Chris LuandGitHub
88c873ecd4
* ec: uniform shard block layout An EC volume is striped as 1GiB blocks until less than one row remains, then 1MiB blocks, and consecutive blocks land on different shards. With ec.encode's -fullPercent 95 against the 30GiB default limit, ~30% of every volume sits in that 1MiB tail, so a 4MB filer chunk there is five stripes on five servers. New encodes now use one block per shard, sized ceil(datSize/dataShards) rounded up to 1MiB and recorded in the .vif (EcShardConfig.block_size, also carried by the .ecsum manifest). A needle now maps to one shard unless it is larger than the block or straddles a boundary. The chosen size equals the legacy layout's padded shard length for every input, so shard sizes, capacity math, and the shard-size credibility checks are unchanged; only the byte placement moved. Reads, decode, and scrub resolve the block sizes from the volume's .vif; absence keeps the legacy interpretation, so existing EC volumes read exactly as before. Rebuild is layout-agnostic. weed fix -ecx recovers the layout from the .vif, else the .ecsum sidecar, and with neither de-stripes under both candidate layouts and keeps the one that indexes more valid needles. Same change in the Rust volume server, which now also streams the encode in 256KB sub-batches like Go instead of allocating whole blocks, and computes the large-row count as shardSize/largeBlock to match Go on exact multiples. On a 26MB fixture both encoders produce byte-identical shards, and a Go-written .vif parses in Rust with the block size intact. * ec: resolve the rust ecx rebuild through the recorded layout The Rust rebuild path regenerated a lost .ecx by scanning the logical .dat through a hand-rolled pure-1MiB striping, which was already wrong for legacy volumes with large-block rows and is wrong for any uniform volume with a block past 1MiB. Route the scan through locate_data with the .vif-recorded block size, the same mapping the read path uses. Also seed the new tests' random data instead of the deprecated global math/rand.Read. * ec: fail the Rust ecx rebuild on any shard read error A read error mid-scan published the entries collected so far as a successful .ecx, and read_at's byte count was ignored so a legal short read passed as complete — a truncated or failing shard could produce a silently incomplete recovery index. Exact-read semantics in read_from_data_shards, error propagation in the needle walk, and a truncated-shard regression test. * ec: fail the mount on an unreadable or malformed vif Both servers silently fell back to the legacy layout when an existing .vif could not be read or parsed. Every new encode records a positive uniform block size there, so the fallback mounted the same shards with legacy offset math and could return wrong data. Absent stays legal (legacy volumes predate the sidecar), and a zero-byte stub still reads as absent (Go's MaybeLoadVolumeInfo convention, now mirrored in Rust); a present-but-unreadable or malformed .vif fails the mount instead. * ec: bound the reconstruct fan-out of one needle's intervals A degraded interval fans out a read to every reachable shard location, each with a buffer the size of the interval. Reading a needle's intervals in parallel multiplied that by the interval concurrency: a needle spanning 8 blocks could hold 8 x MaxShardCount remote reads and buffers at once, where the sequential version peaked at MaxShardCount. Give each needle a single reconstruct budget its intervals share, held for the buffer's lifetime, so separate reads stay independent but one read cannot multiply its own fan-out. * ec: drop the duplicated shard-size formula calculateExpectedShardSize reimplemented the padding rule that UniformBlockSize already owns — TestUniformBlockSizeMatchesLegacyShardSize asserts the two agree for every input — so a change to the rule would have had to be made in both. Defer to the helper, keeping the historic answer for an empty .dat. * ec: resolve the shard block layout from whatever records it Four places still answered the layout question by inference when a record of it was available, or accepted an answer that was not one: - A mount with no .vif defaulted to the legacy layout; the bitrot sidecar records the same config at encode time, so take it when present, as weed fix -ecx already does. The vif itself is now parsed once per mount rather than twice. - The Rust ecx rebuild derived its row count from the padded shard extent, which under the legacy layout reads a shard that is an exact large-block multiple as one row too many. Pass the encode-time .dat size from the .vif and keep the extent as the fallback. - weed fix -ecx read the block size outside the EC-config guard (collapsing the unknown sentinel into a definitive legacy), only wrote the recovered layout back when the .vif was absent rather than unusable, and broke a scan tie by candidate order instead of the documented reach. - The uniform layout tripped writeDatFile's large-block ambiguity guard, which cannot apply when the large and small blocks are the same size. * ec: give the index-recovery tests a parseable vif The fixtures wrote the literal bytes "volinfo" as the source .vif and the recovery copies it verbatim, so the receiving server then mounted the volume from a .vif it could not parse. That used to pass by silently defaulting to the legacy layout; a mount now refuses a vif it cannot read, which is what the tests were exercising all along without meaning to. * ec: validate the layout a vif records, not just its syntax Review follow-ups on the mount-strictness change: - A .vif can parse and still record a block size no encoder could have produced (negative, or not a whole number of small blocks). Both servers took it and mapped every read through it. ValidateBlockSize / the Rust mirror now refuse the mount, the same way an unparseable vif does; 0 stays valid as the legacy two-tier layout. - The bitrot-sidecar fallback accepted parity_shards == 0 and summed the counts in their own width, so values near the ceiling wrapped past the MaxShardCount bound. Require both counts and sum in a wider type. - weed fix -ecx treated a config with