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@@ -67,7 +67,7 @@ Table of Contents * Download the latest binary from https://github.com/chrislusf/seaweedfs/releases and unzip a single binary file `weed` or `weed.exe` * Run `weed server -dir=/some/data/dir -s3` to start one master, one volume server, one filer, and one S3 gateway. -Also, to increase capacity, just add more volume servers by `weed volume -dir="/some/data/dir2" -mserver="<master_host>:9333" -port=8081` locally or a different machine. That is it! +Also, to increase capacity, just add more volume servers by running `weed volume -dir="/some/data/dir2" -mserver="<master_host>:9333" -port=8081` locally, or on a different machine, or on thoudsands of machines. That is it! ## Introduction ## @@ -76,15 +76,17 @@ SeaweedFS is a simple and highly scalable distributed file system. There are two 1. to store billions of files! 2. to serve the files fast! -SeaweedFS started as an Object Store to handle small files efficiently. Instead of managing all file metadata in a central master, the central master only manages file volumes, and it lets these volume servers manage files and their metadata. This relieves concurrency pressure from the central master and spreads file metadata into volume servers, allowing faster file access (O(1), usually just one disk read operation). +SeaweedFS started as an Object Store to handle small files efficiently. Instead of managing all file metadata in a central master, the central master only manages volumes on volume servers, and these volume servers manage files and their metadata. This relieves concurrency pressure from the central master and spreads file metadata into volume servers, allowing faster file access (O(1), usually just one disk read operation). -SeaweedFS can transparently integrate with the cloud. With hot data on local cluster, and warm data on the cloud with O(1) access time, SeaweedFS can achieve both fast local access time and elastic cloud storage capacity, without any client side changes. +SeaweedFS can transparently integrate with the cloud. With hot data on local cluster, and warm data on the cloud with O(1) access time, SeaweedFS can achieve both fast local access time and elastic cloud storage capacity. What's more, the cloud storage access API cost is minimized. Faster and Cheaper than direct cloud storage! There is only 40 bytes of disk storage overhead for each file's metadata. It is so simple with O(1) disk reads that you are welcome to challenge the performance with your actual use cases. SeaweedFS started by implementing [Facebook's Haystack design paper](http://www.usenix.org/event/osdi10/tech/full_papers/Beaver.pdf). Also, SeaweedFS implements erasure coding with ideas from [f4: Facebookâs Warm BLOB Storage System](https://www.usenix.org/system/files/conference/osdi14/osdi14-paper-muralidhar.pdf) -On top of the object store, optional [Filer] can support directories and POSIX attributes. Filer is a separate linearly-scalable stateless server with customizable metadata stores, e.g., MySql, Postgres, Mongodb, Redis, Cassandra, Elastic Search, LevelDB, MemSql, TiDB, Etcd, CockroachDB, etc. +On top of the object store, optional [Filer] can support directories and POSIX attributes. Filer is a separate linearly-scalable stateless server with customizable metadata stores, e.g., MySql, Postgres, Redis, Cassandra, HBase, Mongodb, Elastic Search, LevelDB, RocksDB, MemSql, TiDB, Etcd, CockroachDB, etc. + +For any distributed key value stores, the large values can be offloaded to SeaweedFS. With the fast access speed and linearly scalable capacity, SeaweedFS can work as a distributed [Key-Large-Value store][KeyLargeValueStore]. [Back to TOC](#table-of-contents) @@ -117,7 +119,10 @@ On top of the object store, optional [Filer] can support directories and POSIX a * [WebDAV] accesses as a mapped drive on Mac and Windows, or from mobile devices. * [AES256-GCM Encrypted Storage][FilerDataEncryption] safely stores the encrypted data. * [Super Large Files][SuperLargeFiles] stores large or super large files in tens of TB. + +## Kubernetes ## * [Kubernetes CSI Driver][SeaweedFsCsiDriver] A Container Storage Interface (CSI) Driver. [](https://hub.docker.com/r/chrislusf/seaweedfs-csi-driver/) +* [SeaweedFS Operator](https://github.com/seaweedfs/seaweedfs-operator) [Filer]: