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For solving Problem 3, We redefine the interface implemented by minio. All file storage needs to implement this interface.

Code Block

title	ChunkManager interface
linenumbers	true

type ChunkManager interface {
	GetPath(filePath string) (string, error)
	GetSize(filePath string) (int64, error)
	Write(filePath string, content []byte) error
	MultiWrite(contents map[string][]byte) error
	Exist(filePath string) bool
	Read(filePath string) ([]byte, error)
	MultiRead(filePaths []string) ([][]byte, error)
	ReadWithPrefix(prefix string) ([]string, [][]byte, error)
	ReadAt(filePath string, off int64, length int64) (p []byte, err error)
	Remove(filePath string) error
	MultiRemove(filePaths []string) error
	RemoveWithPrefix(prefix string) error
}

For this interface we will have three implementations, LocalChunkManager, MinioChunkmanager and VectorChunkManager.
VectorChunkManager is an optimized management class for vector reading under distributed milvus. It will use minio as a remote chunkManager and local file system as a vector cache. When reading a file, it will be downloaded from the minio to the local, and then the relevant data will be read from the local. In the standalone version, we will replace minioChunkManager with localChunkManager as the implementation of remoteChunkManager.

ChunkManagerFactory

For Problem 1, a chunkManagerFactory similar to msgStream. Factory is added to generate chunkManagers with different configurations.

Code Block

title	ChunkManager Factory
linenumbers	true

type ChunkManagerFactory struct {
	localStorage string
	remoteStorage string
}
func NewChunkManagerFactory(local, remote string) *ChunkManagerFactory{}
func (cmf *ChunkManagerFactory) NewLocalChunkManager(opts ...storage.Options){}
func (cmf *ChunkManagerFactory) NewRemoteChunkManager(opts ...storage.Options){
	switch (cmf.remoteStorage){
	case "s3":
	case "minio":
	...
	}
}

Options is needed when generating a new chunkManager. The Options maybe like this.

Code Block

title	ChunkManager Config
linenumbers	true

type config struct {
	address string
	bucketName string
	accessKeyID string
	secretAccessKeyID string
	useSSL bool
	createBucket bool
	rootPath string
}

type Option func(*config)

func Address(addr string) Option {
	return func(c *config) {
	c.address = addr
	}
}

This structure will have some redundancy. For example, local storage will not require parameters such as address and bucketname. but will be easier to reuse.

Use a more generic factory instead of the existing msgFactory to build nodes. And the factory will be like this

Code Block

title	Factory Struct
linenumbers	true

type Factory struct {
	msgF msgstream.Factory
	storageF storage.ChunkManagerFactory
}

func newDefaultFactory(opts ...Option) *Factory {
	c := newDefaultConfig()
	for opt := range opts {
		opt(c)
	}
	return &Factory{
		MsgFactory: msgstream.NewFactory(c.msgstream),
		storageF: storage.NewChunkManagerFactory(c.localStorage, c.remoteStorage),
	}
}

type config struct {
	msgStream string
	localStorage string
	remoteStorage string
}
func newDefaultConfig() *config{}

type Option func(*config)

func localStorage(localStorage string) Option {
	return func(c *config) {
		c.localStorage = localStorage
	}
}

deploy in milvus.yaml will set the default storage engine for different deploy mode. The localStorage and remoteStorage will be used to set what to use as the storage engine.
Code Block
language yml
title milvus.yaml
linenumbers true
collapse true
deploy: standalone: localStorage: "local" remoteStorage: "local" distributed: localStorage: "local" remoteStorage: "minio"
In standalone mode, remoteStorage using local is a more efficient choice. Of course you can also choose minio.
However, if the distributed version chooses local storage, because the nodes are located on different machines, the data stored locally is inconsistent. Therefore, careful consideration should be given when choosing a storage engine.

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