mirror of
https://gitee.com/milvus-io/milvus.git
synced 2026-01-05 02:12:48 +08:00
9ff023ee35
Before executing the import, partition IDs should be reordered according to partition names. Otherwise, the data might be hashed to the wrong partition during import. This PR corrects this error. issue: https://github.com/milvus-io/milvus/issues/33237 --------- Signed-off-by: bigsheeper <yihao.dai@zilliz.com>
283 lines
9.5 KiB
Go
283 lines
9.5 KiB
Go
// Licensed to the LF AI & Data foundation under one
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// or more contributor license agreements. See the NOTICE file
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// distributed with this work for additional information
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// regarding copyright ownership. The ASF licenses this file
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// to you under the Apache License, Version 2.0 (the
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// "License"); you may not use this file except in compliance
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// with the License. You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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package importv2
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import (
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"context"
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"encoding/json"
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"fmt"
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"os"
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"testing"
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"time"
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"github.com/apache/arrow/go/v12/arrow/array"
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"github.com/apache/arrow/go/v12/parquet"
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"github.com/apache/arrow/go/v12/parquet/pqarrow"
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"github.com/samber/lo"
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"github.com/sbinet/npyio"
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"github.com/stretchr/testify/assert"
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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/proto/internalpb"
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"github.com/milvus-io/milvus/internal/storage"
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pq "github.com/milvus-io/milvus/internal/util/importutilv2/parquet"
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"github.com/milvus-io/milvus/internal/util/testutil"
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"github.com/milvus-io/milvus/pkg/log"
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"github.com/milvus-io/milvus/pkg/util/merr"
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"github.com/milvus-io/milvus/pkg/util/typeutil"
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"github.com/milvus-io/milvus/tests/integration"
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)
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const dim = 128
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func GenerateParquetFile(filePath string, schema *schemapb.CollectionSchema, numRows int) error {
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_, err := GenerateParquetFileAndReturnInsertData(filePath, schema, numRows)
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return err
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}
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func GenerateParquetFileAndReturnInsertData(filePath string, schema *schemapb.CollectionSchema, numRows int) (*storage.InsertData, error) {
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w, err := os.OpenFile(filePath, os.O_RDWR|os.O_CREATE, 0o666)
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if err != nil {
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return nil, err
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}
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pqSchema, err := pq.ConvertToArrowSchema(schema)
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if err != nil {
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return nil, err
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}
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fw, err := pqarrow.NewFileWriter(pqSchema, w, parquet.NewWriterProperties(parquet.WithMaxRowGroupLength(int64(numRows))), pqarrow.DefaultWriterProps())
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if err != nil {
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return nil, err
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}
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defer fw.Close()
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insertData, err := testutil.CreateInsertData(schema, numRows)
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if err != nil {
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return nil, err
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}
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columns, err := testutil.BuildArrayData(schema, insertData)
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if err != nil {
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return nil, err
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}
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recordBatch := array.NewRecord(pqSchema, columns, int64(numRows))
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return insertData, fw.Write(recordBatch)
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}
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func GenerateNumpyFiles(cm storage.ChunkManager, schema *schemapb.CollectionSchema, rowCount int) (*internalpb.ImportFile, error) {
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writeFn := func(path string, data interface{}) error {
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f, err := os.Create(path)
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if err != nil {
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return err
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}
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defer f.Close()
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err = npyio.Write(f, data)
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if err != nil {
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return err
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}
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return nil
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}
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insertData, err := testutil.CreateInsertData(schema, rowCount)
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if err != nil {
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return nil, err
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}
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var data interface{}
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paths := make([]string, 0)
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for _, field := range schema.GetFields() {
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if field.GetAutoID() && field.GetIsPrimaryKey() {
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continue