https://github.com/chrislusf/seaweedfs/wiki/Directories-and-Files [SuperLargeFiles]: https://github.com/chrislusf/seaweedfs/wiki/Data-Structure-for-Large-Files @@ -134,6 +139,7 @@ On top of the object store, optional [Filer] can support directories and POSIX a [SeaweedFsCsiDriver]: https://github.com/seaweedfs/seaweedfs-csi-driver [ActiveActiveAsyncReplication]: https://github.com/chrislusf/seaweedfs/wiki/Filer-Active-Active-cross-cluster-continuous-synchronization [FilerStoreReplication]: https://github.com/chrislusf/seaweedfs/wiki/Filer-Store-Replication +[KeyLargeValueStore]: https://github.com/chrislusf/seaweedfs/wiki/Filer-as-a-Key-Large-Value-Store [Back to TOC](#table-of-contents) @@ -335,7 +341,7 @@ Usually hot data are fresh and warm data are old. SeaweedFS puts the newly creat With the O(1) access time, the network latency cost is kept at minimum. -If the hot~warm data is split as 20~80, with 20 servers, you can achieve storage capacity of 100 servers. That's a cost saving of 80%! Or you can repurpose the 80 servers to store new data also, and get 5X storage throughput. +If the hot/warm data is split as 20/80, with 20 servers, you can achieve storage capacity of 100 servers. That's a cost saving of 80%! Or you can repurpose the 80 servers to store new data also, and get 5X storage throughput. [Back to TOC](#table-of-contents) @@ -365,7 +371,7 @@ The architectures are mostly the same. SeaweedFS aims to store and read files fa * SeaweedFS optimizes for small files, ensuring O(1) disk seek operation, and can also handle large files. * SeaweedFS statically assigns a volume id for a file. Locating file content becomes just a lookup of the volume id, which can be easily cached. -* SeaweedFS Filer metadata store can be any well-known and proven data stores, e.g., Cassandra, Mongodb, Redis, Elastic Search, MySql, Postgres, MemSql, TiDB, CockroachDB, Etcd etc, and is easy to customized. +* SeaweedFS Filer metadata store can be any well-known and proven data stores, e.g., Redis, Cassandra, HBase, Mongodb, Elastic Search, MySql, Postgres, MemSql, TiDB, CockroachDB, Etcd etc, and is easy to customized. * SeaweedFS Volume server also communicates directly with clients via HTTP, supporting range queries, direct uploads, etc. | System | File Metadata | File Content Read| POSIX | REST API | Optimized for large number of small files | @@ -403,11 +409,11 @@ SeaweedFS has a centralized master group to look up free volumes, while Ceph use Same as SeaweedFS, Ceph is also based on the object store RADOS. Ceph is rather complicated with mixed reviews. -Ceph uses CRUSH hashing to automatically manage the data placement. SeaweedFS places data by assigned volumes. +Ceph uses CRUSH hashing to automatically manage the data placement, which is efficient to locate the data. But the data has to be placed according to the CRUSH algorithm. Any wrong configuration would cause data loss. SeaweedFS places data by assigning them to any writable volumes. If writes to one volume failed, just pick another volume to write. Adding more volumes are also as simple as it can be. SeaweedFS is optimized for small files. Small files are stored as one continuous block of content, with at most 8 unused bytes between files. Small file access is O(1) disk read. -SeaweedFS Filer uses off-the-shelf stores, such as MySql, Postgres, Mongodb, Redis, Elastic Search, Cassandra, MemSql, TiDB, CockroachCB, Etcd, to manage file directories. These stores are proven, scalable, and easier to manage. +SeaweedFS Filer uses off-the-shelf stores, such as MySql, Postgres, Mongodb, Redis, Elastic Search, Cassandra, HBase, MemSql, TiDB, CockroachCB, Etcd, to manage file directories. These stores are proven, scalable, and easier to manage. | SeaweedFS | comparable to Ceph | advantage | | ------------- | ------------- | ---------------- | @@ -436,9 +442,7 @@ MinIO has specific requirements on storage layout. It is not flexible to adjust ## Dev Plan ## -* More tools and documentation, on how to manage and scale the system. For example, how to move volumes, automatically balancing data, how to grow volumes, how to check system status, etc. -* Integrate with Kubernetes. build [SeaweedFS Operator](https://github.com/seaweedfs/seaweedfs-operator). -* Add ftp server. +* More tools and documentation, on how to manage and scale the system. * Read and write stream data. * Support structured data. |