// 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 importv2 import ( "context" "fmt" "math/rand" "os" "testing" "time" "github.com/stretchr/testify/suite" "go.uber.org/zap" "google.golang.org/protobuf/proto" "github.com/milvus-io/milvus-proto/go-api/v2/commonpb" "github.com/milvus-io/milvus-proto/go-api/v2/milvuspb" "github.com/milvus-io/milvus-proto/go-api/v2/schemapb" "github.com/milvus-io/milvus/internal/proto/internalpb" "github.com/milvus-io/milvus/internal/util/importutilv2" "github.com/milvus-io/milvus/internal/util/indexparamcheck" "github.com/milvus-io/milvus/pkg/common" "github.com/milvus-io/milvus/pkg/log" "github.com/milvus-io/milvus/pkg/util/funcutil" "github.com/milvus-io/milvus/pkg/util/metric" "github.com/milvus-io/milvus/pkg/util/paramtable" "github.com/milvus-io/milvus/tests/integration" ) type BulkInsertSuite struct { integration.MiniClusterSuite failed bool failedReason string pkType schemapb.DataType autoID bool fileType importutilv2.FileType vecType schemapb.DataType indexType indexparamcheck.IndexType metricType metric.MetricType } func (s *BulkInsertSuite) SetupTest() { paramtable.Init() s.MiniClusterSuite.SetupTest() s.failed = false s.fileType = importutilv2.Parquet s.pkType = schemapb.DataType_Int64 s.autoID = false s.vecType = schemapb.DataType_FloatVector s.indexType = "HNSW" s.metricType = metric.L2 } func (s *BulkInsertSuite) run() { const ( rowCount = 100 ) c := s.Cluster ctx, cancel := context.WithTimeout(c.GetContext(), 120*time.Second) defer cancel() collectionName := "TestBulkInsert" + funcutil.GenRandomStr() var schema *schemapb.CollectionSchema fieldSchema1 := &schemapb.FieldSchema{FieldID: 100, Name: "id", DataType: s.pkType, TypeParams: []*commonpb.KeyValuePair{{Key: common.MaxLengthKey, Value: "128"}}, IsPrimaryKey: true, AutoID: s.autoID} fieldSchema2 := &schemapb.FieldSchema{FieldID: 101, Name: "image_path", DataType: schemapb.DataType_VarChar, TypeParams: []*commonpb.KeyValuePair{{Key: common.MaxLengthKey, Value: "65535"}}} fieldSchema3 := &schemapb.FieldSchema{FieldID: 102, Name: "embeddings", DataType: s.vecType, TypeParams: []*commonpb.KeyValuePair{{Key: common.DimKey, Value: "128"}}} fieldSchema4 := &schemapb.FieldSchema{FieldID: 103, Name: "embeddings", DataType: s.vecType, TypeParams: []*commonpb.KeyValuePair{}} if s.vecType != schemapb.DataType_SparseFloatVector { schema = integration.ConstructSchema(collectionName, dim, s.autoID, fieldSchema1, fieldSchema2, fieldSchema3) } else { schema = integration.ConstructSchema(collectionName, dim, s.autoID, fieldSchema1, fieldSchema2, fieldSchema4) } marshaledSchema, err := proto.Marshal(schema) s.NoError(err) createCollectionStatus, err := c.Proxy.CreateCollection(ctx, &milvuspb.CreateCollectionRequest{ CollectionName: collectionName, Schema: marshaledSchema, ShardsNum: common.DefaultShardsNum, }) s.NoError(err) s.Equal(commonpb.ErrorCode_Success, createCollectionStatus.GetErrorCode()) var files []*internalpb.ImportFile err = os.MkdirAll(c.ChunkManager.RootPath(), os.ModePerm) s.NoError(err) options := []*commonpb.KeyValuePair{} switch s.fileType { case importutilv2.Numpy: importFile, err := GenerateNumpyFiles(c.ChunkManager, schema, rowCount) s.NoError(err) files = []*internalpb.ImportFile{importFile} case importutilv2.JSON: rowBasedFile := c.ChunkManager.RootPath() + "/" + "test.json" GenerateJSONFile(s.T(), rowBasedFile, schema, rowCount) defer os.Remove(rowBasedFile) files = []*internalpb.ImportFile{ { Paths: []string{ rowBasedFile, }, }, } case importutilv2.Parquet: filePath := fmt.Sprintf("/tmp/test_%d.parquet", rand.Int()) err = GenerateParquetFile(filePath, schema, rowCount) s.NoError(err) defer os.Remove(filePath) files = []*internalpb.ImportFile{ { Paths: []string{ filePath, }, }, } case importutilv2.CSV: filePath := fmt.Sprintf("/tmp/test_%d.csv", rand.Int()) sep := GenerateCSVFile(s.T(), filePath, schema, rowCount) defer os.Remove(filePath) options = []*commonpb.KeyValuePair{{Key: "sep", Value: string(sep)}} s.NoError(err) files = []*internalpb.ImportFile{ { Paths: []string{ filePath, }, }, } } importResp, err := c.Proxy.ImportV2(ctx, &internalpb.ImportRequest{ CollectionName: collectionName, Files: files, Options: options, }) s.NoError(err) s.Equal(int32(0), importResp.GetStatus().GetCode()) log.Info("Import result", zap.Any("importResp", importResp)) jobID := importResp.GetJobID() err = WaitForImportDone(ctx, c, jobID) if s.failed { s.T().Logf("expect failed import, err=%s", err) s.Error(err) s.Contains(err.Error(), s.failedReason) return } s.NoError(err) segments, err := c.MetaWatcher.ShowSegments() s.NoError(err) s.NotEmpty(segments) for _, segment := range segments { s.True(len(segment.GetBinlogs()) > 0) s.NoError(CheckLogID(segment.GetBinlogs())) s.True(len(segment.GetDeltalogs()) == 0) s.True(len(segment.GetStatslogs()) > 0) s.NoError(CheckLogID(segment.GetStatslogs())) } // create index createIndexStatus, err := c.Proxy.CreateIndex(ctx, &milvuspb.CreateIndexRequest{ CollectionName: collectionName, FieldName: "embeddings", IndexName: "_default", ExtraParams: integration.ConstructIndexParam(dim, s.indexType, s.metricType), }) s.NoError(err) s.Equal(commonpb.ErrorCode_Success, createIndexStatus.GetErrorCode()) s.WaitForIndexBuilt(ctx, collectionName, "embeddings") // load loadStatus, err := c.Proxy.LoadCollection(ctx, &milvuspb.LoadCollectionRequest{ CollectionName: collectionName, }) s.NoError(err) s.Equal(commonpb.ErrorCode_Success, loadStatus.GetErrorCode()) s.WaitForLoad(ctx, collectionName) // search expr := "" nq := 10 topk := 10 roundDecimal := -1 params := integration.GetSearchParams(s.indexType, s.metricType) searchReq := integration.ConstructSearchRequest("", collectionName, expr, "embeddings", s.vecType, nil, s.metricType, params, nq, dim, topk, roundDecimal) searchResult, err := c.Proxy.Search(ctx, searchReq) s.NoError(err) s.Equal(commonpb.ErrorCode_Success, searchResult.GetStatus().GetErrorCode()) // s.Equal(nq*topk, len(searchResult.GetResults().GetScores())) } func (s *BulkInsertSuite) TestMultiFileTypes() { fileTypeArr := []importutilv2.FileType{importutilv2.JSON, importutilv2.Numpy, importutilv2.Parquet, importutilv2.CSV} for _, fileType := range fileTypeArr { s.fileType = fileType s.vecType = schemapb.DataType_BinaryVector s.indexType = "BIN_IVF_FLAT" s.metricType = metric.HAMMING s.run() s.vecType = schemapb.DataType_FloatVector s.indexType = "HNSW" s.metricType = metric.L2 s.run() s.vecType = schemapb.DataType_Float16Vector s.indexType = "HNSW" s.metricType = metric.L2 s.run() s.vecType = schemapb.DataType_BFloat16Vector s.indexType = "HNSW" s.metricType = metric.L2 s.run() // TODO: not support numpy for SparseFloatVector by now if fileType != importutilv2.Numpy { s.vecType = schemapb.DataType_SparseFloatVector s.indexType = "SPARSE_WAND" s.metricType = metric.IP s.run() } } } func (s *BulkInsertSuite) TestAutoID() { s.pkType = schemapb.DataType_Int64 s.autoID = true s.run() s.pkType = schemapb.DataType_VarChar s.autoID = true s.run() } func (s *BulkInsertSuite) TestPK() { s.pkType = schemapb.DataType_Int64 s.run() s.pkType = schemapb.DataType_VarChar s.run() } func (s *BulkInsertSuite) TestZeroRowCount() { const ( rowCount = 0 ) c := s.Cluster ctx, cancel := context.WithTimeout(c.GetContext(), 60*time.Second) defer cancel() collectionName := "TestBulkInsert_" + funcutil.GenRandomStr() schema := integration.ConstructSchema(collectionName, dim, true, &schemapb.FieldSchema{FieldID: 100, Name: "id", DataType: schemapb.DataType_Int64, IsPrimaryKey: true, AutoID: true}, &schemapb.FieldSchema{FieldID: 101, Name: "image_path", DataType: schemapb.DataType_VarChar, TypeParams: []*commonpb.KeyValuePair{{Key: common.MaxLengthKey, Value: "65535"}}}, &schemapb.FieldSchema{FieldID: 102, Name: "embeddings", DataType: schemapb.DataType_FloatVector, TypeParams: []*commonpb.KeyValuePair{{Key: common.DimKey, Value: "128"}}}, ) marshaledSchema, err := proto.Marshal(schema) s.NoError(err) createCollectionStatus, err := c.Proxy.CreateCollection(ctx, &milvuspb.CreateCollectionRequest{ CollectionName: collectionName, Schema: marshaledSchema, ShardsNum: common.DefaultShardsNum, }) s.NoError(err) s.Equal(commonpb.ErrorCode_Success, createCollectionStatus.GetErrorCode()) var files []*internalpb.ImportFile filePath := fmt.Sprintf("/tmp/test_%d.parquet", rand.Int()) err = GenerateParquetFile(filePath, schema, rowCount) s.NoError(err) defer os.Remove(filePath) files = []*internalpb.ImportFile{ { Paths: []string{ filePath, }, }, } importResp, err := c.Proxy.ImportV2(ctx, &internalpb.ImportRequest{ CollectionName: collectionName, Files: files, }) s.NoError(err) log.Info("Import result", zap.Any("importResp", importResp)) jobID := importResp.GetJobID() err = WaitForImportDone(ctx, c, jobID) s.NoError(err) segments, err := c.MetaWatcher.ShowSegments() s.NoError(err) s.Empty(segments) } func (s *BulkInsertSuite) TestDiskQuotaExceeded() { paramtable.Get().Save(paramtable.Get().QuotaConfig.DiskProtectionEnabled.Key, "true") paramtable.Get().Save(paramtable.Get().QuotaConfig.DiskQuota.Key, "100") defer paramtable.Get().Reset(paramtable.Get().QuotaConfig.DiskProtectionEnabled.Key) defer paramtable.Get().Reset(paramtable.Get().QuotaConfig.DiskQuota.Key) s.failed = false s.run() paramtable.Get().Save(paramtable.Get().QuotaConfig.DiskQuota.Key, "0.01") s.failed = true s.failedReason = "disk quota exceeded" s.run() } func TestBulkInsert(t *testing.T) { suite.Run(t, new(BulkInsertSuite)) }