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}
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path := fmt.Sprintf("%s/%s.npy", cm.RootPath(), field.GetName())
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fieldID := field.GetFieldID()
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dType := field.GetDataType()
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switch dType {
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case schemapb.DataType_Bool:
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data = insertData.Data[fieldID].(*storage.BoolFieldData).Data
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case schemapb.DataType_Int8:
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data = insertData.Data[fieldID].(*storage.Int8FieldData).Data
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case schemapb.DataType_Int16:
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data = insertData.Data[fieldID].(*storage.Int16FieldData).Data
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case schemapb.DataType_Int32:
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data = insertData.Data[fieldID].(*storage.Int32FieldData).Data
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case schemapb.DataType_Int64:
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data = insertData.Data[fieldID].(*storage.Int64FieldData).Data
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case schemapb.DataType_Float:
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data = insertData.Data[fieldID].(*storage.FloatFieldData).Data
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case schemapb.DataType_Double:
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data = insertData.Data[fieldID].(*storage.DoubleFieldData).Data
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case schemapb.DataType_String, schemapb.DataType_VarChar:
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data = insertData.Data[fieldID].(*storage.StringFieldData).Data
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case schemapb.DataType_BinaryVector:
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vecData := insertData.Data[fieldID].(*storage.BinaryVectorFieldData).Data
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if dim != insertData.Data[fieldID].(*storage.BinaryVectorFieldData).Dim {
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panic(fmt.Sprintf("dim mis-match: %d, %d", dim, insertData.Data[fieldID].(*storage.BinaryVectorFieldData).Dim))
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}
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const rowBytes = dim / 8
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rows := len(vecData) / rowBytes
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binVecData := make([][rowBytes]byte, 0, rows)
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for i := 0; i < rows; i++ {
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rowVec := [rowBytes]byte{}
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copy(rowVec[:], vecData[i*rowBytes:(i+1)*rowBytes])
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binVecData = append(binVecData, rowVec)
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}
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data = binVecData
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case schemapb.DataType_FloatVector:
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vecData := insertData.Data[fieldID].(*storage.FloatVectorFieldData).Data
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if dim != insertData.Data[fieldID].(*storage.FloatVectorFieldData).Dim {
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panic(fmt.Sprintf("dim mis-match: %d, %d", dim, insertData.Data[fieldID].(*storage.FloatVectorFieldData).Dim))
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}
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rows := len(vecData) / dim
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floatVecData := make([][dim]float32, 0, rows)
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for i := 0; i < rows; i++ {
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rowVec := [dim]float32{}
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copy(rowVec[:], vecData[i*dim:(i+1)*dim])
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floatVecData = append(floatVecData, rowVec)
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}
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data = floatVecData
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case schemapb.DataType_Float16Vector:
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vecData := insertData.Data[fieldID].(*storage.Float16VectorFieldData).Data
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if dim != insertData.Data[fieldID].(*storage.Float16VectorFieldData).Dim {
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panic(fmt.Sprintf("dim mis-match: %d, %d", dim, insertData.Data[fieldID].(*storage.Float16VectorFieldData).Dim))
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}
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const rowBytes = dim * 2
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rows := len(vecData) / rowBytes
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float16VecData := make([][rowBytes]byte, 0, rows)
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for i := 0; i < rows; i++ {
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rowVec := [rowBytes]byte{}
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copy(rowVec[:], vecData[i*rowBytes:(i+1)*rowBytes])
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float16VecData = append(float16VecData, rowVec)
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}
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data = float16VecData
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case schemapb.DataType_BFloat16Vector:
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vecData := insertData.Data[fieldID].(*storage.BFloat16VectorFieldData).Data
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if dim != insertData.Data[fieldID].(*storage.BFloat16VectorFieldData).Dim {
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panic(fmt.Sprintf("dim mis-match: %d, %d", dim, insertData.Data[fieldID].(*storage.BFloat16VectorFieldData).Dim))
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}
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const rowBytes = dim * 2
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rows := len(vecData) / rowBytes
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bfloat16VecData := make([][rowBytes]byte, 0, rows)
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for i := 0; i < rows; i++ {
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rowVec := [rowBytes]byte{}
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copy(rowVec[:], vecData[i*rowBytes:(i+1)*rowBytes])
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bfloat16VecData = append(bfloat16VecData, rowVec)
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}
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data = bfloat16VecData
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case schemapb.DataType_SparseFloatVector:
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data = insertData.Data[fieldID].(*storage.SparseFloatVectorFieldData).GetContents()