only DataShards > 0 as usable, so a half-written .vif suppressed the recovery paths AND survived the rewrite. Require a complete, in-range config before trusting it. - Returning the vif-load error left the .ecx and .ecj descriptors open; repeated mount attempts on malformed metadata could exhaust them. * ec: refuse to act on a layout the metadata does not establish - The worker encode only logged a failed .vif write and skipped it in the distribution set, and treated the .ecsum write as best-effort. A worker whose disk filled after the much larger shards landed could still distribute, mount, verify shard inventory, and delete the source replicas — leaving holders with shards whose geometry nothing records. Both writes and both inclusions are encode success conditions now. - A generation-matching .ecsum that disagreed with the .vif geometry only disabled checksums in Go, and in Rust was not compared at all, so protection stayed On while reads used the other layout. Both files record the layout their generation was encoded with, so a disagreement now fails the mount. * ec: reject an invalid recorded block size in weed fix -ecx A .vif with valid shard counts but a negative or unaligned block size was marked usable: a positive invalid value pinned the scan to a geometry that de-stripes to garbage, and a negative one ran the dual scan but left the invalid .vif in place afterwards. Validate it with the same rule the mount applies, and when it fails leave the layout unknown so the scan recovers it and the file is rewritten. * ec: validate the sidecar layout weed fix -ecx recovers from The .ecsum fallback was taken on DataShards > 0 alone, so a CRC-valid sidecar carrying the wrong generation, an incomplete ratio, or an unaligned block size would pin the reconstruction to one incorrect uniform-layout candidate instead of letting the dual scan decide. Require generation 0, a complete in-range ratio, and a valid block size; anything less leaves the layout unknown, which is the answer that still recovers by scanning. * ec: let only a genuinely absent sidecar choose the legacy layout With no .vif the bitrot sidecar is the only record of a volume's layout, and the mount fallback read a failed load, an unusable config, or a sidecar stamped for another generation as "assume legacy". A uniform generation-0 volume could therefore mount with legacy or another generation's geometry and answer reads with the wrong bytes. Present-but-unusable now fails the mount; only actual absence keeps the legacy defaults. Shared as EcShardConfigFromSidecar so every caller reads the sidecar the same way. * ec: treat a recorded-but-impossible layout as corruption, not as legacy - A .vif whose ecShardConfig is PRESENT but records an impossible ratio was answered with the default 10+4 and the legacy block layout, in both languages. That reads a uniform volume's shards at the wrong offsets and returns the wrong bytes. Only an entirely absent config still means "this predates the record"; a present one that cannot be true fails the mount. - The shard-count bound summed two uint32 counts as int, which wraps on a 32-bit build: 0x7fffffff + 0x7fffffff lands at -2 and slips under MaxShardCount. ValidEcShardCounts sums in uint64, and every EC call site that checked a recorded ratio now goes through it. * ec: rebuild on the geometry the sidecar records, and flag it when it disagrees The rebuild RPC passes BackgroundECContext, so RebuildEcFiles resolves the layout itself — and it resolved a missing or invalid .vif to the default 10+4 with the legacy block size. Two consequences: a 12+4 volume was reconstructed through a 10+4 matrix, which produces wrong bytes and never regenerates shards 14-15; and the chosen geometry then contradicted a valid uniform sidecar, which loadRebuildSidecar reported as BitrotOff — silently skipping the input and regenerated-shard checksum checks precisely when the volume had already lost its metadata. The layout now resolves from the bitrot sidecar (found across the server's disks, not just beside the base name) before falling back to the defaults, and a present-but-impossible ratio fails instead of being replaced. A sidecar that contradicts the chosen geometry is BitrotInvalid, which the existing unsafeIgnoreSidecar override still lets an operator push past. * ec: let the Rust rebuild read metadata off a sibling disk read_ec_shard_config searches only the location the rebuild writes into, so a volume whose .vif or generation-0 .ecsum sits on another of the server's disks resolved to the default 10+4 with the legacy block layout — the Rust half of the geometry-guessing the Go rebuild just stopped doing. It then reconstructs a custom-ratio or uniform volume through the wrong Reed-Solomon matrix and de-striping geometry. The rebuild now looks for the .vif in its own location and then each sibling, falls back to the generation-0 sidecar wherever that lives, and only defaults when neither exists anywhere. The encode-time .dat size the ecx rebuild needs is resolved the same way. * ec: resolve a rebuild's vif from every directory that may hold it RebuildEcFiles probed only <data-base>.vif. The caller knows the selected location's index directory and the sibling locations, but passed neither for metadata: additionalDirs carried shard directories only, and were searched for shards and the checksum sidecar. A split -dir/-dir.idx layout, or a disk holding only shards, therefore resolved a pre-sidecar custom-ratio volume to 10+4 and reconstructed through the wrong matrix — never regenerating shards 14-15. The caller now hands over the index and sibling directories, and the resolver probes the vif across all of them, matching what the Rust resolver already does for both the vif and the sidecar. * ec: make every rebuild consumer agree on the layout it resolved - The post-rebuild bitrot backfill re-derived the geometry from this directory's .vif alone and dropped the block size entirely, so a rebuild that resolved its layout from a sibling, the sidecar, or a uniform vif wrote a manifest describing a DIFFERENT layout — one later mounts reject, or that covers only the default shard count. The