mirror of
https://gitee.com/milvus-io/milvus.git
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63843dce33
issue:https://github.com/milvus-io/milvus/issues/27576 Signed-off-by: zhenshan.cao <zhenshan.cao@zilliz.com>
348 lines
10 KiB
Go
348 lines
10 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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"fmt"
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"math/rand"
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"os"
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"testing"
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"time"
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"github.com/stretchr/testify/suite"
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"go.uber.org/zap"
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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/milvuspb"
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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/util/importutilv2"
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"github.com/milvus-io/milvus/internal/util/indexparamcheck"
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"github.com/milvus-io/milvus/pkg/common"
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"github.com/milvus-io/milvus/pkg/log"
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"github.com/milvus-io/milvus/pkg/util/funcutil"
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"github.com/milvus-io/milvus/pkg/util/metric"
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"github.com/milvus-io/milvus/pkg/util/paramtable"
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"github.com/milvus-io/milvus/tests/integration"
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)
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type BulkInsertSuite struct {
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integration.MiniClusterSuite
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failed bool
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failedReason string
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pkType schemapb.DataType
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autoID bool
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fileType importutilv2.FileType
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vecType schemapb.DataType
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indexType indexparamcheck.IndexType
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metricType metric.MetricType
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}
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func (s *BulkInsertSuite) SetupTest() {
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paramtable.Init()
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s.MiniClusterSuite.SetupTest()
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s.failed = false
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s.fileType = importutilv2.Parquet
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s.pkType = schemapb.DataType_Int64
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s.autoID = false
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s.vecType = schemapb.DataType_FloatVector
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s.indexType = "HNSW"
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s.metricType = metric.L2
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}
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func (s *BulkInsertSuite) run() {
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const (
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rowCount = 100
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)
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c := s.Cluster
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ctx, cancel := context.WithTimeout(c.GetContext(), 120*time.Second)
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defer cancel()
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collectionName := "TestBulkInsert" + funcutil.GenRandomStr()
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var schema *schemapb.CollectionSchema
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fieldSchema1 := &schemapb.FieldSchema{FieldID: 100, Name: "id", DataType: s.pkType, TypeParams: []*commonpb.KeyValuePair{{Key: common.MaxLengthKey, Value: "128"}}, IsPrimaryKey: true, AutoID: s.autoID}
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fieldSchema2 := &schemapb.FieldSchema{FieldID: 101, Name: "image_path", DataType: schemapb.DataType_VarChar, TypeParams: []*commonpb.KeyValuePair{{Key: common.MaxLengthKey, Value: "65535"}}}
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fieldSchema3 := &schemapb.FieldSchema{FieldID: 102, Name: "embeddings", DataType: s.vecType, TypeParams: []*commonpb.KeyValuePair{{Key: common.DimKey, Value: "128"}}}
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fieldSchema4 := &schemapb.FieldSchema{FieldID: 103, Name: "embeddings", DataType: s.vecType, TypeParams: []*commonpb.KeyValuePair{}}
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if s.vecType != schemapb.DataType_SparseFloatVector {
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schema = integration.ConstructSchema(collectionName, dim, s.autoID, fieldSchema1, fieldSchema2, fieldSchema3)
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} else {
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schema = integration.ConstructSchema(collectionName, dim, s.autoID, fieldSchema1, fieldSchema2, fieldSchema4)
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}
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marshaledSchema, err := proto.Marshal(schema)
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s.NoError(err)
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createCollectionStatus, err := c.Proxy.CreateCollection(ctx, &milvuspb.CreateCollectionRequest{
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CollectionName: collectionName,
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Schema: marshaledSchema,
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ShardsNum: common.DefaultShardsNum,
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})
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s.NoError(err)
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s.Equal(commonpb.ErrorCode_Success, createCollectionStatus.GetErrorCode())
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var files []*internalpb.ImportFile
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err = os.MkdirAll(c.ChunkManager.RootPath(), os.ModePerm)
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s.NoError(err)
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options := []*commonpb.KeyValuePair{}
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switch s.fileType {
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case importutilv2.Numpy:
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importFile, err := GenerateNumpyFiles(c.ChunkManager, schema, rowCount)
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s.NoError(err)
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files = []*internalpb.ImportFile{importFile}
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case importutilv2.JSON:
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rowBasedFile := c.ChunkManager.RootPath() + "/" + "test.json"
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GenerateJSONFile(s.T(), rowBasedFile, schema, rowCount)
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defer os.Remove(rowBasedFile)
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files = []*internalpb.ImportFile{
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{
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Paths: []string{
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rowBasedFile,
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},