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case schemapb.DataType_JSON:
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data = insertData.Data[fieldID].(*storage.JSONFieldData).Data
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case schemapb.DataType_Array:
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data = insertData.Data[fieldID].(*storage.ArrayFieldData).Data
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default:
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panic(fmt.Sprintf("unsupported data type: %s", dType.String()))
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}
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err := writeFn(path, data)
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if err != nil {
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return nil, err
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}
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paths = append(paths, path)
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}
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return &internalpb.ImportFile{
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Paths: paths,
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}, nil
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}
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func GenerateJSONFile(t *testing.T, filePath string, schema *schemapb.CollectionSchema, count int) {
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insertData, err := testutil.CreateInsertData(schema, count)
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assert.NoError(t, err)
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rows := make([]map[string]any, 0, count)
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fieldIDToField := lo.KeyBy(schema.GetFields(), func(field *schemapb.FieldSchema) int64 {
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return field.GetFieldID()
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})
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for i := 0; i < count; i++ {
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data := make(map[int64]interface{})
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for fieldID, v := range insertData.Data {
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dataType := fieldIDToField[fieldID].GetDataType()
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if fieldIDToField[fieldID].GetAutoID() {
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continue
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}
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switch dataType {
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case schemapb.DataType_Array:
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data[fieldID] = v.GetRow(i).(*schemapb.ScalarField).GetIntData().GetData()
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case schemapb.DataType_JSON:
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data[fieldID] = string(v.GetRow(i).([]byte))
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case schemapb.DataType_BinaryVector:
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bytes := v.GetRow(i).([]byte)
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ints := make([]int, 0, len(bytes))
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for _, b := range bytes {
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ints = append(ints, int(b))
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}
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data[fieldID] = ints
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case schemapb.DataType_Float16Vector:
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bytes := v.GetRow(i).([]byte)
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data[fieldID] = typeutil.Float16BytesToFloat32Vector(bytes)
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case schemapb.DataType_BFloat16Vector:
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bytes := v.GetRow(i).([]byte)
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data[fieldID] = typeutil.BFloat16BytesToFloat32Vector(bytes)
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case schemapb.DataType_SparseFloatVector:
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bytes := v.GetRow(i).([]byte)
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data[fieldID] = typeutil.SparseFloatBytesToMap(bytes)
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default:
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data[fieldID] = v.GetRow(i)
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}
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}
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row := lo.MapKeys(data, func(_ any, fieldID int64) string {
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return fieldIDToField[fieldID].GetName()
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})
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rows = append(rows, row)
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}
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jsonBytes, err := json.Marshal(rows)
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assert.NoError(t, err)
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err = os.WriteFile(filePath, jsonBytes, 0o644) // nolint
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assert.NoError(t, err)
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}
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func WaitForImportDone(ctx context.Context, c *integration.MiniClusterV2, jobID string) error {
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for {
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resp, err := c.Proxy.GetImportProgress(ctx, &internalpb.GetImportProgressRequest{
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JobID: jobID,
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})
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if err != nil {
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return err
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}
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if err = merr.Error(resp.GetStatus()); err != nil {
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return err
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}
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switch resp.GetState() {
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case internalpb.ImportJobState_Completed:
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return nil
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case internalpb.ImportJobState_Failed:
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return merr.WrapErrImportFailed(resp.GetReason())
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default:
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log.Info("import progress", zap.String("jobID", jobID),
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zap.Int64("progress", resp.GetProgress()),
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zap.String("state", resp.GetState().String()))
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time.Sleep(1 * time.Second)
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}
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}
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}
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