layout is resolved once now, through an exported ResolveRebuildECContext, and the rebuild and the backfill share that answer. - The Rust rebuild collected only each location's data directory, so a sibling's INDEX directory — where a split -dir/-dir.idx layout keeps .ecx/.ecj/.vif — was never probed, and a custom-ratio volume still resolved to 10+4 with the legacy layout. Both directories of every location are carried now, deduped against the rebuild's own. - A shard delivery can bring the checksum manifest with it, but the receive path only writes the file: a server that already had the volume mounted kept its resolved protection state (off) until a remount. The mount RPC re-resolves it once the shards it describes have been added. * ec: cover the rebuild's directory search with tests Reviewers flagged the sibling index directory twice, and the fix that closed it had no test of its own: the assembly sat inline in the rebuild handler, reachable only through a gRPC call against a populated store. Lifting it into rebuildSearchDirs / select_rebuild_location makes the rule assertable — a sibling contributes BOTH its data and its index directory, a shared index directory is listed once, and the rebuild's own data directory never repeats. Writing the Rust cases surfaced that the two implementations do not agree on where the rebuild's own index directory belongs, and both are right: Go's resolver takes a single directory list, so that directory has to be inside it, while Rust's takes the rebuild's data and index directories as their own arguments and would search them twice. The tests now state which contract each side is holding to, so neither drifts into the other's shape. Pure refactor otherwise; no behaviour change. * ec: search the index directory for the layout sidecar The Rust resolver looked for the generation-0 .ecsum in the rebuild's data directory and the sibling list, but not in the rebuild's own index directory — while the .vif lookup directly above it did, and Go's findBitrotSidecar has always checked both bases. On a split -dir/-dir.idx location that directory is where the metadata lives, and callers leave it out of the sibling list precisely because it is passed here separately, so nothing searched it. With no .vif anywhere the sidecar is the only surviving record of the layout. Missing it resolved a 12+4 uniform volume to 10+4 with the legacy striping — the test added here fails with (10, 4, 0) against the old code — and the rebuild then reconstructs through the wrong matrix and writes .ecx offsets that no reader can follow. * ec: let the rebuild see its own index directory The Rust rebuild takes a single flat directory list — the shape Go's RebuildEcFiles uses — so it cannot be handed the rebuild location's index directory separately the way the layout resolvers are, and the handler was passing the sibling list, which deliberately omits exactly that directory. On a split -dir/-dir.idx location that is where .ecx and .vif live, so the shard and index lookups could not see them. Go has always carried that directory in additionalDirs; this lines the two call sites up. * ec: let a config-free vif fall through to the layout sidecar A .vif that carries no ecShardConfig answers nothing about the layout, so it is no more informative than an absent one — but both trees treated its mere existence as the end of the search. Go went straight to the 10+4 legacy defaults without consulting the sidecar at all; Rust returned whatever ec_shard_config_from could make of a single directory. A 12+4 uniform volume with a legacy config-free vif therefore resolved as 10+4 legacy, and every read landed at the wrong shard offset. The sidecar lookup was also single-directory on both sides, while a split -dir/-dir.idx layout keeps .vif and .ecsum with the INDEX. Go's findBitrotSidecar has always taken both bases; the callers here passed only the data base, and the Rust bitrot resolver derived its path from the data base alone. Rust's layout resolver now takes a candidate directory list — data, index, then any siblings — and searches all of it, which also removes the early return that made the vif's presence decisive. load_vif_info_across_dirs reported `dir` even when load_vif_info had found the vif in `dir_idx`. Nothing reads that field today, so this changes no behaviour; it stops the next caller that resolves the rest of the volume's metadata against the answer from being sent to a disk holding none of it. Absence stays legal throughout: a volume with neither record is genuinely legacy. Present-but-unusable still fails the mount, now in the config-free-vif branch too. * ec: activate a delivered sidecar on every per-disk runtime A vid mounts as one EcVolume per disk, each with its own resolved protection state, but the post-delivery reload used the first-match lookup and so touched exactly one of them. The siblings kept reporting no protection until a remount — and since shard distribution deduplicates the metadata files onto the first target disk for a node, the runtime that got the .ecsum is not necessarily the one the lookup returns. Iterate every runtime instead, via a new FindAllEcVolumes and its Rust mut equivalent. Combined with each runtime now resolving its sidecar against its index directory as well as its data directory, a server sharing one -dir.idx across its disks activates all of them from the single delivered copy. The Rust volume server had no post-mount reload at all; it gets one here, matching Go. * ec: resolve the delivered sidecar across every EC metadata directory Reloading every per-disk runtime, added last round, did not by itself make the delivered manifest reachable. Startup mirroring copies .ecx/.ecj/.vif to every shard-bearing disk so each mounts self-contained, but deliberately not .ecsum, and a repair delivers exactly one copy. Each runtime was resolving against its own two directories, so every sibling of the disk that received the file kept reporting no protection however often it reloaded. Resolve one authoritative copy across every EC metadata directory instead of duplicating the file. Mirroring .ecsum would have to keep pace with a file that