自动提交
手动同步提交
while (true) {
ConsumerRecords<String, String> records =
consumer.poll(Duration.ofSeconds(1));
process(records); // 处理消息
try {
consumer.commitSync();
} catch (CommitFailedException e) {
handle(e); // 处理提交失败异常
}
}
手动异步提交
while (true) {
ConsumerRecords<String, String> records =
consumer.poll(Duration.ofSeconds(1));
process(records); // 处理消息
consumer.commitAsync((offsets, exception) -> {
if (exception != null)
handle(exception);
});
}
手动提交位移
try {
while(true) {
ConsumerRecords<String, String> records =
consumer.poll(Duration.ofSeconds(1));
process(records); // 处理消息
commitAysnc(); // 使用异步提交规避阻塞
}
} catch(Exception e) {
handle(e); // 处理异常
} finally {
try {
consumer.commitSync(); // 最后一次提交使用同步阻塞式提交
} finally {
consumer.close();
}
}
手动自由提交偏移量
private Map<TopicPartition, OffsetAndMetadata> offsets = new HashMap<>();
int count = 0;
……
while (true) {
ConsumerRecords<String, String> records =
consumer.poll(Duration.ofSeconds(1));
for (ConsumerRecord<String, String> record: records) {
process(record); // 处理消息
offsets.put(new TopicPartition(record.topic(), record.partition()),
new OffsetAndMetadata(record.offset() + 1);
if(count % 100 == 0)
consumer.commitAsync(offsets, null); // 回调处理逻辑是 null
count++;
}
}
本文深入探讨Kafka消费者的不同提交策略,包括自动提交、手动同步提交、手动异步提交及自由提交偏移量的方式。解析每种提交方式的实现细节与应用场景,帮助开发者理解如何选择合适的提交策略以优化消费流程。
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