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},
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}
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case importutilv2.Parquet:
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filePath := fmt.Sprintf("/tmp/test_%d.parquet", rand.Int())
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err = GenerateParquetFile(filePath, schema, rowCount)
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s.NoError(err)
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defer os.Remove(filePath)
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files = []*internalpb.ImportFile{
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{
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Paths: []string{
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filePath,
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},
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},
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}
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case importutilv2.CSV:
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filePath := fmt.Sprintf("/tmp/test_%d.csv", rand.Int())
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sep := GenerateCSVFile(s.T(), filePath, schema, rowCount)
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defer os.Remove(filePath)
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options = []*commonpb.KeyValuePair{{Key: "sep", Value: string(sep)}}
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s.NoError(err)
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files = []*internalpb.ImportFile{
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{
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Paths: []string{
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filePath,
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},
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},
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}
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}
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importResp, err := c.Proxy.ImportV2(ctx, &internalpb.ImportRequest{
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CollectionName: collectionName,
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Files: files,
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Options: options,
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})
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s.NoError(err)
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s.Equal(int32(0), importResp.GetStatus().GetCode())
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log.Info("Import result", zap.Any("importResp", importResp))
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jobID := importResp.GetJobID()
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err = WaitForImportDone(ctx, c, jobID)
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if s.failed {
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s.T().Logf("expect failed import, err=%s", err)
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s.Error(err)
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s.Contains(err.Error(), s.failedReason)
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return
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}
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s.NoError(err)
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segments, err := c.MetaWatcher.ShowSegments()
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s.NoError(err)
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s.NotEmpty(segments)
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for _, segment := range segments {
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s.True(len(segment.GetBinlogs()) > 0)
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s.NoError(CheckLogID(segment.GetBinlogs()))
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s.True(len(segment.GetDeltalogs()) == 0)
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s.True(len(segment.GetStatslogs()) > 0)
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s.NoError(CheckLogID(segment.GetStatslogs()))
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}
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// create index
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createIndexStatus, err := c.Proxy.CreateIndex(ctx, &milvuspb.CreateIndexRequest{
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CollectionName: collectionName,
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FieldName: "embeddings",
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IndexName: "_default",
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ExtraParams: integration.ConstructIndexParam(dim, s.indexType, s.metricType),
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})
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s.NoError(err)
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s.Equal(commonpb.ErrorCode_Success, createIndexStatus.GetErrorCode())
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s.WaitForIndexBuilt(ctx, collectionName, "embeddings")
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// load
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loadStatus, err := c.Proxy.LoadCollection(ctx, &milvuspb.LoadCollectionRequest{
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CollectionName: collectionName,
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})
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s.NoError(err)
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s.Equal(commonpb.ErrorCode_Success, loadStatus.GetErrorCode())
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s.WaitForLoad(ctx, collectionName)
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// search
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expr := ""
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nq := 10
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topk := 10
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roundDecimal := -1
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params := integration.GetSearchParams(s.indexType, s.metricType)
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searchReq := integration.ConstructSearchRequest("", collectionName, expr,
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"embeddings", s.vecType, nil, s.metricType, params, nq, dim, topk, roundDecimal)
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searchResult, err := c.Proxy.Search(ctx, searchReq)
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s.NoError(err)
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s.Equal(commonpb.ErrorCode_Success, searchResult.GetStatus().GetErrorCode())
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// s.Equal(nq*topk, len(searchResult.GetResults().GetScores()))
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}
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func (s *BulkInsertSuite) TestMultiFileTypes() {
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fileTypeArr := []importutilv2.FileType{importutilv2.JSON, importutilv2.Numpy, importutilv2.Parquet, importutilv2.CSV}
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for _, fileType := range fileTypeArr {
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s.fileType = fileType
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s.vecType = schemapb.DataType_BinaryVector
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s.indexType = "BIN_IVF_FLAT"
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s.metricType = metric.HAMMING
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s.run()
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s.vecType = schemapb.DataType_FloatVector
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s.indexType = "HNSW"
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s.metricType = metric.L2
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s.run()
