Fault Tolerance Guarantees of Data Sources and Sinks 数据源和接收器的容错保证

Flink’s fault tolerance mechanism recovers programs in the presence of failures and continues to execute them. Such failures include machine hardware failures, network failures, transient program failures, etc. Flink的容错机制在出现故障时恢复程序并继续执行它们。这些故障包括机器硬件故障，网络故障，瞬时程序故障等。

Flink can guarantee exactly-once state updates to user-defined state only when the source participates in the snapshotting mechanism. The following table lists the state update guarantees of Flink coupled with the bundled connectors. 仅当源参与快照机制时，Flink才能保证将一次准确的状态更新为用户定义的状态。下表列出了Flink和捆绑的连接器的状态更新保证。

Please read the documentation of each connector to understand the details of the fault tolerance guarantees. 请阅读每个连接器的文档以了解容错保证的详细信息。

Source Guarantees Notes
Apache Kafka exactly once Use the appropriate Kafka connector for your version
AWS Kinesis Streams exactly once
RabbitMQ at most once (v 0.10) / exactly once (v 1.0)
Twitter Streaming API at most once
Collections exactly once
Files exactly once
Sockets at most once

To guarantee end-to-end exactly-once record delivery (in addition to exactly-once state semantics), the data sink needs to take part in the checkpointing mechanism. The following table lists the delivery guarantees (assuming exactly-once state updates) of Flink coupled with bundled sinks: 为了保证端到端的一次精确记录传递（除了一次精确的状态语义），数据接收器需要参与检查点机制。下表列出了Flink和捆绑的接收器的交付保证（假设一次状态更新）：

Sink Guarantees Notes
HDFS rolling sink exactly once Implementation depends on Hadoop version
Elasticsearch at least once
Kafka producer at least once
Cassandra sink at least once / exactly once exactly once only for idempotent updates
AWS Kinesis Streams at least once
File sinks at least once
Socket sinks at least once
Standard output at least once
Redis sink at least once