Chris LuandGitHub
9e06e1d0f9
* s3tables: report a delete the filer rejected deleteDirectory discarded DeleteEntryResponse and checked only the transport error, so DeleteTable, DeleteNamespace, DeleteView and DeleteTableBucket answered 200 for a delete the filer refused. Call filer_pb.DoRemove, which reads resp.Error and still treats a missing entry as success. Claude-Session: https://claude.ai/code/session_01BjDWtZsCoZY6x4pdDmGWxU * admin: report a delete the filer rejected The bucket delete, the file browser handlers and the topic retention purger all discarded DeleteEntryResponse, so a delete the filer refused came back as success. Call filer_pb.DoRemove, which reads resp.Error. Claude-Session: https://claude.ai/code/session_01BjDWtZsCoZY6x4pdDmGWxU * credential: report a delete the filer rejected DeleteUser, DeletePolicy and the full-sync cleanup loops discarded DeleteEntryResponse, so a rejected delete answered success and left the credential file in place. The service account path in the same store already read resp.Error; the rest now do too, via filer_pb.DoRemove where not-found is already tolerated. Claude-Session: https://claude.ai/code/session_01BjDWtZsCoZY6x4pdDmGWxU * shell: report a delete the filer rejected remote.configure -delete, remote.cache and the remote metadata sync discarded DeleteEntryResponse, so a rejected delete printed as removed. Call filer_pb.DoRemove, which reads resp.Error. Claude-Session: https://claude.ai/code/session_01BjDWtZsCoZY6x4pdDmGWxU * mq: report a delete the filer rejected The consumer offset group purge and the coordinator assignment delete discarded DeleteEntryResponse. Call filer_pb.DoRemove, which reads resp.Error. Claude-Session: https://claude.ai/code/session_01BjDWtZsCoZY6x4pdDmGWxU * iam: count only the revocation entries the filer actually deleted The expiry sweep discarded DeleteEntryResponse, so a rejected delete was counted as purged and the entry stayed. Call filer_pb.DoRemove, which reads resp.Error, matching the role and provider stores beside it. Claude-Session: https://claude.ai/code/session_01BjDWtZsCoZY6x4pdDmGWxU * mount: fail rmdir when the unary fallback delete was rejected The streaming branch turns DeleteEntryResponse.Error into an error, the unary fallback dropped it, so rmdir of a non-empty directory answered OK off the stream and ENOTEMPTY on it. Surface it in both. Claude-Session: https://claude.ai/code/session_01BjDWtZsCoZY6x4pdDmGWxU * s3tables: fail DeleteTableBucket when the directory delete is refused The handler only failed when both the leaf entry and the directory delete failed, so a refused bucket directory delete still answered 200 with the bucket in place. The directory is the bucket, so it decides; the leaf entry stays best-effort. Claude-Session: https://claude.ai/code/session_01BjDWtZsCoZY6x4pdDmGWxU
SeaweedMQ Message Queue on SeaweedFS (WIP, not ready)
What are the use cases it is designed for?
Message queues are like water pipes. Messages flow in the pipes to their destinations.
However, what if a flood comes? Of course, you can increase the number of partitions, add more brokers, restart, and watch the traffic level closely.
Sometimes the flood is expected. For example, backfill some old data in batch, and switch to online messages. You may want to ensure enough brokers to handle the data and reduce them later to cut cost.
SeaweedMQ is designed for use cases that need to:
- Receive and save large number of messages.
- Handle spike traffic automatically.
What is special about SeaweedMQ?
- Separate computation and storage nodes to scale independently.
- Unlimited storage space by adding volume servers.
- Unlimited message brokers to handle incoming messages.
- Offline messages can be operated as normal files.
- Scale up and down with auto split and merge message topics.
- Topics can automatically split into segments when traffic increases, and vice verse.
- Pass messages by reference instead of copying.
- Clients can optionally upload the messages first and just submit the references.
- Drastically reduce the broker load.
- Stateless brokers
- All brokers are equal. One broker is dynamically picked as the leader.
- Add brokers at any time.
- Allow rolling restart brokers or remove brokers at a pace.
Design
How it works?
Brokers are just computation nodes without storage. When a broker starts, it reports itself to masters. Among all the brokers, one of them will be selected as the leader by the masters.
A topic needs to define its partition key on its messages.
Messages for a topic are divided into segments. One segment can cover a range of partitions. A segment can be split into 2 segments, or 2 neighboring segments can be merged back to one segment.
During write time, the client will ask the broker leader for a few brokers to process the segment.
The broker leader will check whether the segment already has assigned the brokers. If not, select a few brokers based on their loads, save the selection into filer, and tell the client.
The client will write the messages for this segment to the selected brokers.
Failover
The broker leader does not contain any state. If it fails, the masters will select a different broker.
For a segment, if any one of the selected brokers is down, the remaining brokers should try to write received messages to the filer, and close the segment to the clients.
Then the clients should start a new segment. The masters should assign other healthy brokers to handle the new segment.
So any brokers can go down without losing data.
Auto Split or Merge
(The idea is learned from Pravega.)
The brokers should report its traffic load to the broker leader periodically.
If any segment has too much load, the broker leader will ask the brokers to tell the client to close current one and create two new segments.
If 2 neighboring segments have the combined load below average load per segment, the broker leader will ask the brokers to tell the client to close this 2 segments and create a new segment.