milvus insert api的数据结构源码分析

2024-02-18 17:07:49 浏览数 (3)

insert api的数据结构

一个完整的insert例子:

代码语言：python代码运行次数：0复制
import numpy as np
from pymilvus import (
    connections,
    FieldSchema, CollectionSchema, DataType,
    Collection,
)

num_entities, dim = 10, 3

print("start connecting to Milvus")
connections.connect("default", host="192.168.230.71", port="19530")

fields = [
    FieldSchema(name="pk", dtype=DataType.INT64, is_primary=True, auto_id=True),
    FieldSchema(name="book_id", dtype=DataType.INT64),
    FieldSchema(name="embeddings", dtype=DataType.FLOAT_VECTOR, dim=dim)
]

schema = CollectionSchema(fields, "hello_milvus is the simplest demo to introduce the APIs")

print("Create collection `hello_milvus`")
hello_milvus = Collection("hello_milvus", schema, consistency_level="Eventually",shards_num=1)


print("Start inserting entities")
rng = np.random.default_rng(seed=19530)
entities = [
    [i for i in range(num_entities)],  # field book_id
    rng.random((num_entities, dim)),    # field embeddings
]

insert_result = hello_milvus.insert(entities)

hello_milvus.flush()

InsertRequest数据结构:

代码语言：go复制
type InsertRequest struct {
	Base                 *commonpb.MsgBase
	DbName               string
	CollectionName       string
	PartitionName        string
	FieldsData           []*schemapb.FieldData
	HashKeys             []uint32
	NumRows              uint32
	XXX_NoUnkeyedLiteral struct{}
	XXX_unrecognized     []byte
	XXX_sizecache        int32
}

FieldsData是一个数组，如果insert有3列，则数组长度为3，按照插入顺序。

FieldData数据结构:

代码语言：go复制
type FieldData struct {
	Type      DataType 
	FieldName string   
	// Types that are valid to be assigned to Field:
	//
	//	*FieldData_Scalars
	//	*FieldData_Vectors
	Field                isFieldData_Field
	FieldId              int64
	IsDynamic            bool
	XXX_NoUnkeyedLiteral struct{}
	XXX_unrecognized     []byte
	XXX_sizecache        int32
}

isFieldData_Field是一个接口:

代码语言：go复制
type isFieldData_Field interface {
	isFieldData_Field()
}

它有2个实现:FieldData_Scalars和FieldData_Vectors。

代码语言：go复制
type FieldData_Scalars struct {
	Scalars *ScalarField
}

type FieldData_Vectors struct {
	Vectors *VectorField
}

FieldData_Scalars存储标量数据，FieldData_Vectors存储向量数据。

ScalarField数据结构:

代码语言：go复制
type ScalarField struct {
	// Types that are valid to be assigned to Data:
	//
	//	*ScalarField_BoolData
	//	*ScalarField_IntData
	//	*ScalarField_LongData
	//	*ScalarField_FloatData
	//	*ScalarField_DoubleData
	//	*ScalarField_StringData
	//	*ScalarField_BytesData
	//	*ScalarField_ArrayData
	//	*ScalarField_JsonData
	Data                 isScalarField_Data
	XXX_NoUnkeyedLiteral struct{}
	XXX_unrecognized     []byte
	XXX_sizecache        int32
}

isScalarField_Data是一个接口。

代码语言：go复制
type isScalarField_Data interface {
	isScalarField_Data()
}

isScalarField_Data的实现有9个：

  • ScalarField_BoolData
  • ScalarField_IntData
  • ScalarField_LongData
  • ScalarField_FloatData
  • ScalarField_DoubleData
  • ScalarField_StringData
  • ScalarField_BytesData
  • ScalarField_ArrayData
  • ScalarField_JsonData

以ScalarField_LongData为例:

代码语言：go复制
type ScalarField_LongData struct {
	LongData *LongArray
}

type LongArray struct {
	Data                 []int64
	XXX_NoUnkeyedLiteral struct{}
	XXX_unrecognized     []byte
	XXX_sizecache        int32
}

VectorField数据结构:

代码语言：go复制
type VectorField struct {
	Dim int64
	// Types that are valid to be assigned to Data:
	//
	//	*VectorField_FloatVector
	//	*VectorField_BinaryVector
	//	*VectorField_Float16Vector
	Data                 isVectorField_Data
	XXX_NoUnkeyedLiteral struct{}
	XXX_unrecognized     []byte
	XXX_sizecache        int32
}

isVectorField_Data是一个接口。

代码语言：go复制
type isVectorField_Data interface {
	isVectorField_Data()
}

isVectorField_Data有3种实现:

  • VectorField_FloatVector
  • VectorField_BinaryVector
  • VectorField_Float16Vector

以VectorField_FloatVector为例:

代码语言：go复制
type VectorField_FloatVector struct {
	FloatVector *FloatArray
}

type FloatArray struct {
	Data                 []float32
	XXX_NoUnkeyedLiteral struct{}
	XXX_unrecognized     []byte
	XXX_sizecache        int32
}

案例

向hello_milvus插入10个3维向量。

代码语言：python代码运行次数：0复制
num_entities, dim = 10, 3
rng = np.random.default_rng(seed=19530)
entities = [
    [i for i in range(num_entities)],
    rng.random((num_entities, dim)), 
]
insert_result = hello_milvus.insert(entities)

FloatVector是一个长度为30的float32数组，插入的是10个3维向量，1个向量是3个float32，在这里展开了。

向量数据库milvus

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