如何产生一个Kafkaavro记录完全一样生产使用avro控制台生产者?

zwghvu4y  于 2021-06-07  发布在  Kafka
关注(0)|答案(2)|浏览(360)

我正在使用confluent 3.3.0。我的意图是使用kafka connect将kafka主题中的值插入到oracle表中。我的连接器与我使用avro控制台生产商制作的avro唱片配合良好,如下所示:

./kafka-avro-console-producer --broker-list 192.168.0.1:9092 --topic topic6 --property value.schema='{"type":"record","name":"flights3","fields":[{"name":"flight_id","type":"string"},{"name":"flight_to", "type": "string"}, {"name":"flight_from", "type": "string"}]}'

我插入如下值:

{"flight_id":"1","flight_to":"QWE","flight_from":"RTY"}

我试图实现的是使用java应用程序插入相同的数据,使用对象。以下是我的生产商代码:

public class Sender {
    public static void main(String[] args) {
        Properties props = new Properties();
        props.put("bootstrap.servers", "192.168.0.1:9092");
        props.put("acks", "all");
        props.put("retries", 0);
        props.put("key.serializer", "org.apache.kafka.common.serialization.StringSerializer");
        props.put("value.serializer", "serializers.custom.FlightSerializer");
        props.put("schema.registry.url", "http://192.168.0.1:8081");
        Producer<String, Flight> producer = new KafkaProducer<String, Flight>(props);
        Flight myflight = new Flight("testflight1","QWE","RTY");
        ProducerRecord<String, Flight> record = new ProducerRecord<String, Flight>("topic5","key",myflight);

        try {
            producer.send(record).get();
        } catch (Exception e) {
            e.printStackTrace();
        }
    }
}

以下是航班vo:

package vo;

public class Flight {
    String flight_id,flight_to,flight_from;

    public Flight(String flight_id, String flight_to, String flight_from) {
        this.flight_id = flight_id;
        this.flight_to = flight_to;
        this.flight_from = flight_from;
    }

    public Flight(){
    }

    public String getFlight_id() {
        return flight_id;
    }

    public void setFlight_id(String flight_id) {
        this.flight_id = flight_id;
    }

    public String getFlight_to() {
        return flight_to;
    }

    public void setFlight_to(String flight_to) {
        this.flight_to = flight_to;
    }

    public String getFlight_from() {
        return flight_from;
    }

    public void setFlight_from(String flight_from) {
        this.flight_from = flight_from;
    }
}

最后,序列化程序:

package serializers.custom;

import java.util.Map;
import org.apache.kafka.common.serialization.Serializer;
import vo.Flight;
import com.fasterxml.jackson.databind.ObjectMapper;

public class FlightSerializer implements Serializer<Flight> {
    @Override
    public void close() {
    }

    @Override
    public void configure(Map<String, ?> arg0, boolean arg1) {
    }

    @Override
    public byte[] serialize(String arg0, Flight arg1) {
        byte[] retVal = null;
        ObjectMapper objectMapper = new ObjectMapper();

        try {
            retVal = objectMapper.writeValueAsString(arg1).getBytes();
        } catch (Exception e) {
            e.printStackTrace();
        }

        return retVal;
    }
}

但我所理解的是,需要定义一些类似schema的东西,并使用一些avro序列化程序来获取确切的数据,就像我使用avro控制台console consumer那样。我看过一些示例代码,但没有一个对我有用。

编辑

我尝试了以下代码。但没有什么是来在avro控制台消费者。

package producer.serialized.avro;

import org.apache.avro.Schema;
import org.apache.avro.generic.GenericData;
import org.apache.avro.generic.GenericRecord;
import org.apache.kafka.clients.producer.KafkaProducer;
import org.apache.kafka.clients.producer.ProducerConfig;
import org.apache.kafka.clients.producer.ProducerRecord;
import vo.Flight;
import java.util.Properties;

public class Sender {
public static void main(String[] args) {
String flightSchema = "{\"type\":\"record\"," + "\"name\":\"flights\","
+ "\"fields\":[{\"name\":\"flight_id\",\"type\":\"string\"},{\"name\":\"flight_to\",\"type\":\"string\"},{\"name\":\"flight_from\",\"type\":\"string\"}]}";
Properties props = new Properties();
props.put(ProducerConfig.BOOTSTRAP_SERVERS_CONFIG, "192.168.0.1:9092");
props.put(ProducerConfig.KEY_SERIALIZER_CLASS_CONFIG,io.confluent.kafka.serializers.KafkaAvroSerializer.class);
props.put(ProducerConfig.VALUE_SERIALIZER_CLASS_CONFIG,io.confluent.kafka.serializers.KafkaAvroSerializer.class);
props.put("schema.registry.url", "http://192.168.0.1:8081");
KafkaProducer producer = new KafkaProducer(props);
Schema.Parser parser = new Schema.Parser();
Schema schema = parser.parse(flightSchema);
GenericRecord avroRecord = new GenericData.Record(schema);
avroRecord.put("flight_id", "1");
avroRecord.put("flight_to", "QWE");
avroRecord.put("flight_from", "RTY");
ProducerRecord<String, GenericRecord> record = new ProducerRecord<>("topic6", avroRecord);

try {
producer.send(record);
} catch (Exception e) {
e.printStackTrace();
}
}
}
o2g1uqev

o2g1uqev1#

架构没有定义,所以 KafkaAvroSerializer 必须联系架构注册表才能提交该架构—它将不具有该架构。
你必须为你的对象创建一个模式 Flight 下面的file.avdl(avro扩展名文件之一)示例可以:

@namespace("vo")
protocol FlightSender {

    record Flight {
       union{null, string} flight_id = null;
       union{null, string} flight_to = null;
       union{null, string} flight_from = null;
    }
}

见avro idl文件
在编译时,当您使用 avro-maven-plugin ,上面的avro模式将生成您的java Flight 类,因此必须删除以前创建的。
当涉及到主类时,必须设置如下两个属性:

props.put(ProducerConfig.KEY_SERIALIZER_CLASS_CONFIG,io.confluent.kafka.serializers.KafkaAvroSerializer.class);
props.put(ProducerConfig.VALUE_SERIALIZER_CLASS_CONFIG,io.confluent.kafka.serializers.KafkaAvroSerializer.class);

和你的制作人,你可以使用你生成的,特定的avro类

Producer<String, Flight> producer = new KafkaProducer<String, Flight>(props);

希望有帮助:-)

e4yzc0pl

e4yzc0pl2#

准确的数据就像我使用avro控制台一样
你可以看看它的源代码
假设你想使用通用记录,这一切都是正确的,

Properties props = new Properties();
props.put(ProducerConfig.BOOTSTRAP_SERVERS_CONFIG, "192.168.0.1:9092");
...
props.put(ProducerConfig.VALUE_SERIALIZER_CLASS_CONFIG,io.confluent.kafka.serializers.KafkaAvroSerializer.class);
props.put("schema.registry.url", "http://192.168.0.1:8081");

Producer<String, GenericRecord> producer = new KafkaProducer<>(props);

...

GenericRecord avroRecord = new GenericData.Record(schema);
avroRecord.put("flight_id", "1");
avroRecord.put("flight_to", "QWE");
avroRecord.put("flight_from", "RTY");
ProducerRecord<String, GenericRecord> record = new ProducerRecord<>("topic6", avroRecord);

try {
    producer.send(record);
} catch (Exception e) {
    e.printStackTrace();
}

但你错过了一个电话 producer.flush() 以及 producer.close() 最后实际发送该批记录

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