Function BenchmarkVectorOperations

api/service/vectorstore/test_basic.go:195–276

BenchmarkVectorOperations 向量操作性能基准测试

(vectorCount int, dimension int)

// BenchmarkVectorOperations 向量操作性能基准测试
func BenchmarkVectorOperations(vectorCount int, dimension int) error {
	logger.SysLogf("=== 性能基准测试: %d个%d维向量 ===", vectorCount, dimension)

	config := LoadFromEnv()
	store, err := NewVectorStore(config)
	if err != nil {
		return fmt.Errorf("创建向量存储失败: %v", err)
	}

	ctx := context.Background()
	if err := store.Connect(ctx); err != nil {
		return fmt.Errorf("连接失败: %v", err)
	}
	defer store.Disconnect(ctx)

	testCollection := "benchmark_collection_" + fmt.Sprintf("%d", time.Now().Unix())

	// 创建集合
	collectionConfig := CollectionConfig{
		Name:      testCollection,
		Dimension: dimension,
		Metric:    "cosine",
		IndexType: "HNSW",
	}

	if err := store.CreateCollection(ctx, collectionConfig); err != nil {
		return fmt.Errorf("创建集合失败: %v", err)
	}
	defer store.DeleteCollection(ctx, testCollection)

	// 生成测试向量
	vectors := make([]VectorRecord, vectorCount)
	for i := 0; i < vectorCount; i++ {
		vector := make([]float32, dimension)
		for j := 0; j < dimension; j++ {
			vector[j] = float32(i*dimension + j)
		}
		vectors[i] = VectorRecord{
			ID:     i + 1,
			Vector: vector,
			Metadata: map[string]interface{}{
				"index": i,
			},
		}
	}

	// 测试批量插入性能
	logger.SysLogf("插入 %d 个向量...", vectorCount)
	startTime := time.Now()
	if err := store.BatchInsert(ctx, testCollection, vectors); err != nil {
		return fmt.Errorf("批量插入失败: %v", err)
	}
	insertDuration := time.Since(startTime)
	insertThroughput := float64(vectorCount) / insertDuration.Seconds()

	logger.SysLogf("插入完成: 耗时 %v, 吞吐量 %.2f vectors/sec", insertDuration, insertThroughput)

	// 测试搜索性能