is rewritten as shards are repaired, and would not help the reported case at all: the delivery happens at runtime, and mirroring only runs at startup. The regression test pins both halves — a reload restricted to the volume's own directories still finds nothing, and the same reload given the server's metadata directories turns protection on. * ec: ask every directory before writing a TOFU baseline After a rebuild the opportunistic backfill asks whether this volume already has a checksum manifest, and answered from the data base alone. A split -dir/-dir.idx layout keeps the sidecar with the index, and a multi-disk server may keep it on a sibling, so an existing manifest read as absent. The consequence is worse than a missed read. On a false "no" the backfill writes a fresh sidecar at the data base from whatever the shards say right now — and the data base is the first candidate every resolver checks, so that TOFU baseline shadows the real manifest rather than sitting beside it. A shard that was silently corrupt gets blessed, and the record that would have caught it stops being consulted. FindBitrotSidecar exports the search the package already used internally, so the question is asked of the data base, the index base and the sibling disks — the same candidates the rebuild resolves its layout from. * ec: refuse a shard block size no encoder could have produced weed fix -ecx derived one from the raw shard extent, so a truncated or partially copied shard wrote a .vif that NewEcVolume then permanently refuses — the volume the tool was run to rescue could never mount again. An extent that is not a whole number of small blocks cannot have come from a uniform encode, so it is no longer offered as a candidate, and nothing unvalidated reaches the .vif. Claude-Session: https://claude.ai/code/session_011FRRoNKBiGbH58rs2AQyA7 * ec: derive the .vif's dat size and block size from one measurement VolumeEcShardsGenerate stat'ed the .dat before the encode while WriteEcFiles stat'ed it again to size the blocks. A write landing between the two produced a .vif whose own two fields describe different files. WriteEcFiles now leaves both on the context, and fills a placeholder context in place so the caller can read them back. Claude-Session: https://claude.ai/code/session_011FRRoNKBiGbH58rs2AQyA7 * ec: keep the source volume until every holder serves its shard layout The uniform layout rides in a .vif field older volume servers never knew: they discard it, mount the shards as legacy and return wrong bytes with nothing erroring, and the shard files are the same length either way so no other check notices. The upgrade order lived only in the release note. VolumeEcShardsInfo now reports the block size the holder actually serves, in both the Go and Rust servers, and the pre-delete verification refuses to drop the source unless every reachable holder echoes the one the shards were encoded with — while a rollback still exists. A server that predates the field answers 0, which is the negative answer. Claude-Session: https://claude.ai/code/session_011FRRoNKBiGbH58rs2AQyA7 * ec: drop the rebuild's dead block-size parameters generateMissingEcFiles never reads largeBlockSize/smallBlockSize — Reed-Solomon reconstruction is layout-agnostic — so passing the legacy constants only advertised a layout the rebuild does not use. Also move UniformBlockSize's doc off ValidateBlockSize. Claude-Session: https://claude.ai/code/session_011FRRoNKBiGbH58rs2AQyA7 * ec: warn about EC defaults only when the mount used them The "vif file not found, using defaults" warning fired even after the bitrot sidecar supplied a non-default layout, sending anyone triaging wrong bytes after the legacy layout the volume never mounted on. Claude-Session: https://claude.ai/code/session_011FRRoNKBiGbH58rs2AQyA7 * ec: stat the distributed bitrot sidecar once The strict check re-stat'ed the file immediately before the stat that already gates inclusion, and a failed sidecar write now fails the encode outright, so the first could only fire on a deletion between the two lines. Claude-Session: https://claude.ai/code/session_011FRRoNKBiGbH58rs2AQyA7 * ec: say what the reconstruct budget actually bounds A shard's buffer stays in bufs until its interval reconstructs, which is after the read that filled it released its permit, so the semaphore bounds round trips in flight and not retained bytes. Peak memory is the intervals reconstructing at once times the shards each reaches times the interval size. Claude-Session: https://claude.ai/code/session_011FRRoNKBiGbH58rs2AQyA7 * test: let the fake volume server report its delivered EC layout The pre-delete verification now asks each holder which shard block layout it serves, and a fake that always answered "unset" looked exactly like a volume server too old to know the field. Distribution ships the .vif to every holder alongside its shards, so read the layout back out of it as a real holder does. Claude-Session: https://claude.ai/code/session_011FRRoNKBiGbH58rs2AQyA7
SeaweedFS
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Table of Contents
- Quick Start
- Introduction
- Features
- Example: Using Seaweed Blob Store
- Architecture
- Compared to Other File Systems
- Dev Plan
- Installation Guide
- Disk Related Topics
- Benchmark
- Enterprise
- License
Quick Start
Quick Start with weed mini
Download the latest binary from https://github.com/seaweedfs/seaweedfs/releases and unzip the single weed (or weed.exe) file, or run go install github.com/seaweedfs/seaweedfs/weed@latest. Then start a ready-to-use S3 object store with credentials and a pre-created bucket in one command:
AWS_ACCESS_KEY_ID=admin \
AWS_SECRET_ACCESS_KEY=secret \
S3_BUCKET=my-bucket \
./weed mini -dir=/data
That's it — the S3 endpoint is at http://localhost:8333, my-bucket already exists, and admin/secret are valid credentials. S3_BUCKET accepts a comma-separated list (e.g. raw,processed); use S3_TABLE_BUCKET for S3 Tables buckets, each name or name:FORMAT where the format is ICEBERG (the default) or LANCE. Drop any of the env vars to skip that piece (no AWS keys → S3 runs in unauthenticated "Allow All" mode for development).