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s.vecType = schemapb.DataType_Float16Vector
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s.indexType = "HNSW"
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s.metricType = metric.L2
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s.run()
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s.vecType = schemapb.DataType_BFloat16Vector
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s.indexType = "HNSW"
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s.metricType = metric.L2
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s.run()
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// TODO: not support numpy for SparseFloatVector by now
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if fileType != importutilv2.Numpy {
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s.vecType = schemapb.DataType_SparseFloatVector
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s.indexType = "SPARSE_WAND"
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s.metricType = metric.IP
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s.run()
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}
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}
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}
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func (s *BulkInsertSuite) TestAutoID() {
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s.pkType = schemapb.DataType_Int64
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s.autoID = true
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s.run()
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s.pkType = schemapb.DataType_VarChar
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s.autoID = true
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s.run()
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}
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func (s *BulkInsertSuite) TestPK() {
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s.pkType = schemapb.DataType_Int64
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s.run()
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s.pkType = schemapb.DataType_VarChar
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s.run()
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}
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func (s *BulkInsertSuite) TestZeroRowCount() {
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const (
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rowCount = 0
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)
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c := s.Cluster
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ctx, cancel := context.WithTimeout(c.GetContext(), 60*time.Second)
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defer cancel()
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collectionName := "TestBulkInsert_" + funcutil.GenRandomStr()
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schema := integration.ConstructSchema(collectionName, dim, true,
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&schemapb.FieldSchema{FieldID: 100, Name: "id", DataType: schemapb.DataType_Int64, IsPrimaryKey: true, AutoID: true},
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&schemapb.FieldSchema{FieldID: 101, Name: "image_path", DataType: schemapb.DataType_VarChar, TypeParams: []*commonpb.KeyValuePair{{Key: common.MaxLengthKey, Value: "65535"}}},
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&schemapb.FieldSchema{FieldID: 102, Name: "embeddings", DataType: schemapb.DataType_FloatVector, TypeParams: []*commonpb.KeyValuePair{{Key: common.DimKey, Value: "128"}}},
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)
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marshaledSchema, err := proto.Marshal(schema)
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s.NoError(err)
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createCollectionStatus, err := c.Proxy.CreateCollection(ctx, &milvuspb.CreateCollectionRequest{
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CollectionName: collectionName,
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Schema: marshaledSchema,
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ShardsNum: common.DefaultShardsNum,
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})
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s.NoError(err)
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s.Equal(commonpb.ErrorCode_Success, createCollectionStatus.GetErrorCode())
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var files []*internalpb.ImportFile
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filePath := fmt.Sprintf("/tmp/test_%d.parquet", rand.Int())
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err = GenerateParquetFile(filePath, schema, rowCount)
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s.NoError(err)
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defer os.Remove(filePath)
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files = []*internalpb.ImportFile{
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{
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Paths: []string{
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filePath,
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},
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},
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}
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importResp, err := c.Proxy.ImportV2(ctx, &internalpb.ImportRequest{
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CollectionName: collectionName,
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Files: files,
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})
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s.NoError(err)
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log.Info("Import result", zap.Any("importResp", importResp))
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jobID := importResp.GetJobID()
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err = WaitForImportDone(ctx, c, jobID)
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s.NoError(err)
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segments, err := c.MetaWatcher.ShowSegments()
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s.NoError(err)
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s.Empty(segments)
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}
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func (s *BulkInsertSuite) TestDiskQuotaExceeded() {
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paramtable.Get().Save(paramtable.Get().QuotaConfig.DiskProtectionEnabled.Key, "true")
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paramtable.Get().Save(paramtable.Get().QuotaConfig.DiskQuota.Key, "100")
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defer paramtable.Get().Reset(paramtable.Get().QuotaConfig.DiskProtectionEnabled.Key)
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defer paramtable.Get().Reset(paramtable.Get().QuotaConfig.DiskQuota.Key)
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s.failed = false
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s.run()
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paramtable.Get().Save(paramtable.Get().QuotaConfig.DiskQuota.Key, "0.01")
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s.failed = true
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s.failedReason = "disk quota exceeded"
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s.run()
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}
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func TestBulkInsert(t *testing.T) {
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suite.Run(t, new(BulkInsertSuite))
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}
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