Apache Kafka:在 0.10 版中恰好只有一次 [英] Apache Kafka: Exactly Once in Version 0.10

问题描述

为了实现 Kafka 消费者对消息的一次处理，我一次提交一条消息，如下所示

To achieve exactly-once processing of messages by Kafka consumer I am committing one message at a time, like below

public void commitOneRecordConsumer(long seconds) {
        KafkaConsumer<String, String> consumer = consumerConfigFactory.getConsumerConfig();

        try {

            while (running) {
                ConsumerRecords<String, String> records = consumer.poll(1000);
                try {
                    for (ConsumerRecord<String, String> record : records) {

                        processingService.process(record);

                        consumer.commitSync(Collections.singletonMap(new TopicPartition(record.topic(),record.partition()), new OffsetAndMetadata(record.offset() + 1)));

                        System.out.println("Committed Offset" + ": " + record.offset());

                    }
                } catch (CommitFailedException e) {
                    // application specific failure handling
                }
            }
        } finally {
            consumer.close();
        }
    }

上面的代码将消息的处理异步委托给下面的另一个类.

The above code delegates the processing of message asynchronously to another class below.

@Service
public class ProcessingService {

    @Async
    public void process(ConsumerRecord<String, String> record) throws InterruptedException {
        Thread.sleep(5000L);
        Map<String, Object> map = new HashMap<>();
        map.put("partition", record.partition());
        map.put("offset", record.offset());
        map.put("value", record.value());
        System.out.println("Processed" + ": " + map);
    }

}

但是，这仍然不能保证一次传递，因为如果处理失败，它可能仍然提交其他消息，而之前的消息将永远不会被处理和提交，我在这里有什么选择?

However, this still does not guarantee exactly-once delivery, because if the processing fails, it might still commit other messages and the previous messages will never be processed and committed, what are my options here?

推荐答案

针对 0.10.2 及更早版本的原始答案(对于 0.11 及更高版本，请参阅答案吹)

目前，Kafka 无法提供开箱即用的一次性处理.如果在成功处理消息后提交消息，则可以进行至少一次处理，或者如果在开始处理之前直接在 poll() 之后提交消息，则可以进行至多一次处理.

Currently, Kafka cannot provide exactly-once processing out-of-the box. You can either have at-least-once processing if you commit messages after you successfully processed them, or you can have at-most-once processing if you commit messages directly after poll() before you start processing.

(另请参阅 交付保证"="noreferrer">http://docs.confluent.io/3.0.0/clients/consumer.html#synchronous-commits)

(see also paragraph "Delivery Guarantees" in http://docs.confluent.io/3.0.0/clients/consumer.html#synchronous-commits)

然而，至少一次保证足够好"；如果您的处理是幂等的，即即使您处理记录两次，最终结果也将相同.幂等处理的示例是将消息添加到键值存储.即使你两次添加相同的记录，第二次插入只会替换第一个当前的键值对，KV-store 中仍然会有正确的数据.

However, at-least-once guarantee is "good enough" if your processing is idempotent, i.e., the final result will be the same even if you process a record twice. Examples for idempotent processing would be adding a message to a key-value store. Even if you add the same record twice, the second insert will just replace the first current key-value-pair and the KV-store will still have the correct data in it.

在上面的示例代码中，您更新了一个 HashMap，这将是一个幂等操作.即使您可能在失败的情况下出现不一致的状态，例如在崩溃之前只执行了两个 put 调用.但是，这种不一致的状态将在再次重新处理同一记录时得到修复.

In your example code above, you update a HashMap and this would be an idempotent operation. Even if your might have an inconsistent state in case of failure if for example only two put calls are executed before the crash. However, this inconsistent state would be fixed on reprocessing the same record again.

对 println() 的调用不是幂等的，因为这是一个具有副作用"的操作.但我想打印仅用于调试目的.

The call to println() is not idempotent though because this is an operation with "side effect". But I guess the print is for debugging purpose only.

作为替代方案，您需要在您的用户代码中实现事务语义，这需要撤消"(部分执行)失败时的操作.总的来说，这是一个难题.

As an alternative, you would need to implement transaction semantics in your user code which requires to "undo" (partly executed) operation in case of failure. In general, this is a hard problem.

Apache Kafka 0.11+ 的更新(对于 0.11 之前的版本，请参阅上面的答案)

从 0.11 开始，Apache Kafka 支持使用 Kafka Streams 的幂等生产者、事务性生产者和一次性处理.它还为消费者添加了一个 read_committed" 模式，以仅读取已提交的消息(并删除/过滤中止的消息).

Since 0.11, Apache Kafka supports idempotent producers, transactional producer, and exactly-once-processing using Kafka Streams. It also adds a "read_committed" mode to the consumer to only read committed messages (and to drop/filter aborted messages).

• https://kafka.apache.org/documentation/#semantics
• https://www.confluent.io/blog/exactly-once-semantics-are-possible-heres-how-apache-kafka-does-it/
• https://www.confluent.io/blog/transactions-apache-kafka/
• https://www.confluent.io/blog/enabling-exactly-kafka-streams/

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