The same command starts everything else too:
- S3 Endpoint: http://localhost:8333
- Master UI: http://localhost:9333
- Volume Server: http://localhost:9340
- Filer UI: http://localhost:8888
- WebDAV: http://localhost:7333
- Admin UI: http://localhost:23646
macOS: if the binary is quarantined, run
xattr -d com.apple.quarantine ./weedfirst.
Perfect for development, testing, learning SeaweedFS, and single-node deployments. To scale out, add more volume servers by running weed volume -dir="/some/data/dir2" -master="<master_host>:9333" -port=8081 locally, on another machine, or on thousands of machines.
Quick Start for S3 API on Docker
docker run -p 8333:8333 \
-e AWS_ACCESS_KEY_ID=admin \
-e AWS_SECRET_ACCESS_KEY=secret \
-e S3_BUCKET=my-bucket \
chrislusf/seaweedfs
Same behavior as the weed mini command above — the S3 endpoint is at http://localhost:8333 with my-bucket pre-created. Drop the env vars to run anonymously for development.
Introduction
SeaweedFS is a simple and highly scalable distributed file system. There are two objectives:
- to store billions of files!
- to serve the files fast!
SeaweedFS started as a blob 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).
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. Also, SeaweedFS implements erasure coding with ideas from f4: Facebook’s Warm BLOB Storage System, and has a lot of similarities with Facebook’s Tectonic Filesystem and Google's Colossus File System
On top of the blob 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, Sqlite, MemSql, TiDB, Etcd, CockroachDB, YDB, etc.
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!
SeaweedFS also ships a built-in Iceberg REST Catalog, turning the same cluster into a self-contained lakehouse. Spark, Trino, Dremio, DuckDB, and RisingWave can query Iceberg tables directly — no Hive Metastore, Glue, or external catalog service required. Storage and table metadata live in one system, simplifying on-prem and small-team analytics stacks.
Features
Additional Blob Store Features
- Support different replication levels, with rack and data center aware.
- Automatic master servers failover - no single point of failure (SPOF).
- Automatic compression depending on file MIME type.
- Automatic compaction to reclaim disk space after deletion or update.
- Automatic entry TTL expiration.
- Flexible Capacity Expansion: Any server with some disk space can add to the total storage space.
- Adding/Removing servers does not cause any data re-balancing unless triggered by admin commands.
- Optional picture resizing.
- Support ETag, Accept-Range, Last-Modified, etc.
- Support in-memory/leveldb/readonly mode tuning for memory/performance balance.
- Support rebalancing the writable and readonly volumes.
- Customizable Multiple Storage Tiers: Customizable storage disk types to balance performance and cost.
- Transparent cloud integration: unlimited capacity via tiered cloud storage for warm data.
- Erasure Coding for warm storage Rack-Aware 10.4 erasure coding reduces storage cost and increases availability. Enterprise version can customize EC ratio.
Filer Features
- Filer server provides "normal" directories and files via HTTP.
- File TTL automatically expires file metadata and actual file data.
- Mount filer reads and writes files directly as a local directory via FUSE.
- Filer Store Replication enables HA for filer meta data stores.
- Active-Active Replication enables asynchronous one-way or two-way cross cluster continuous replication.
- Amazon S3 compatible API accesses files with S3 tooling.
- Hadoop Compatible File System accesses files from Hadoop/Spark/Flink/etc or even runs HBase.
- Async Replication To Cloud has extremely fast local access and backups to Amazon S3, Google Cloud Storage, Azure, BackBlaze.
- WebDAV accesses as a mapped drive on Mac and Windows, or from mobile devices.
- AES256-GCM Encrypted Storage safely stores the encrypted data.
- Super Large Files stores large or super large files in tens of TB.
- Cloud Drive mounts cloud storage to local cluster, cached for fast read and write with asynchronous write back.
- Gateway to Remote Object Store mirrors bucket operations to remote object storage, in addition to Cloud Drive
Data Lakehouse Features
- S3 Table Buckets expose a dedicated namespace for Iceberg tables with strict layout validation.
- Built-in Iceberg REST Catalog runs alongside the S3 endpoint — no external metastore needed.
- Native integrations with Apache Spark, Trino, Dremio, DuckDB, and RisingWave.
- Automated table maintenance: compaction, snapshot expiration, orphan removal, manifest rewriting.
- Granular IAM at the bucket, namespace, and table level via standard S3 bucket policies.
Kubernetes
- Kubernetes CSI Driver A Container Storage Interface (CSI) Driver.
- SeaweedFS Operator
Example: Using Seaweed Blob Store
By default, the master node runs on port 9333, and the volume nodes run on port 8080. Let's start one master node, and two volume nodes on port 8080 and 8081. Ideally, they should be started from different machines. We'll use localhost as an example.
SeaweedFS uses HTTP REST operations to read, write, and delete. The responses are in JSON or JSONP format.
