librdkafka生产者如何了解Kafka中的新主题分区 [英] How does librdkafka producer learn about new topic partitions in Kafka

问题描述

我正在运行 rdkafka_simple_producer.c 来向 Kafka 集群生成消息.我有一个主题和 30 个分区.使用默认的循环分区器.当生产者正在工作并向 Kafka 生成消息时，我向 Kafka 添加了更多分区

I'm running rdkafka_simple_producer.c to produce messages to a Kafka cluster. I have one topic and 30 partitions. Using the default round-robin partitioner. While the producer is working and generating messages to Kafka, I add more partitions to Kafka

kafka/bin/kafka-topics.sh --alter --zookeeper server2:2181 --topic demotest --partitions 40

我希望制作人能够意识到这一变化，并最终开始制作所有 40 个主题.但是，最后我只看到数据生成到原来的 30 个分区.

I'd expect the producer to realize about the change and eventually begin to produce to all 40 topics. However, at the end I only see data was produced to the original 30 partitions.

在测试中，生产者运行了 2 分钟.

In the test the producer ran for 2 minutes.

我需要在 simple_producer 中添加任何函数调用还是我需要考虑的 Kafka 参数?

Do I need to add any function call in the simple_producer or is it a Kafka parameter I need to consider?

提前致谢！

推荐答案

这个问题我终于有了答案.实际上，生产者会定期刷新有关元数据的信息.间隔由配置参数topic.metadata.refresh.interval.ms定义

I finally have a response for this question. Actually the producer is refreshed periodically about metadata. The interval is defined by configuration parameter topic.metadata.refresh.interval.ms

topic.metadata.refresh.interval.ms 的默认值为 300000(以毫秒为单位).这是 5 分钟，测试只持续了 2 分钟.生产者将在元数据刷新后自动识别新添加的分区.

The value of topic.metadata.refresh.interval.ms is 300000 (in ms) by default. This is 5 minutes and test lasted only 2 minutes. The producer will recognize the new added partitions automatically after the metadata refresh.

因此，对于遇到相同问题的任何人，您都可以配置此参数以加快元数据刷新.无需编码，只需通过以下方式设置此值:

So, for anybody with the same problem, you can configure this parameter to have faster metadata refresh. No coding needed more than setting this value with:

rd_kafka_conf_set(conf, "topic.metadata.refresh.interval.ms", "15000",
                          errstr, sizeof(errstr)) != RD_KAFKA_CONF_OK)

当然，您需要考虑这意味着代理和生产者之间有更多的消息传递.更多关于 librdkafka 配置:librdkafka 配置

Of course, you need to consider this implies more messaging between a broker and a producer. More on librdkafka configuration: librdkafka configuration

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