Avro + Kafka Native API

  1. 比较繁琐
    • 编译Schema
    • 依赖于Avro实现自定义的序列化器和反序列化器

引入依赖

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<dependency>
    <groupId>com.twitter</groupId>
    <artifactId>bijection-avro_2.12</artifactId>
    <version>0.9.6</version>
</dependency>

Schema

路径：src/main/resources/user.json

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{
  "type": "record",
  "name": "User",
  "fields": [
    {"name": "id", "type": "int"},
    {"name": "name",  "type": "string"},
    {"name": "age", "type": "int"}
  ]
}

发送消息

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String schemaFilePath = BijectionProducer.class.getClassLoader().getResource("user.json").getPath();
Schema schema = new Schema.Parser().parse(new File(schemaFilePath));
Injection<GenericRecord, byte[]> recordInjection = GenericAvroCodecs.toBinary(schema);

Properties props = new Properties();
props.put("bootstrap.servers", "localhost:9092");
props.put("key.serializer", StringSerializer.class.getName());
props.put("value.serializer", ByteArraySerializer.class.getName());
Producer<String, byte[]> producer = new KafkaProducer<>(props);

for (int i = 0; i < 10; i++) {
    GenericData.Record record = new GenericData.Record(schema);
    record.put("id", i);
    record.put("name", TOPIC + i);
    record.put("age", i);
    byte[] bytes = recordInjection.apply(record);
    ProducerRecord<String, byte[]> producerRecord = new ProducerRecord<>(TOPIC, bytes);
    RecordMetadata metadata = producer.send(producerRecord).get();
    log.info("id={}, timestamp={}, partition={}, offset={}",
            record.get("id"), metadata.timestamp(), metadata.partition(), metadata.offset());
}
producer.close();

消费消息

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String schemaFilePath = BijectionProducer.class.getClassLoader().getResource("user.json").getPath();
Schema schema = new Schema.Parser().parse(new File(schemaFilePath));
Injection<GenericRecord, byte[]> recordInjection = GenericAvroCodecs.toBinary(schema);

Properties props = new Properties();
props.put("bootstrap.servers", "localhost:9092");
props.put("key.serializer", StringSerializer.class.getName());
props.put("value.serializer", ByteArraySerializer.class.getName());
Producer<String, byte[]> producer = new KafkaProducer<>(props);

for (int i = 0; i < 10; i++) {
    GenericData.Record record = new GenericData.Record(schema);
    record.put("id", i);
    record.put("name", TOPIC + i);
    record.put("age", i);
    byte[] bytes = recordInjection.apply(record);
    ProducerRecord<String, byte[]> producerRecord = new ProducerRecord<>(TOPIC, bytes);
    RecordMetadata metadata = producer.send(producerRecord).get();
    log.info("id={}, timestamp={}, partition={}, offset={}",
            record.get("id"), metadata.timestamp(), metadata.partition(), metadata.offset());
}
producer.close();