Start Master Server
> ./weed master
Start Volume Servers
> weed volume -dir="/tmp/data1" -max=5 -master="localhost:9333" -port=8080 &
> weed volume -dir="/tmp/data2" -max=10 -master="localhost:9333" -port=8081 &
Write A Blob
A blob, also referred as a needle, a chunk, or mistakenly as a file, is just a byte array. It can have attributes, such as name, mime type, create or update time, etc. But basically it is just a byte array of a relatively small size, such as 2 MB ~ 64 MB. The size is not fixed.
To upload a blob: first, send a HTTP POST, PUT, or GET request to /dir/assign to get an fid and a volume server URL:
> curl http://localhost:9333/dir/assign
{"count":1,"fid":"3,01637037d6","url":"127.0.0.1:8080","publicUrl":"localhost:8080"}
Second, to store the blob content, send a HTTP multi-part POST request to url + '/' + fid from the response:
> curl -F file=@/home/chris/myphoto.jpg http://127.0.0.1:8080/3,01637037d6
{"name":"myphoto.jpg","size":43234,"eTag":"1cc0118e"}
To update, send another POST request with updated blob content.
For deletion, send an HTTP DELETE request to the same url + '/' + fid URL:
> curl -X DELETE http://127.0.0.1:8080/3,01637037d6
Save Blob Id
Now, you can save the fid, 3,01637037d6 in this case, to a database field.
The number 3 at the start represents a volume id. After the comma, it's one file key, 01, and a file cookie, 637037d6.
The volume id is an unsigned 32-bit integer. The file key is an unsigned 64-bit integer. The file cookie is an unsigned 32-bit integer, used to prevent URL guessing.
The file key and file cookie are both coded in hex. You can store the <volume id, file key, file cookie> tuple in your own format, or simply store the fid as a string.
If stored as a string, in theory, you would need 8+1+16+8=33 bytes. A char(33) would be enough, if not more than enough, since most uses will not need 2^32 volumes.
If space is really a concern, you can store the file id in the binary format. You would need one 4-byte integer for volume id, 8-byte long number for file key, and a 4-byte integer for the file cookie. So 16 bytes are more than enough.
Read a Blob
Here is an example of how to render the URL.
First look up the volume server's URLs by the file's volumeId:
> curl http://localhost:9333/dir/lookup?volumeId=3
{"volumeId":"3","locations":[{"publicUrl":"localhost:8080","url":"localhost:8080"}]}
Since (usually) there are not too many volume servers, and volumes don't move often, you can cache the results most of the time. Depending on the replication type, one volume can have multiple replica locations. Just randomly pick one location to read.
Now you can take the public URL, render the URL or directly read from the volume server via URL:
http://localhost:8080/3,01637037d6.jpg
Notice we add a file extension ".jpg" here. It's optional and just one way for the client to specify the file content type.
If you want a nicer URL, you can use one of these alternative URL formats:
http://localhost:8080/3/01637037d6/my_preferred_name.jpg
http://localhost:8080/3/01637037d6.jpg
http://localhost:8080/3,01637037d6.jpg
http://localhost:8080/3/01637037d6
http://localhost:8080/3,01637037d6
If you want to get a scaled version of an image, you can add some params:
http://localhost:8080/3/01637037d6.jpg?height=200&width=200
http://localhost:8080/3/01637037d6.jpg?height=200&width=200&mode=fit
http://localhost:8080/3/01637037d6.jpg?height=200&width=200&mode=fill
Rack-Aware and Data Center-Aware Replication
SeaweedFS applies the replication strategy at a volume level. So, when you are getting a blob id, you can specify the replication strategy. For example:
curl http://localhost:9333/dir/assign?replication=001
The replication parameter options are:
000: no replication
001: replicate once on the same rack
010: replicate once on a different rack, but same data center
100: replicate once on a different data center
200: replicate twice on two different data center
110: replicate once on a different rack, and once on a different data center
More details about replication can be found on the wiki.
You can also set the default replication strategy when starting the master server.
Allocate Blob Key on Specific Data Center
Volume servers can be started with a specific data center name:
weed volume -dir=/tmp/1 -port=8080 -dataCenter=dc1
weed volume -dir=/tmp/2 -port=8081 -dataCenter=dc2
When requesting a blob key, an optional "dataCenter" parameter can limit the assigned volume to the specific data center. For example, this specifies that the assigned volume should be limited to 'dc1':
http://localhost:9333/dir/assign?dataCenter=dc1
Other Features
- No Single Point of Failure
- Insert with your own keys
- Chunking large files
- Collection as a Simple Name Space
Blob Store Architecture
Usually distributed file systems split each file into chunks. A central server keeps a mapping of filenames to chunks, and also which chunks each chunk server has.
The main drawback is that the central server can't handle many small files efficiently, and since all read requests need to go through the central master, so it might not scale well for many concurrent users.
Instead of managing chunks, SeaweedFS manages data volumes in the master server. Each data volume is 32GB in size, and can hold a lot of blobs. And each storage node can have many data volumes. So the master node only needs to store the metadata about the volumes, which is a fairly small amount of data and is generally stable.
The actual blob metadata, which are the blob volume, offset, and size, is stored in each volume on volume servers. Since each volume server only manages metadata of blobs on its own disk, with only 16 bytes for each blob, all access can read the metadata just from memory and only needs one disk operation to actually read file data.
For comparison, consider that an xfs inode structure in Linux is 536 bytes.
