Kafka消费者重置offset读取数据

1public class KafkaConsumer2 {
2
3    public static void main(String[] args) {
4        Properties props = new Properties();
5        props.put("bootstrap.servers", "127.0.0.1:9092");
6        props.put("group.id", "one");
7        props.put("enable.auto.commit", true);
8        props.put("auto.commit.interval.ms", 5000);
9        props.put("session.timeout.ms", 50000);
10        props.put("key.deserializer", "org.apache.kafka.common.serialization.StringDeserializer");
11        props.put("value.deserializer", "org.apache.kafka.common.serialization.StringDeserializer");
12        //设置使用最开始的offset偏移量为该group.id的最早。如果不设置，则会是latest即该topic最新一个消息的offset
13        //如果采用latest，消费者只能得道其启动后，生产者生产的消息
14//        props.put("auto.offset.reset", "earliest");
15        props.put("auto.offset.reset", "latest");
16        KafkaConsumer<String, String> consumer =  new KafkaConsumer(props);
17        try {
18            String topicName = "mykafka";
19            //重置offset，可同时设置多个topic和partition
20            Map<TopicPartition, OffsetAndMetadata> hashMaps = new HashMap<TopicPartition, OffsetAndMetadata>();
21            hashMaps.put(new TopicPartition(topicName, 0), new OffsetAndMetadata(2));
22            consumer.commitSync(hashMaps);
23            //启动订阅
24            consumer.subscribe(Arrays.asList(topicName));
25            while (true) {
26                ConsumerRecords<String, String> records = consumer.poll(Long.MAX_VALUE);
27                for (ConsumerRecord<String, String> record : records) {
28                    String value = record.value();
29                    long offset = record.offset();
30                    int partition = record.partition();
31                    String topic = record.topic();
32                    String f="-------->>>topic=%s,offset=%s,partition=%s,value=%s";
33                    System.out.println(String.format(f,topic,offset,partition,value));
34                }
35                consumer.commitSync();
36            }
37        } catch (Exception e) {
38            e.printStackTrace();
39        }finally {
40            if(consumer != null){
41                consumer.close();
42            }
43        }
44    }
45}
46
47public class KafkaProudcer2 {
48
49    public static void main(String[] args) {
50        Properties props = new Properties();
51        props.put("bootstrap.servers", "127.0.0.1:9092");
52        props.put("retries", 3);
53        props.put("linger.ms", 1);
54        props.put("key.serializer",   "org.apache.kafka.common.serialization.StringSerializer");
55        props.put("value.serializer",  "org.apache.kafka.common.serialization.StringSerializer");
56        KafkaProducer<String, String> producer = new KafkaProducer<String, String>(props);
57        while (true){
58            String topicName = "mykafka";
59            ProducerRecord<String, String> record = new ProducerRecord<String, String>(
60                    topicName, System.currentTimeMillis()+"", "今天天气不错哟yoyo=======>");
61            producer.send(record, new Callback() {
62                public void onCompletion(RecordMetadata metadata, Exception e) {
63                    if (e != null)
64                        System.out.println("the producer has a error:" + e.getMessage());
65                    else {
66                        String f="----------->>>partition=%s,offset=%s";
67                        System.out.println(String.format(f,metadata.partition(),metadata.offset()));
68                    }
69                }
70            });
71            try {
72                Thread.sleep(1000);
73            } catch (InterruptedException e1) {
74                e1.printStackTrace();
75            }
76        }
77        // producer.close();
78    }
79}