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https://gitee.com/milvus-io/milvus.git
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The Out of Memory (OOM) error occurs because a handler retains the entire ImportRecordBatch in memory. Consequently, even when child arrays within the batch are flushed, the memory for the complete batch is not released. We temporarily fixed by deep copying record batch in #43724. The proposed fix is to split the RecordBatch into smaller sub-batches by column group. These sub-batches will be transferred via CGO, then reassembled before being written to storage using the Storage V2 API. Thus we can achieve zero-copy and only transferring references in CGO. related: #43310 Signed-off-by: shaoting-huang <shaoting.huang@zilliz.com>
209 lines
6.1 KiB
Go
209 lines
6.1 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 getvector
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import (
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"context"
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"fmt"
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"testing"
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"github.com/stretchr/testify/suite"
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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/pkg/v2/common"
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"github.com/milvus-io/milvus/pkg/v2/util/funcutil"
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"github.com/milvus-io/milvus/pkg/v2/util/metric"
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"github.com/milvus-io/milvus/tests/integration"
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)
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type TestArrayStructSuite struct {
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integration.MiniClusterSuite
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dbName string
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// test params
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nq int
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topK int
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indexType string
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metricType string
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vecType schemapb.DataType
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}
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func (s *TestArrayStructSuite) run() {
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ctx, cancel := context.WithCancel(s.Cluster.GetContext())
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defer cancel()
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collection := fmt.Sprintf("TestGetVector_%d_%d_%s_%s_%s",
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s.nq, s.topK, s.indexType, s.metricType, funcutil.GenRandomStr())
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const (
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NB = 10000
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dim = 16
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)
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if len(s.dbName) > 0 {
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createDataBaseStatus, err := s.Cluster.MilvusClient.CreateDatabase(ctx, &milvuspb.CreateDatabaseRequest{
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DbName: s.dbName,
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})
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s.Require().NoError(err)
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s.Require().Equal(createDataBaseStatus.GetErrorCode(), commonpb.ErrorCode_Success)
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}
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pkFieldName := "pkField"
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vecFieldName := "vecField"
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structFieldName := "structField"
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structSubVecFieldName := "structSubVecField"
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pk := &schemapb.FieldSchema{
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FieldID: 100,
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Name: pkFieldName,
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IsPrimaryKey: true,
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Description: "",
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DataType: schemapb.DataType_Int64,
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TypeParams: []*commonpb.KeyValuePair{
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{
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Key: common.MaxLengthKey,
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Value: "100",
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},
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},
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IndexParams: nil,
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AutoID: false,
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}
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fVec := &schemapb.FieldSchema{
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FieldID: 101,
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Name: vecFieldName,
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IsPrimaryKey: false,
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Description: "",
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DataType: schemapb.DataType_FloatVector,
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TypeParams: []*commonpb.KeyValuePair{
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{
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Key: common.DimKey,
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Value: fmt.Sprintf("%d", dim),
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},
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},
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IndexParams: nil,
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}
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structSubVec := &schemapb.FieldSchema{
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FieldID: 102,
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Name: structSubVecFieldName,
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IsPrimaryKey: false,
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Description: "",
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DataType: schemapb.DataType_ArrayOfVector,
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ElementType: s.vecType,
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TypeParams: []*commonpb.KeyValuePair{
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{
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Key: common.DimKey,
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Value: fmt.Sprintf("%d", dim),
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},
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},
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IndexParams: nil,
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}
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structField := &schemapb.StructArrayFieldSchema{
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FieldID: 103,
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Name: structFieldName,
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Fields: []*schemapb.FieldSchema{structSubVec},
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}
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schema := &schemapb.CollectionSchema{
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Name: collection,
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Description: "",
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AutoID: false,
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Fields: []*schemapb.FieldSchema{pk, fVec},
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StructArrayFields: []*schemapb.StructArrayFieldSchema{structField},
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}
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marshaledSchema, err := proto.Marshal(schema)
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s.Require().NoError(err)
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createCollectionStatus, err := s.Cluster.MilvusClient.CreateCollection(ctx, &milvuspb.CreateCollectionRequest{
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DbName: s.dbName,
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CollectionName: collection,
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Schema: marshaledSchema,
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ShardsNum: 2,
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})
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s.Require().NoError(err)
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s.Require().Equal(createCollectionStatus.GetErrorCode(), commonpb.ErrorCode_Success)
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fieldsData := make([]*schemapb.FieldData, 0, 5)
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// pk
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fieldsData = append(fieldsData, integration.NewInt64FieldData(pkFieldName, NB))
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// vec
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fieldsData = append(fieldsData, integration.NewFloatVectorFieldData(vecFieldName, NB, dim))
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// struct
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fieldsData = append(fieldsData, integration.NewStructArrayFieldData(structField, structFieldName, NB, dim))
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hashKeys := integration.GenerateHashKeys(NB)
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insertResult, err := s.Cluster.MilvusClient.Insert(ctx, &milvuspb.InsertRequest{
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DbName: s.dbName,
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CollectionName: collection,
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FieldsData: fieldsData,
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HashKeys: hashKeys,
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NumRows: uint32(NB),
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})
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s.Require().NoError(err)
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s.Require().Equal(insertResult.GetStatus().GetErrorCode(), commonpb.ErrorCode_Success)
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// flush
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flushResp, err := s.Cluster.MilvusClient.Flush(ctx, &milvuspb.FlushRequest{
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DbName: s.dbName,
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CollectionNames: []string{collection},
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})
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s.Require().NoError(err)
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segmentIDs, has := flushResp.GetCollSegIDs()[collection]
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ids := segmentIDs.GetData()
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s.Require().NotEmpty(segmentIDs)
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s.Require().True(has)
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flushTs, has := flushResp.GetCollFlushTs()[collection]
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s.Require().True(has)
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s.WaitForFlush(ctx, ids, flushTs, s.dbName, collection)
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segments, err := s.Cluster.ShowSegments(collection)
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s.Require().NoError(err)
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s.Require().NotEmpty(segments)
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// // create index
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// createIndexResult, err := s.Cluster.Proxy.CreateIndex(ctx, &milvuspb.CreateIndexRequest{
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// DbName: s.dbName,
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// CollectionName: collection,
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// FieldName: structSubVecFieldName,
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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.Require().NoError(err)
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// s.Require().Equal(createIndexResult.GetErrorCode(), commonpb.ErrorCode_Success)
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// s.WaitForIndexBuiltWithDB(ctx, s.dbName, collection, structSubVecFieldName)
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}
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func (s *TestArrayStructSuite) TestGetVector_ArrayStruct_FloatVector() {
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s.nq = 10
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s.topK = 10
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s.indexType = integration.IndexHNSW
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s.metricType = metric.L2
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s.vecType = schemapb.DataType_FloatVector
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s.run()
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}
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func TestGetVectorArrayStruct(t *testing.T) {
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t.Skip("Skip integration test, need to refactor integration test framework.")
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suite.Run(t, new(TestArrayStructSuite))
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}
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