Comments (1)
Context
Initial idea of implementing error recovery was to have single point, in tcp connection object where all error recovery would be made.
But it turned out too low level, because depending on what this connection is doing, we might want different strategy for recovery.
When RecoveryMonitor tests either broker is available, we do not want any recovery and want fail fast instead.
Another issue is that currently only fetcher and producer are well protected, whereas earlier stages, such as connection, offset resolution,
metadata fetching are more fragile, or have to implement their own recovery, thus polluting the code.
Requirements
Fast reaction: consider partition failed immediately after tcp error, and not after many retries.
Remember to fail all request tasks which are waiting for responses.
While waiting for recovery, pay attention to changes in metadata
Work nicely with shutdown and drain logic
List of failure stages
- In seed broker resolution
- In offset resolution
- In Metadata fetching
- In recovery monitor
- In produce message
- In fetch message
from kafka4net.
Related Issues (20)
- How to start consuming with a specific offset. HOT 6
- Producer throws exception when sending a lot of messages HOT 3
- Memory leak HOT 19
- Closing and opening connection right after, throws exception
- Producer starts writing to the same single partition (when no Message.Key is specified) HOT 1
- Producer stops working after manual partition reassignment HOT 5
- Memory leak in producer HOT 1
- ObjectDisposedException after closing producer HOT 6
- Sample consumer code for multi-topic subscription HOT 2
- How should I handle the situation when Kafka starts re-balancing data on brokers. HOT 4
- Implement protocol v1 and v2 (aka kafka-0.9 and 0.10) HOT 3
- Better backward comptibility when enhancing configuration classes
- Upgrade to System.Reactive 3 HOT 2
- Consumer flow control is broken HOT 2
- Consumer subscription to messages lost HOT 4
- Idle Connections getting closed are logged as Error
- Cannot configure Tcp Keepalive HOT 1
- Use RecyclableMemoryStream instead of MemoryStream HOT 4
- Huge memory and threads consumption HOT 5
- Upgrade to System.Reactive 4
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from kafka4net.