问题描述
Kafka是常用的消息中间件。在Spring Boot项目中，使用KafkaTemplate作为生产者发送消息。有时，为了不影响主业务流程，会采用异步发送的方式，如下所示。
@Slf4j
@Component
public class KafkaSender {
@Resource
private KafkaTemplate<String, String> kafkaTemplate;
public void sendAsync(String topic, String message) {
kafkaTemplate.send(topic, message)
.addCallback(
sendResult -> log.info("Send success"),
e -> log.error("Send failed", e));
}
}
本以为采用异步发送，必然不会影响到主业务流程。但实际使用时发现，在第一次发送消息时，如果Kafka Broker连接失败，调用sendAsync()方法的主线程会长时间阻塞。这点是出乎意料的。
原因分析
跟踪源码可知，Kafka生产者在第一次发送消息时，会尝试从Broker获取元数据Metadata（见KafkaProducer的waitOnMetadata()方法），如果Broker连接失败，则会一直阻塞于此，循环尝试获取，直至超时（超时时间由max.block.ms定义）。
/**
* Wait for cluster metadata including partitions for the given topic to be available.
* @param topic The topic we want metadata for
* @param partition A specific partition expected to exist in metadata, or null if there's no preference
* @param nowMs The current time in ms
* @param maxWaitMs The maximum time in ms for waiting on the metadata
* @return The cluster containing topic metadata and the amount of time we waited in ms
* @throws TimeoutException if metadata could not be refreshed within {@code max.block.ms}
* @throws KafkaException for all Kafka-related exceptions, including the case where this method is called after producer close
*/
private ClusterAndWaitTime waitOnMetadata(String topic, Integer partition, long nowMs, long maxWaitMs) throws InterruptedException {
// add topic to metadata topic list if it is not there already and reset expiry
Cluster cluster = metadata.fetch();
if (cluster.invalidTopics().contains(topic))
throw new InvalidTopicException(topic);
metadata.add(topic, nowMs);
Integer partitionsCount = cluster.partitionCountForTopic(topic);
// Return cached metadata if we have it, and if the record's partition is either undefined
// or within the known partition range
if (partitionsCount != null && (partition == null || partition < partitionsCount))
return new ClusterAndWaitTime(cluster, 0);
long remainingWaitMs = maxWaitMs;
long elapsed = 0;
// Issue metadata requests until we have metadata for the topic and the requested partition,
// or until maxWaitTimeMs is exceeded. This is necessary in case the metadata
// is stale and the number of partitions for this topic has increased in the meantime.
do {
if (partition != null) {
log.trace("Requesting metadata update for partition {} of topic {}.", partition, topic);
} else {
log.trace("Requesting metadata update for topic {}.", topic);
}
metadata.add(topic, nowMs + elapsed);
int version = metadata.requestUpdateForTopic(topic);
sender.wakeup();
try {
metadata.awaitUpdate(version, remainingWaitMs);
} catch (TimeoutException ex) {
// Rethrow with original maxWaitMs to prevent logging exception with remainingWaitMs
throw new TimeoutException(
String.format("Topic %s not present in metadata after %d ms.",
topic, maxWaitMs));
}
cluster = metadata.fetch();
elapsed = time.milliseconds() - nowMs;
if (elapsed >= maxWaitMs) {
throw new TimeoutException(partitionsCount == null ?
String.format("Topic %s not present in metadata after %d ms.",
topic, maxWaitMs) :
String.format("Partition %d of topic %s with partition count %d is not present in metadata after %d ms.",
partition, topic, partitionsCount, maxWaitMs));
}
metadata.maybeThrowExceptionForTopic(topic);
remainingWaitMs = maxWaitMs - elapsed;
partitionsCount = cluster.partitionCountForTopic(topic);
} while (partitionsCount == null || (partition != null && partition >= partitionsCount));
return new ClusterAndWaitTime(cluster, elapsed);
}
也就是说，Kafka生产者在发送消息前，要先获取到Metadata。对于异步发送，虽然消息发送的过程是非阻塞的，但获取Metadata的过程是阻塞的。如果因为Broker连接失败、Topic未创建等原因而一直获取不到Metadata，主线程将长时间阻塞。
解决办法
解决办法也很简单。如果Kafka发送消息并非关键业务，为了不影响主业务流程的进行，可以创建线程池来专门执行消息发送工作，保证sendAsync()方法一定是异步执行的。注意，线程池大小和工作队列长度需要合理限定，避免因阻塞任务过多而OOM；拒绝策略可以视情况选择DiscardPolicy。
另外，还可以考虑指定max.block.ms，来限制获取Metadata的最大阻塞时间（默认60000ms）：
spring:
kafka:
producer:
properties:
max.block.ms: 1000
实际上，在异步发送消息的过程中，除了因为获取不到Metadata而阻塞外，还可能因为消息缓冲池已满而阻塞（参考：Kafka Producer 异步发送消息居然也会阻塞？）。这2种阻塞的超时时间均由max.block.ms定义。文章来源：https://www.toymoban.com/news/detail-412084.html
总结
Kafka生产者异步发送消息的方法（如Spring Boot中的kafkaTemplate.send()），看似异步，实则可能阻塞。由于发送消息前需要获取元数据Metadata，如果一直获取失败（可能原因包括Broker连接失败、Topic未创建等），将导致长时间阻塞。这点与我们的一般理解不符，需要特别注意。文章来源地址https://www.toymoban.com/news/detail-412084.html
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