chrislu
e2722045a4
CRITICAL FIX: Implement proper JoinGroup request parsing and consumer subscription extraction ## Issues Fixed: - JoinGroup was ignoring protocol type and group protocols from requests - Consumer subscription extraction was hardcoded to 'test-topic' - Protocol metadata parsing was completely stubbed out - Group instance ID for static membership was not parsed ## JoinGroup Request Parsing: - Parse Protocol Type (string) - validates consumer vs producer protocols - Parse Group Protocols array with: - Protocol name (range, roundrobin, sticky, etc.) - Protocol metadata (consumer subscriptions, user data) - Parse Group Instance ID (nullable string) for static membership (Kafka 2.3+) - Added comprehensive debug logging for all parsed fields ## Consumer Subscription Extraction: - Implement proper consumer protocol metadata parsing: - Version (2 bytes) - protocol version - Topics array (4 bytes count + topic names) - actual subscriptions - User data (4 bytes length + data) - client metadata - Support for multiple assignment strategies (range, roundrobin, sticky) - Fallback to 'test-topic' only if parsing fails - Added detailed debug logging for subscription extraction ## Protocol Compliance: - Follows Kafka JoinGroup protocol specification - Proper handling of consumer protocol metadata format - Support for static membership (group instance ID) - Robust error handling for malformed requests ## Testing: - Compilation successful - Debug logging will show actual parsed protocols and subscriptions - Should enable real consumer group coordination with proper topic assignments This fix resolves the third critical compatibility issue preventing real Kafka consumers from joining groups and getting correct partition assignments.
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.