Table of Contents

Aggregate metadata updates

Persist metadata changes to local embedded store
Example Topologies
Topologies Not Working!
How is it implemented?
Limitation

Parallel filers with embedded filer store

If one filer is not enough, you can add more filers. This seems easy with shared filer stores, such as Redis, MySql, Postgres, Cassandra, HBase, etc.

But did you notice this also works for embedded filer stores, such as LevelDB, RocksDB, SQLite, etc?

How is it possible?

Automatic Peer Discovery

When a filer starts up, it will report itself to the master. So the master knows all the filers. It will keep each filer updated about its peers (since version 2.77).

So when a filer was added or removed from the cluster, there is no configuration change needed. This makes rolling-restart much easier, and filer instances in Kubernetes can run in ReplicaSet instead of StatefulSet.

What's more, adding a fresh new filer will automatically synchronize the metadata with other filers. Resuming a paused filer will also resume the metadata synchronization from when it was stopped. Everything will/should just work!

Note however that using multiple replicated embedded filers is only eventually consistent. So using this setup behind a load-balancer might not work as expected.

Metadata synchronization

Knowing all the peers, one filer will keep its own metadata updated:

Aggregate filer meta data changes from peers
Replay filer meta data changes to local filer store, if it is an embedded store.

Aggregate metadata updates

This is tightly related to FUSE Mount, which streams filer meta data changes from one filer. When using multiple filers but without peer file metadata updates, a FUSE mount can only see the changes applied to the connected filer.

So aggregating metadata updates form its peers is required when the filers are using either shared or dedicated filer stores.

  FUSE mount <----> filer1 -- filer2
                       \       /
                        \     /
                         filer3

Persist metadata changes to local embedded store

If the filer is running on embedded store, the metadata updates from its peers would be saved locally.

This basically synchronize the metadata across all the filer stores, where every filer store will have a full copy of all the metadata.

This also naturally replicated the filer store to achieve high availability for metadata.

Example Topologies

Multiple filers with leveldb stores

filer1(leveldb) <-> filer2(leveldb) <-> filer3(leveldb)

Two filers are fine. There is no requirements for number of filers.

filer1(leveldb) <-> filer2(leveldb)

Two filers with different embedded stores are also fine. Of course, you will need a different filer.toml.

filer1(leveldb) <-> filer2(rocksdb)

Two filers with one shared store instance are fine.

filer1(mysql) <-> filer2(mysql)

Topologies Not Working!

Two filers with a shared store and an embedded store are NOT fine.

This is because the filer2 here will not attempt to persist filer1 metadata updates to its mysql store.

filer1(leveldb) <--XX NOT WORKING XX---> filer2(mysql)

How is it implemented?

Each filer has a local meta data change log. When starting, each filer will subscribe to meta data changes from its peers and apply to local filer store.

Each filer store will auto generate a unique filer.store.id. So for shared filer stores, such as mysql/postgres/redis, there is no need to setup peers because the filer.store.id will be the same.

The subscription will also periodically checkpoint the subscription progress, so the subscription can resume if either filer is restarted.

It is actually OK if you need to change filer IP or port. The replication can still resume as long as the filer store has the same content.

Limitation

Multiple filers with local leveldb filer stores can work well. However, this layout does not work well with weed filer.sync cross data center replication as of now. This is because currently weed filer.sync use filer.store.id to identify data that needs to be replicated. Having multiple filer.store.id will confuse the weed filer.sync.

Introduction

API

Configuration

Filer

Filer Stores

Advanced Filer Configurations

FUSE Mount

FIO benchmark

WebDAV

Cloud Drive

AWS S3 API

AWS IAM

Machine Learning

TensorFlow with SeaweedFS

HDFS

Replication and Backup

Async Replication to another Filer [Deprecated]
Async Backup
Async Filer Metadata Backup
Async Replication to Cloud [Deprecated]
Kubernetes Backups and Recovery with K8up