Master Server and Volume Server
The architecture is fairly simple. The actual data is stored in volumes on storage nodes. One volume server can have multiple volumes, and can both support read and write access with basic authentication.
All volumes are managed by a master server. The master server contains the volume id to volume server mapping. This is fairly static information, and can be easily cached.
On each write request, the master server also generates a file key, which is a growing 64-bit unsigned integer. Since write requests are not generally as frequent as read requests, one master server should be able to handle the concurrency well.
Write and Read files
When a client sends a write request, the master server returns (volume id, file key, file cookie, volume node URL) for the blob. The client then contacts the volume node and POSTs the blob content.
When a client needs to read a blob based on (volume id, file key, file cookie), it asks the master server by the volume id for the (volume node URL, volume node public URL), or retrieves this from a cache. Then the client can GET the content, or just render the URL on web pages and let browsers fetch the content.
Saving memory
All blob metadata stored on a volume server is readable from memory without disk access. Each file takes just a 16-byte map entry of <64bit key, 32bit offset, 32bit size>. Of course, each map entry has its own space cost for the map. But usually the disk space runs out before the memory does.
Tiered Storage to the cloud
The local volume servers are much faster, while cloud storages have elastic capacity and are actually more cost-efficient if not accessed often (usually free to upload, but relatively costly to access). With the append-only structure and O(1) access time, SeaweedFS can take advantage of both local and cloud storage by offloading the warm data to the cloud.
Usually hot data are fresh and warm data are old. SeaweedFS puts the newly created volumes on local servers, and optionally upload the older volumes on the cloud. If the older data are accessed less often, this literally gives you unlimited capacity with limited local servers, and still fast for new data.
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.
SeaweedFS Filer
Built on top of the blob store, SeaweedFS Filer adds directory structure to create a file system. The directory structure is an interface that is implemented in many key-value stores or databases.
The content of a file is mapped to one or many blobs, distributed to multiple volumes on multiple volume servers.
Compared to Other File Systems
Most other distributed file systems seem more complicated than necessary.
SeaweedFS is meant to be fast and simple, in both setup and operation. If you do not understand how it works when you reach here, we've failed! Please raise an issue with any questions or update this file with clarifications.
SeaweedFS is constantly moving forward. Same with other systems. These comparisons can be outdated quickly. Please help to keep them updated.
Compared to HDFS
HDFS uses the chunk approach for each file, and is ideal for storing large files.
SeaweedFS is ideal for serving relatively smaller files quickly and concurrently.
SeaweedFS can also store extra large files by splitting them into manageable data chunks, and store the file ids of the data chunks into a meta chunk. This is managed by "weed upload/download" tool, and the weed master or volume servers are agnostic about it.
Compared to GlusterFS, Ceph
The architectures are mostly the same. SeaweedFS aims to store and read files fast, with a simple and flat architecture. The main differences are
- 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 store, e.g., Redis, Cassandra, HBase, Mongodb, Elastic Search, MySql, Postgres, Sqlite, MemSql, TiDB, CockroachDB, Etcd, YDB etc, and is easy to customize.
- 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 |
|---|---|---|---|---|---|
| SeaweedFS | lookup volume id, cacheable | O(1) disk seek | Yes | Yes | |
| SeaweedFS Filer | Linearly Scalable, Customizable | O(1) disk seek | FUSE | Yes | Yes |
| GlusterFS | hashing | FUSE, NFS | |||
| Ceph | hashing + rules | FUSE | Yes | ||
| MooseFS | in memory | FUSE | No | ||
| MinIO | separate meta file per drive for each file | Yes | No | ||
| RustFS | separate meta file per drive for each file | Yes | No |
Compared to GlusterFS
GlusterFS stores files, both directories and content, in configurable volumes called "bricks".
GlusterFS hashes the path and filename into ids, and assigned to virtual volumes, and then mapped to "bricks".
Compared to MooseFS
MooseFS chooses to neglect small file issue. From moosefs 3.0 manual, "even a small file will occupy 64KiB plus additionally 4KiB of checksums and 1KiB for the header", because it "was initially designed for keeping large amounts (like several thousands) of very big files"
MooseFS Master Server keeps all meta data in memory. Same issue as HDFS namenode.
Compared to Ceph
Ceph can be setup similar to SeaweedFS as a key->blob store. It is much more complicated, with the need to support layers on top of it. Here is a more detailed comparison
SeaweedFS has a centralized master group to look up free volumes, while Ceph uses hashing and metadata servers to locate its objects. Having a centralized master makes it easy to code and manage.
Ceph, like SeaweedFS, is based on the object store RADOS. Ceph is rather complicated with mixed reviews.
Ceph uses CRUSH hashing to automatically manage 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. Topology changes, such as adding new servers to increase capacity, will cause data migration with high IO cost to fit the CRUSH algorithm. 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 is 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, Sqlite, Mongodb, Redis, Elastic Search, Cassandra, HBase, MemSql, TiDB, CockroachCB, Etcd, YDB, to manage file directories. These stores are proven, scalable, and easier to manage.
| SeaweedFS | comparable to Ceph | advantage |
|---|---|---|
| Master | MDS | simpler |
| Volume | OSD | optimized for small files |
| Filer | Ceph FS | linearly scalable, Customizable, O(1) or O(logN) |
Compared to MinIO, RustFS
Please note, as Apr 25, 2026 MinIO ceased development. It's strongly discouraged to use that unmaintained software with multiple security bugs. RustFS is a MinIO reimplementation in Rust, Apache 2.0 licensed and still developed, keeping MinIO's storage model down to a byte-compatible on-disk format. So the points below apply to both.
