVectorFieldData).Data
dim := singleData.(*BinaryVectorFieldData).Dim
// dim for binary vector must be multiplier of 8, simple verion for swapping:
steps := dim / 8
for idx := 0; idx < steps; idx++ {
data[i*steps+idx], data[j*steps+idx] = data[j*steps+idx], data[i*steps+idx]
}
case schemapb.DataType_FloatVector:
data := singleData.(*FloatVectorFieldData).Data
dim := singleData.(*FloatVectorFieldData).Dim
for idx := 0; idx < dim; idx++ {
data[i*dim+idx], data[j*dim+idx] = data[j*dim+idx], data[i*dim+idx]
}
case schemapb.DataType_Float16Vector:
data := singleData.(*Float16VectorFieldData).Data
dim := singleData.(*Float16VectorFieldData).Dim
steps := dim * 2
for idx := 0; idx < steps; idx++ {
data[i*steps+idx], data[j*steps+idx] = data[j*steps+idx], data[i*steps+idx]
}
case schemapb.DataType_BFloat16Vector:
data := singleData.(*BFloat16VectorFieldData).Data
dim := singleData.(*BFloat16VectorFieldData).Dim
steps := dim * 2
for idx := 0; idx < steps; idx++ {
data[i*steps+idx], data[j*steps+idx] = data[j*steps+idx], data[i*steps+idx]
}
case schemapb.DataType_Array:
data := singleData.(*ArrayFieldData).Data
data[i], data[j] = data[j], data[i]
case schemapb.DataType_JSON:
data := singleData.(*JSONFieldData).Data
data[i], data[j] = data[j], data[i]
case schemapb.DataType_Geometry:
data := singleData.(*GeometryFieldData).Data
data[i], data[j] = data[j], data[i]
case schemapb.DataType_SparseFloatVector:
fieldData := singleData.(*SparseFloatVectorFieldData)
fieldData.Contents[i], fieldData.Contents[j] = fieldData.Contents[j], fieldData.Contents[i]
case schemapb.DataType_ArrayOfVector:
fieldData := singleData.(*VectorArrayFieldData)
fieldData.Data[i], fieldData.Data[j] = fieldData.Data[j], fieldData.Data[i]
default:
errMsg := "undefined data type " + string(field.DataType)
panic(errMsg)
}
}
}
// Less returns whether i-th entry is less than j-th entry, using ID field comparison result
func (ds *DataSorter) Less(i, j int) bool {
idField := ds.getRowIDFieldData()
if idField == nil {
return true // to skip swap
}
data, ok := idField.(*Int64FieldData)
if !ok || data.Data == nil {
return true // to skip swap
}
l := len(data.Data)
// i,j range check
if i < 0 || i >= l || j < 0 || j > l {
return true // to skip swap
}
ids := data.Data
return ids[i] < ids[j]
}