MinIO followed AWS S3 closely and was ideal for testing for S3 API. It had good UI, policies, versionings, etc. SeaweedFS is trying to catch up here.
The metadata are in simple files. Each file write incurs extra writes to the corresponding meta file, on every drive of the erasure set. Changing only tags or retention rewrites that meta file on all of them, so the write amplification does not shrink with object size.
There is no optimization for lots of small files. The files are simply stored as is to local disks. Plus the extra meta file and shards for erasure coding, it only amplifies the LOSF problem.
Multiple disk IO are needed to read one file. SeaweedFS has O(1) disk reads, even for erasure coded files.
Erasure coding is full-time. SeaweedFS uses replication on hot data for faster speed and optionally applies erasure coding on warm data.
No POSIX-like API support.
There are specific requirements on storage layout, which makes it hard to scale out and to maintain. An erasure set must be 2 to 16 drives and must divide the drive list symmetrically, and capacity grows or shrinks a whole pool at a time. In SeaweedFS, just start one volume server pointing to the master. That's all.
Dev Plan
- More tools and documentation, on how to manage and scale the system.
- Read and write stream data.
- Support structured data.
This is a super exciting project! And we need helpers and support!
Installation Guide
Installation guide for users who are not familiar with golang
Step 1: install go on your machine and setup the environment by following the instructions at:
https://golang.org/doc/install
make sure to define your $GOPATH
Step 2: checkout this repo:
git clone https://github.com/seaweedfs/seaweedfs.git
Step 3: download, compile, and install the project by executing the following command
cd seaweedfs/weed && make install
Once this is done, you will find the executable "weed" in your $GOPATH/bin directory
For more installation options, including how to run with Docker, see the Getting Started guide.
Disk Related Topics
Hard Drive Performance
When testing read performance on SeaweedFS, it basically becomes a performance test of your hard drive's random read speed. Hard drives usually get 100MB/s~200MB/s.
Solid State Disk
To modify or delete small files, SSD must delete a whole block at a time, and move content in existing blocks to a new block. SSD is fast when brand new, but will get fragmented over time and you have to garbage collect, compacting blocks. SeaweedFS is friendly to SSD since it is append-only. Deletion and compaction are done on volume level in the background, not slowing reading and not causing fragmentation.
Benchmark
My Own Unscientific Single Machine Results on Mac Book with Solid State Disk, CPU: 1 Intel Core i7 2.6GHz.
Write 1 million 1KB file:
Concurrency Level: 16
Time taken for tests: 66.753 seconds
Completed requests: 1048576
Failed requests: 0
Total transferred: 1106789009 bytes
Requests per second: 15708.23 [#/sec]
Transfer rate: 16191.69 [Kbytes/sec]
Connection Times (ms)
min avg max std
Total: 0.3 1.0 84.3 0.9
Percentage of the requests served within a certain time (ms)
50% 0.8 ms
66% 1.0 ms
75% 1.1 ms
80% 1.2 ms
90% 1.4 ms
95% 1.7 ms
98% 2.1 ms
99% 2.6 ms
100% 84.3 ms
Randomly read 1 million files:
Concurrency Level: 16
Time taken for tests: 22.301 seconds
Completed requests: 1048576
Failed requests: 0
Total transferred: 1106812873 bytes
Requests per second: 47019.38 [#/sec]
Transfer rate: 48467.57 [Kbytes/sec]
Connection Times (ms)
min avg max std
Total: 0.0 0.3 54.1 0.2
Percentage of the requests served within a certain time (ms)
50% 0.3 ms
90% 0.4 ms
98% 0.6 ms
99% 0.7 ms
100% 54.1 ms
Run WARP and launch a mixed benchmark.
make benchmark
warp: Benchmark data written to "warp-mixed-2025-12-05[194844]-kBpU.csv.zst"
Mixed operations.
Operation: DELETE, 10%, Concurrency: 20, Ran 42s.
* Throughput: 55.13 obj/s
Operation: GET, 45%, Concurrency: 20, Ran 42s.
* Throughput: 2477.45 MiB/s, 247.75 obj/s
Operation: PUT, 15%, Concurrency: 20, Ran 42s.
* Throughput: 825.85 MiB/s, 82.59 obj/s
Operation: STAT, 30%, Concurrency: 20, Ran 42s.
* Throughput: 165.27 obj/s
Cluster Total: 3302.88 MiB/s, 550.51 obj/s over 43s.
Enterprise
For enterprise users, please visit seaweedfs.com for the SeaweedFS Enterprise Edition, which has advanced features, including data recovery, self-healing storage, customizable erasure coding, EC vacuum and repair, etc.
License
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.
The text of this page is available for modification and reuse under the terms of the Creative Commons Attribution-Sharealike 3.0 Unported License and the GNU Free Documentation License (unversioned, with no invariant sections, front-cover texts, or back-cover texts).
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